From 29254ebe0d7deb5c5091853970d3bbc34579c5f6 Mon Sep 17 00:00:00 2001
From: kolinwei <331911734@qq.com>
Date: Mon, 23 Apr 2018 14:51:41 +0800
Subject: [PATCH 001/195] Update stacked_dynamic_lstm.py
---
benchmark/fluid/stacked_dynamic_lstm.py | 6 +++---
1 file changed, 3 insertions(+), 3 deletions(-)
diff --git a/benchmark/fluid/stacked_dynamic_lstm.py b/benchmark/fluid/stacked_dynamic_lstm.py
index 5fcbdd64af..73bcc47b4d 100644
--- a/benchmark/fluid/stacked_dynamic_lstm.py
+++ b/benchmark/fluid/stacked_dynamic_lstm.py
@@ -23,10 +23,10 @@ import random
import time
import numpy
-import paddle.v2 as paddle
-import paddle.v2.dataset.imdb as imdb
+import paddle
+import paddle.dataset.imdb as imdb
import paddle.fluid as fluid
-from paddle.v2 import batch
+import paddle.batch as batch
import paddle.fluid.profiler as profiler
From 44b460919c1794a70c2d6b4fa175512b91711464 Mon Sep 17 00:00:00 2001
From: kolinwei <331911734@qq.com>
Date: Mon, 23 Apr 2018 14:52:26 +0800
Subject: [PATCH 002/195] Update machine_translation.py
---
benchmark/fluid/machine_translation.py | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/benchmark/fluid/machine_translation.py b/benchmark/fluid/machine_translation.py
index d7a421c109..adde5f21ac 100644
--- a/benchmark/fluid/machine_translation.py
+++ b/benchmark/fluid/machine_translation.py
@@ -21,7 +21,7 @@ import argparse
import time
import distutils.util
-import paddle.v2 as paddle
+import paddle
import paddle.fluid as fluid
import paddle.fluid.core as core
import paddle.fluid.framework as framework
From dd680c69e70e75e099471eeab405d29130961d44 Mon Sep 17 00:00:00 2001
From: kolinwei <331911734@qq.com>
Date: Mon, 23 Apr 2018 14:52:51 +0800
Subject: [PATCH 003/195] Update mnist.py
---
benchmark/fluid/mnist.py | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/benchmark/fluid/mnist.py b/benchmark/fluid/mnist.py
index dc10ac2ec1..1e2185dfac 100644
--- a/benchmark/fluid/mnist.py
+++ b/benchmark/fluid/mnist.py
@@ -20,7 +20,7 @@ import numpy as np
import argparse
import time
-import paddle.v2 as paddle
+import paddle
import paddle.fluid as fluid
import paddle.fluid.profiler as profiler
From e964164e36010657aeea67a64ebb416d5ea87c59 Mon Sep 17 00:00:00 2001
From: kolinwei <331911734@qq.com>
Date: Mon, 23 Apr 2018 14:53:11 +0800
Subject: [PATCH 004/195] Update resnet.py
---
benchmark/fluid/resnet.py | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/benchmark/fluid/resnet.py b/benchmark/fluid/resnet.py
index 1af5eaf6b4..831fa2c019 100644
--- a/benchmark/fluid/resnet.py
+++ b/benchmark/fluid/resnet.py
@@ -23,7 +23,7 @@ import time
import cProfile, pstats, StringIO
-import paddle.v2 as paddle
+import paddle
import paddle.fluid as fluid
import paddle.fluid.core as core
import paddle.fluid.profiler as profiler
From d7762b65de4f17dc702ac765b345911121093a67 Mon Sep 17 00:00:00 2001
From: kolinwei <331911734@qq.com>
Date: Mon, 23 Apr 2018 14:53:48 +0800
Subject: [PATCH 005/195] Update vgg.py
---
benchmark/fluid/vgg.py | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/benchmark/fluid/vgg.py b/benchmark/fluid/vgg.py
index 9d990eff62..53e34e0cbd 100644
--- a/benchmark/fluid/vgg.py
+++ b/benchmark/fluid/vgg.py
@@ -17,7 +17,7 @@ from __future__ import print_function
import sys
import time
import numpy as np
-import paddle.v2 as paddle
+import paddle
import paddle.fluid as fluid
import paddle.fluid.core as core
import argparse
From 25d5e226ab6716a403251d0d216bfdf833f0d218 Mon Sep 17 00:00:00 2001
From: Wojciech Uss <wojciech.uss@intel.com>
Date: Wed, 25 Apr 2018 13:30:52 +0200
Subject: [PATCH 006/195] Fix typo in wmt16
---
python/paddle/dataset/wmt16.py | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/python/paddle/dataset/wmt16.py b/python/paddle/dataset/wmt16.py
index ad23338a96..540d43b692 100644
--- a/python/paddle/dataset/wmt16.py
+++ b/python/paddle/dataset/wmt16.py
@@ -96,7 +96,7 @@ def __get_dict_size(src_dict_size, trg_dict_size, src_lang):
src_dict_size = min(src_dict_size, (TOTAL_EN_WORDS if src_lang == "en" else
TOTAL_DE_WORDS))
trg_dict_size = min(trg_dict_size, (TOTAL_DE_WORDS if src_lang == "en" else
- TOTAL_ENG_WORDS))
+ TOTAL_EN_WORDS))
return src_dict_size, trg_dict_size
From eeed7af5c3b6d51399412ba3cd0cab2125b33e90 Mon Sep 17 00:00:00 2001
From: typhoonzero <typhoonzero1986@gmail.com>
Date: Wed, 2 May 2018 20:19:58 +0800
Subject: [PATCH 007/195] add gen_nccl_id_op
---
paddle/fluid/operators/CMakeLists.txt | 7 +-
paddle/fluid/operators/gen_nccl_id_op.cc | 123 ++++++++++++++++++
.../fluid/operators/lookup_sparse_table_op.cc | 2 +-
3 files changed, 130 insertions(+), 2 deletions(-)
create mode 100644 paddle/fluid/operators/gen_nccl_id_op.cc
diff --git a/paddle/fluid/operators/CMakeLists.txt b/paddle/fluid/operators/CMakeLists.txt
index 256aded8ca..ad0732131c 100644
--- a/paddle/fluid/operators/CMakeLists.txt
+++ b/paddle/fluid/operators/CMakeLists.txt
@@ -184,6 +184,11 @@ endif()
add_subdirectory(detail)
if(WITH_DISTRIBUTE)
+ if(WITH_GPU)
+ op_library(gen_nccl_id_op DEPS nccl_common)
+ else()
+ set(DEPS_OPS ${DEPS_OPS} gen_nccl_id_op)
+ endif()
set(DISTRIBUTE_DEPS sendrecvop_grpc grpc++_unsecure grpc_unsecure gpr cares zlib protobuf)
set(DISTRIBUTE_COMPILE_FLAGS "-Wno-non-virtual-dtor -Wno-error=non-virtual-dtor -Wno-error=delete-non-virtual-dtor")
op_library(send_op DEPS ${DISTRIBUTE_DEPS})
@@ -201,7 +206,7 @@ if(WITH_DISTRIBUTE)
set_source_files_properties(send_recv_op_test.cc PROPERTIES COMPILE_FLAGS ${DISTRIBUTE_COMPILE_FLAGS})
cc_test(test_send_recv SRCS send_recv_op_test.cc DEPS prefetch_op send_op listen_and_serv_op sum_op executor)
else()
- set(DEPS_OPS ${DEPS_OPS} send_op prefetch_op recv_op listen_and_serv_op send_vars_op send_barrier_op)
+ set(DEPS_OPS ${DEPS_OPS} send_op prefetch_op recv_op listen_and_serv_op send_vars_op send_barrier_op gen_nccl_id_op)
endif()
op_library(cross_entropy_op DEPS cross_entropy)
diff --git a/paddle/fluid/operators/gen_nccl_id_op.cc b/paddle/fluid/operators/gen_nccl_id_op.cc
new file mode 100644
index 0000000000..e75e045fcb
--- /dev/null
+++ b/paddle/fluid/operators/gen_nccl_id_op.cc
@@ -0,0 +1,123 @@
+/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License. */
+
+#include <nccl.h>
+#include <stdint.h>
+#include <ostream>
+#include <string>
+
+#include "paddle/fluid/framework/executor.h"
+#include "paddle/fluid/framework/lod_tensor.h"
+#include "paddle/fluid/framework/op_registry.h"
+#include "paddle/fluid/framework/threadpool.h"
+#include "paddle/fluid/operators/detail/grpc_client.h"
+#include "paddle/fluid/operators/detail/grpc_server.h"
+
+namespace paddle {
+namespace operators {
+
+class GenNCCLIdOp : public framework::OperatorBase {
+ public:
+ GenNCCLIdOp(const std::string& type, const framework::VariableNameMap& inputs,
+ const framework::VariableNameMap& outputs,
+ const framework::AttributeMap& attrs)
+ : OperatorBase(type, inputs, outputs, attrs) {}
+
+ void RunImpl(const framework::Scope& scope,
+ const platform::Place& dev_place) const override {
+ platform::DeviceContextPool& pool = platform::DeviceContextPool::Instance();
+ auto& dev_ctx = *pool.Get(dev_place);
+ int trainer_id = Attr<int>("trainer_id");
+ framework::Scope& local_scope = scope.NewScope();
+
+ if (trainer_id == 0) {
+ GenerateAndSend(&local_scope, dev_ctx);
+ } else {
+ GetIdByServer(&local_scope, dev_ctx);
+ }
+ }
+
+ private:
+ void GenerateAndSend(framework::Scope* scope,
+ const platform::DeviceContext& dev_ctx) const {
+ auto var = scope->FindVar("NCCLID");
+ PADDLE_ENFORCE_NOT_NULL(var);
+ auto id = var->GetMutable<ncclUniqueId>();
+ ncclGetUniqueId(id);
+
+ std::vector<std::string> endpoint_list =
+ Attr<std::vector<std::string>>("endpoint_list");
+ detail::RPCClient client;
+ for (auto& ep : endpoint_list) {
+ client.AsyncSendVariable(ep, dev_ctx, *scope, "NCCLID");
+ }
+ client.Wait();
+ }
+
+ void GetIdByServer(framework::Scope* scope,
+ const platform::DeviceContext& dev_ctx) const {
+ std::string endpoint = Attr<std::string>("endpoint");
+ rpc_service_.reset(new detail::AsyncGRPCServer(endpoint, true));
+ framework::ProgramDesc empty_program;
+ framework::Executor executor(dev_ctx.GetPlace());
+ rpc_service_->SetScope(scope);
+ rpc_service_->SetDevCtx(&dev_ctx);
+ rpc_service_->SetProgram(&empty_program);
+ rpc_service_->SetExecutor(&executor);
+
+ server_thread_.reset(new std::thread(std::bind(
+ &detail::AsyncGRPCServer::RunSyncUpdate, rpc_service_.get())));
+
+ auto recv = rpc_service_->Get();
+ rpc_service_->ShutDown();
+ // TODO(wuyi): reinit nccl communicators
+ }
+
+ protected:
+ mutable std::shared_ptr<detail::AsyncGRPCServer> rpc_service_;
+ mutable std::shared_ptr<std::thread> server_thread_;
+};
+
+class GenNCCLIdOpMaker : public framework::OpProtoAndCheckerMaker {
+ public:
+ GenNCCLIdOpMaker(OpProto* proto, OpAttrChecker* op_checker)
+ : GenNCCLIdOpMaker(proto, op_checker) {
+ AddOutput("NCCLID", "Raw variable contains a NCCL UniqueId instaces.");
+ AddComment(R"DOC(
+GenNCCLId operator
+
+For trainer 0: generate a new UniqueId and send it to all the other trainers.
+For trainer 1~n: start a gRPC server to get the UniqueId, once got, stop the server.
+)DOC");
+ AddAttr<std::string>("endpoint",
+ "(string), e.g. 127.0.0.1:6175 "
+ "current listen endpoint");
+ AddAttr<std::vector<std::string>>(
+ "endpoint_list",
+ "['trainer1_ip:port', 'trainer2_ip:port', ...] "
+ "list of trainer endpoints start from trainer 1")
+ .SetDefault({});
+ AddAttr<int>("trainer_id",
+ "(int default 0) "
+ "The index of the trainer in distributed training.")
+ .SetDefault(0);
+ }
+};
+
+} // namespace operators
+} // namespace paddle
+
+namespace ops = paddle::operators;
+
+REGISTER_OPERATOR(gen_nccl_id_op, ops::GenNCCLIdOp, ops::GenNCCLIdOpMaker);
diff --git a/paddle/fluid/operators/lookup_sparse_table_op.cc b/paddle/fluid/operators/lookup_sparse_table_op.cc
index f1839e456d..66b626ed79 100644
--- a/paddle/fluid/operators/lookup_sparse_table_op.cc
+++ b/paddle/fluid/operators/lookup_sparse_table_op.cc
@@ -62,7 +62,7 @@ class LookupSparseTableOp : public framework::OperatorBase {
auto w_t = w_var->GetMutable<framework::SelectedRows>();
std::vector<int64_t> keys;
keys.resize(ids_t.numel());
- for (size_t i = 0; i < ids_t.numel(); ++i) {
+ for (int64_t i = 0; i < ids_t.numel(); ++i) {
keys[i] = ids_t.data<int64_t>()[i];
}
From 7237323c5dfb2bac5e55cdf183e27f631d4c1d3d Mon Sep 17 00:00:00 2001
From: typhoonzero <typhoonzero1986@gmail.com>
Date: Thu, 3 May 2018 12:22:21 +0800
Subject: [PATCH 008/195] fix compile
---
paddle/fluid/operators/gen_nccl_id_op.cc | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/paddle/fluid/operators/gen_nccl_id_op.cc b/paddle/fluid/operators/gen_nccl_id_op.cc
index e75e045fcb..235995aeb4 100644
--- a/paddle/fluid/operators/gen_nccl_id_op.cc
+++ b/paddle/fluid/operators/gen_nccl_id_op.cc
@@ -92,7 +92,7 @@ class GenNCCLIdOp : public framework::OperatorBase {
class GenNCCLIdOpMaker : public framework::OpProtoAndCheckerMaker {
public:
GenNCCLIdOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : GenNCCLIdOpMaker(proto, op_checker) {
+ : OpProtoAndCheckerMaker(proto, op_checker) {
AddOutput("NCCLID", "Raw variable contains a NCCL UniqueId instaces.");
AddComment(R"DOC(
GenNCCLId operator
From d9320dcd944bba599135a711113d831551fa4814 Mon Sep 17 00:00:00 2001
From: typhoonzero <typhoonzero1986@gmail.com>
Date: Fri, 4 May 2018 16:23:30 +0800
Subject: [PATCH 009/195] complete code
---
paddle/fluid/framework/parallel_executor.cc | 10 ++++--
paddle/fluid/framework/parallel_executor.h | 3 +-
paddle/fluid/operators/detail/send_recv.proto | 1 +
.../operators/detail/sendrecvop_utils.cc | 21 +++++++++++-
.../operators/detail/variable_response.cc | 11 ++++++-
paddle/fluid/operators/gen_nccl_id_op.cc | 4 +--
paddle/fluid/platform/nccl_helper.h | 32 +++++++++++++++----
paddle/fluid/pybind/pybind.cc | 6 ++--
8 files changed, 73 insertions(+), 15 deletions(-)
diff --git a/paddle/fluid/framework/parallel_executor.cc b/paddle/fluid/framework/parallel_executor.cc
index 4712efeff6..bd2a2cfba5 100644
--- a/paddle/fluid/framework/parallel_executor.cc
+++ b/paddle/fluid/framework/parallel_executor.cc
@@ -58,7 +58,7 @@ ParallelExecutor::ParallelExecutor(
const std::unordered_set<std::string> &bcast_vars,
const ProgramDesc &main_program, const std::string &loss_var_name,
Scope *scope, const std::vector<Scope *> &local_scopes, bool allow_op_delay,
- bool use_default_grad_scale)
+ bool use_default_grad_scale, size_t num_trainers, size_t trainer_id)
: member_(new ParallelExecutorPrivate(places)) {
member_->global_scope_ = scope;
@@ -80,7 +80,13 @@ ParallelExecutor::ParallelExecutor(
// Bcast Parameters to all GPUs
#ifdef PADDLE_WITH_CUDA
- member_->nccl_ctxs_.reset(new platform::NCCLContextMap(member_->places_));
+ auto *nccl_id_var = scope->FindVar("NCCLID");
+ ncclUniqueId *nccl_id = nullptr;
+ if (nccl_id_var != nullptr) {
+ nccl_id = nccl_id_var->GetMutable<ncclUniqueId>();
+ }
+ member_->nccl_ctxs_.reset(new platform::NCCLContextMap(
+ member_->places_, nccl_id, num_trainers, trainer_id));
#endif
if (platform::is_gpu_place(places[0]) && member_->local_scopes_.size() != 1 &&
local_scopes.empty()) { // Is CUDA
diff --git a/paddle/fluid/framework/parallel_executor.h b/paddle/fluid/framework/parallel_executor.h
index ecd107d81f..306d2bdfaf 100644
--- a/paddle/fluid/framework/parallel_executor.h
+++ b/paddle/fluid/framework/parallel_executor.h
@@ -40,7 +40,8 @@ class ParallelExecutor {
const ProgramDesc& main_program,
const std::string& loss_var_name, Scope* scope,
const std::vector<Scope*>& local_scopes,
- bool allow_op_delay, bool use_default_grad_scale);
+ bool allow_op_delay, bool use_default_grad_scale,
+ size_t num_trainers = 0, size_t trainer_id = 0);
~ParallelExecutor();
diff --git a/paddle/fluid/operators/detail/send_recv.proto b/paddle/fluid/operators/detail/send_recv.proto
index 02bb2b9ceb..3b343a7e56 100644
--- a/paddle/fluid/operators/detail/send_recv.proto
+++ b/paddle/fluid/operators/detail/send_recv.proto
@@ -32,6 +32,7 @@ service SendRecvService {
enum VarType {
LOD_TENSOR = 0;
SELECTED_ROWS = 1;
+ NCCL_ID = 2;
}
// NOTICE(gongwb):don't modify this proto if you are not
diff --git a/paddle/fluid/operators/detail/sendrecvop_utils.cc b/paddle/fluid/operators/detail/sendrecvop_utils.cc
index 766bcf1ac5..800d6d8bd2 100644
--- a/paddle/fluid/operators/detail/sendrecvop_utils.cc
+++ b/paddle/fluid/operators/detail/sendrecvop_utils.cc
@@ -43,13 +43,16 @@ void SerializeToByteBuffer(const std::string& name, framework::Variable* var,
void* buf = buffer.get();
void* payload = nullptr;
- size_t payload_size;
+ size_t payload_size = 0;
ProtoEncodeHelper e(static_cast<char*>(buf), 1024);
e.WriteString(VarMsg::kVarnameFieldNumber, name);
if (var->IsType<framework::LoDTensor>()) {
e.WriteUint64(VarMsg::kTypeFieldNumber, 0);
} else if (var->IsType<framework::SelectedRows>()) {
e.WriteUint64(VarMsg::kTypeFieldNumber, 1);
+ } else if (var->IsType<ncclUniqueId>()) {
+ // NOTE: sendrecv only support RAW type for NCCL_ID
+ e.WriteUint64(VarMsg::kTypeFieldNumber, 2);
}
if (!out_name.empty()) {
@@ -139,11 +142,27 @@ void SerializeToByteBuffer(const std::string& name, framework::Variable* var,
payload_size = tensor->numel() * framework::SizeOfType(tensor->type());
e.WriteVarlengthBeginning(VarMsg::kSerializedFieldNumber, payload_size);
} break;
+ case framework::proto::VarType_Type_RAW: {
+ e.WriteVarlengthBeginning(VarMsg::kSerializedFieldNumber,
+ NCCL_UNIQUE_ID_BYTES);
+ ncclUniqueId* uid = var->GetMutable<ncclUniqueId>();
+ e.WriteRawBytes(std::string(uid->internal, NCCL_UNIQUE_ID_BYTES));
+ } break;
default:
PADDLE_THROW("Serialize does not support type: %s",
typeid(var->Type()).name());
break;
}
+
+ if (framework::ToVarType(var->Type()) == framework::proto::VarType_Type_RAW) {
+ // for serialize NCCL_ID
+ ::grpc::Slice slices(e.size());
+ memcpy(const_cast<uint8_t*>(slices.begin()), e.data(), e.size());
+ ::grpc::ByteBuffer tmp(&slices, 1);
+ msg->Swap(&tmp);
+ return;
+ }
+
// steal reference of tensor data
::grpc::Slice slices[4]; // metadata, tensor, rows meta, rows
int num_slices = 2; // only SelectedRows have rows buffer
diff --git a/paddle/fluid/operators/detail/variable_response.cc b/paddle/fluid/operators/detail/variable_response.cc
index fbef8d02a4..81d755f5fc 100644
--- a/paddle/fluid/operators/detail/variable_response.cc
+++ b/paddle/fluid/operators/detail/variable_response.cc
@@ -367,9 +367,18 @@ int VariableResponse::Parse(Source* source) {
}
case sendrecv::VariableMessage::kSerializedFieldNumber: {
PADDLE_ENFORCE((meta_.type() == sendrecv::SELECTED_ROWS ||
- meta_.type() == sendrecv::LOD_TENSOR) &&
+ meta_.type() == sendrecv::LOD_TENSOR ||
+ meta_.type() == sendrecv::NCCL_ID) &&
meta_.varname() != "",
"meta info should be got first!");
+ if (meta_.type() == sendrecv::NCCL_ID) {
+ auto* var = scope_->FindVar(meta_.varname());
+ if (var != nullptr) {
+ ncclUniqueId* id = var->GetMutable<ncclUniqueId>();
+ memcpy(id->internal, meta_.serialized().c_str(),
+ meta_.serialized().size());
+ }
+ }
int length = 0;
if (wt != WIRETYPE_LENGTH_DELIMITED ||
diff --git a/paddle/fluid/operators/gen_nccl_id_op.cc b/paddle/fluid/operators/gen_nccl_id_op.cc
index 235995aeb4..afb228fa6f 100644
--- a/paddle/fluid/operators/gen_nccl_id_op.cc
+++ b/paddle/fluid/operators/gen_nccl_id_op.cc
@@ -54,7 +54,7 @@ class GenNCCLIdOp : public framework::OperatorBase {
auto var = scope->FindVar("NCCLID");
PADDLE_ENFORCE_NOT_NULL(var);
auto id = var->GetMutable<ncclUniqueId>();
- ncclGetUniqueId(id);
+ platform::dynload::ncclGetUniqueId(id);
std::vector<std::string> endpoint_list =
Attr<std::vector<std::string>>("endpoint_list");
@@ -120,4 +120,4 @@ For trainer 1~n: start a gRPC server to get the UniqueId, once got, stop the ser
namespace ops = paddle::operators;
-REGISTER_OPERATOR(gen_nccl_id_op, ops::GenNCCLIdOp, ops::GenNCCLIdOpMaker);
+REGISTER_OPERATOR(gen_nccl_id, ops::GenNCCLIdOp, ops::GenNCCLIdOpMaker);
diff --git a/paddle/fluid/platform/nccl_helper.h b/paddle/fluid/platform/nccl_helper.h
index 0013597fd5..3b52587a28 100644
--- a/paddle/fluid/platform/nccl_helper.h
+++ b/paddle/fluid/platform/nccl_helper.h
@@ -73,7 +73,9 @@ struct NCCLContextMap {
std::unordered_map<int, NCCLContext> contexts_;
std::vector<int> order_;
- explicit NCCLContextMap(const std::vector<platform::Place> &places) {
+ explicit NCCLContextMap(const std::vector<platform::Place> &places,
+ ncclUniqueId *nccl_id = nullptr,
+ size_t node_count = 0, size_t trainer_id = 0) {
PADDLE_ENFORCE(!places.empty());
order_.reserve(places.size());
for (auto &p : places) {
@@ -85,18 +87,36 @@ struct NCCLContextMap {
order_.size(), contexts_.size(),
"NCCL Context Map does not support contain two or more same device");
- if (places.size() > 1) {
- std::unique_ptr<ncclComm_t[]> comms(new ncclComm_t[order_.size()]);
+ if (places.size() <= 1) {
+ return;
+ }
+ std::unique_ptr<ncclComm_t[]> comms(new ncclComm_t[order_.size()]);
+ // if pass nccl_id here, can assume we are doing multi node training
+ if (nccl_id == nullptr) {
{
std::lock_guard<std::mutex> guard(NCCLGroupGuard::NCCLMutex());
PADDLE_ENFORCE(platform::dynload::ncclCommInitAll(
comms.get(), static_cast<int>(order_.size()), order_.data()));
}
- int i = 0;
- for (auto &dev_id : order_) {
- contexts_.at(dev_id).comm_ = comms[i++];
+ } else {
+ PADDLE_ENFORCE_GT(node_count, 0);
+ PADDLE_ENFORCE_EQ(node_count % places.size(), 0,
+ "must have same number of GPUs on each node");
+ {
+ std::lock_guard<std::mutex> guard(NCCLGroupGuard::NCCLMutex());
+ int nranks = node_count * order_.size();
+ for (auto &gpu_id : order_) {
+ int rank = trainer_id * order_.size() + gpu_id;
+ PADDLE_ENFORCE(cudaSetDevice(gpu_id));
+ PADDLE_ENFORCE(
+ ncclCommInitRank(comms.get() + gpu_id, nranks, *nccl_id, rank));
+ }
}
}
+ int i = 0;
+ for (auto &dev_id : order_) {
+ contexts_.at(dev_id).comm_ = comms[i++];
+ }
}
NCCLContextMap(const NCCLContextMap &other) = delete;
diff --git a/paddle/fluid/pybind/pybind.cc b/paddle/fluid/pybind/pybind.cc
index c925686f83..827c2701ba 100644
--- a/paddle/fluid/pybind/pybind.cc
+++ b/paddle/fluid/pybind/pybind.cc
@@ -502,11 +502,13 @@ All parameter, weight, gradient are variables in Paddle.
const std::unordered_set<std::string> &bcast_vars,
const ProgramDesc &main_program, const std::string &loss_var_name,
Scope *scope, std::vector<Scope *> &local_scopes,
- bool allow_op_delay, bool use_default_grad_scale) {
+ bool allow_op_delay, bool use_default_grad_scale,
+ size_t num_trainers, size_t trainer_id) {
new (&self) ParallelExecutor(
num_threads, use_event, places, params, bcast_vars,
main_program, loss_var_name, scope, local_scopes,
- allow_op_delay, use_default_grad_scale);
+ allow_op_delay, use_default_grad_scale, num_trainers,
+ trainer_id);
})
.def("bcast_params", &ParallelExecutor::BCastParamsToGPUs)
// NOTE: even we return a vec<Scope*>* to Python use reference policy.
From 3667578ec2f820dddf5067bab5e918313d8bf383 Mon Sep 17 00:00:00 2001
From: typhoonzero <typhoonzero1986@gmail.com>
Date: Sat, 5 May 2018 17:34:56 +0800
Subject: [PATCH 010/195] testing
---
paddle/fluid/platform/nccl_helper.h | 4 ++--
python/paddle/fluid/parallel_executor.py | 8 ++++++--
2 files changed, 8 insertions(+), 4 deletions(-)
diff --git a/paddle/fluid/platform/nccl_helper.h b/paddle/fluid/platform/nccl_helper.h
index 3b52587a28..f3c4c92afa 100644
--- a/paddle/fluid/platform/nccl_helper.h
+++ b/paddle/fluid/platform/nccl_helper.h
@@ -108,8 +108,8 @@ struct NCCLContextMap {
for (auto &gpu_id : order_) {
int rank = trainer_id * order_.size() + gpu_id;
PADDLE_ENFORCE(cudaSetDevice(gpu_id));
- PADDLE_ENFORCE(
- ncclCommInitRank(comms.get() + gpu_id, nranks, *nccl_id, rank));
+ PADDLE_ENFORCE(platform::dynload::ncclCommInitRank(
+ comms.get() + gpu_id, nranks, *nccl_id, rank));
}
}
}
diff --git a/python/paddle/fluid/parallel_executor.py b/python/paddle/fluid/parallel_executor.py
index f4128dcbe9..34899a54b6 100644
--- a/python/paddle/fluid/parallel_executor.py
+++ b/python/paddle/fluid/parallel_executor.py
@@ -30,7 +30,9 @@ class ParallelExecutor(object):
num_threads=None,
allow_op_delay=False,
share_vars_from=None,
- use_default_grad_scale=True):
+ use_default_grad_scale=True,
+ num_nodes=0,
+ trainer_id=0):
"""
ParallelExecutor can run program in parallel.
@@ -129,7 +131,9 @@ class ParallelExecutor(object):
scope,
local_scopes,
allow_op_delay,
- use_default_grad_scale)
+ use_default_grad_scale,
+ num_nodes,
+ trainer_id)
self.scope = scope
def run(self, fetch_list, feed=None, feed_dict=None):
From 0598a4b36627b219c6a80c721e133e269c3b8bc5 Mon Sep 17 00:00:00 2001
From: typhoonzero <typhoonzero1986@gmail.com>
Date: Sat, 5 May 2018 18:27:07 +0800
Subject: [PATCH 011/195] fix ci
---
paddle/fluid/operators/detail/sendrecvop_utils.cc | 1 +
python/paddle/fluid/framework.py | 2 +-
2 files changed, 2 insertions(+), 1 deletion(-)
diff --git a/paddle/fluid/operators/detail/sendrecvop_utils.cc b/paddle/fluid/operators/detail/sendrecvop_utils.cc
index 800d6d8bd2..d754630fd7 100644
--- a/paddle/fluid/operators/detail/sendrecvop_utils.cc
+++ b/paddle/fluid/operators/detail/sendrecvop_utils.cc
@@ -14,6 +14,7 @@ limitations under the License. */
#include "paddle/fluid/operators/detail/sendrecvop_utils.h"
+#include <nccl.h>
#include <sys/time.h>
#include <thread> // NOLINT
diff --git a/python/paddle/fluid/framework.py b/python/paddle/fluid/framework.py
index 2cdf010926..c6262d54ac 100644
--- a/python/paddle/fluid/framework.py
+++ b/python/paddle/fluid/framework.py
@@ -487,7 +487,7 @@ class Operator(object):
'rnn_memory_helper_grad', 'conditional_block', 'while', 'send',
'recv', 'listen_and_serv', 'parallel_do', 'save_combine',
'load_combine', 'ncclInit', 'channel_create', 'channel_close',
- 'channel_send', 'channel_recv', 'select'
+ 'channel_send', 'channel_recv', 'select', 'gen_nccl_id'
}
if type not in no_kernel_op_set:
self.desc.infer_var_type(self.block.desc)
From 82c61dbde3cd496c5aeddb1d94eb0dd82d039268 Mon Sep 17 00:00:00 2001
From: typhoonzero <typhoonzero1986@gmail.com>
Date: Mon, 7 May 2018 13:51:03 +0800
Subject: [PATCH 012/195] fix testing
---
paddle/fluid/operators/detail/grpc_client.cc | 2 +-
paddle/fluid/operators/detail/grpc_client.h | 6 +-
paddle/fluid/operators/detail/grpc_server.cc | 2 +-
paddle/fluid/operators/detail/grpc_server.h | 2 +
.../operators/detail/sendrecvop_utils.cc | 169 +++++++++---------
.../operators/detail/variable_response.cc | 23 ++-
paddle/fluid/operators/gen_nccl_id_op.cc | 14 +-
7 files changed, 117 insertions(+), 101 deletions(-)
diff --git a/paddle/fluid/operators/detail/grpc_client.cc b/paddle/fluid/operators/detail/grpc_client.cc
index 661dfa69fe..ae60ab1532 100644
--- a/paddle/fluid/operators/detail/grpc_client.cc
+++ b/paddle/fluid/operators/detail/grpc_client.cc
@@ -52,7 +52,7 @@ bool RPCClient::AsyncSendVariable(const std::string& ep,
// stub context
SendProcessor* s = new SendProcessor(ch);
s->Prepare(var_h, time_out);
- s->response_call_back_ = NULL;
+ s->response_call_back_ = nullptr;
auto call = s->stub_g_.PrepareUnaryCall(
s->context_.get(), "/sendrecv.SendRecvService/SendVariable", req, &cq_);
diff --git a/paddle/fluid/operators/detail/grpc_client.h b/paddle/fluid/operators/detail/grpc_client.h
index f6229b71bc..dabce7414d 100644
--- a/paddle/fluid/operators/detail/grpc_client.h
+++ b/paddle/fluid/operators/detail/grpc_client.h
@@ -57,7 +57,9 @@ void ProcGetResponse(const VarHandle& var_h, const grpc::ByteBuffer& msg);
class BaseProcessor {
public:
- explicit BaseProcessor(std::shared_ptr<grpc::Channel> ch) { context_ = NULL; }
+ explicit BaseProcessor(std::shared_ptr<grpc::Channel> ch) {
+ context_ = nullptr;
+ }
virtual ~BaseProcessor() {}
@@ -105,7 +107,7 @@ class SendProcessor : public BaseProcessor {
::grpc::GenericStub stub_g_;
::grpc::ByteBuffer reply_;
- RequestSendCallBack response_call_back_ = NULL;
+ RequestSendCallBack response_call_back_ = nullptr;
};
typedef std::function<void(const VarHandle&, const ::grpc::ByteBuffer&)>
diff --git a/paddle/fluid/operators/detail/grpc_server.cc b/paddle/fluid/operators/detail/grpc_server.cc
index 7ca694886e..1cdfe01170 100644
--- a/paddle/fluid/operators/detail/grpc_server.cc
+++ b/paddle/fluid/operators/detail/grpc_server.cc
@@ -261,8 +261,8 @@ void AsyncGRPCServer::ShutdownQueue() {
// This URL explains why shutdown is complicate:
void AsyncGRPCServer::ShutDown() {
is_shut_down_ = true;
- ShutdownQueue();
server_->Shutdown();
+ ShutdownQueue();
}
void AsyncGRPCServer::TryToRegisterNewSendOne() {
diff --git a/paddle/fluid/operators/detail/grpc_server.h b/paddle/fluid/operators/detail/grpc_server.h
index 99b87b8c6c..0e1592eed4 100644
--- a/paddle/fluid/operators/detail/grpc_server.h
+++ b/paddle/fluid/operators/detail/grpc_server.h
@@ -47,6 +47,8 @@ class AsyncGRPCServer final {
explicit AsyncGRPCServer(const std::string &address, bool sync_mode)
: address_(address), sync_mode_(sync_mode) {}
+ ~AsyncGRPCServer() {}
+
void RunSyncUpdate();
// functions to sync server barrier status.
diff --git a/paddle/fluid/operators/detail/sendrecvop_utils.cc b/paddle/fluid/operators/detail/sendrecvop_utils.cc
index d754630fd7..207ea3cb8b 100644
--- a/paddle/fluid/operators/detail/sendrecvop_utils.cc
+++ b/paddle/fluid/operators/detail/sendrecvop_utils.cc
@@ -53,109 +53,106 @@ void SerializeToByteBuffer(const std::string& name, framework::Variable* var,
e.WriteUint64(VarMsg::kTypeFieldNumber, 1);
} else if (var->IsType<ncclUniqueId>()) {
// NOTE: sendrecv only support RAW type for NCCL_ID
+ VLOG(3) << "serilizing: setting var type nccl id";
e.WriteUint64(VarMsg::kTypeFieldNumber, 2);
}
if (!out_name.empty()) {
e.WriteString(VarMsg::kOutVarnameFieldNumber, out_name);
}
- switch (framework::ToVarType(var->Type())) {
- case framework::proto::VarType_Type_LOD_TENSOR: {
- auto tensor = var->Get<framework::LoDTensor>();
- e.WriteUint64(VarMsg::kDataTypeFieldNumber,
- framework::ToDataType(tensor.type()));
- for (auto& dim : framework::vectorize(tensor.dims())) {
- e.WriteUint64(VarMsg::kDimsFieldNumber, dim);
- }
- auto lod = tensor.lod(); // std::vector<Vector<size_t>>
- if (lod.size() > 0) {
- e.WriteUint64(VarMsg::kLodLevelFieldNumber, lod.size());
-
- for (auto& each : lod) {
- e.WriteVarlengthBeginning(VarMsg::kLodFieldNumber,
- 2 + // tag + varintlength of submessage
- 1 + // kLodDataFieldNumber
- each.size());
- // auto copied from GPU
- for (auto& d : each) {
- e.WriteUint64(VarMsg::LodData::kLodDataFieldNumber, d);
- }
+ if (var->IsType<framework::LoDTensor>()) {
+ // ===========================Tensor==================================
+ auto tensor = var->Get<framework::LoDTensor>();
+ e.WriteUint64(VarMsg::kDataTypeFieldNumber,
+ framework::ToDataType(tensor.type()));
+ for (auto& dim : framework::vectorize(tensor.dims())) {
+ e.WriteUint64(VarMsg::kDimsFieldNumber, dim);
+ }
+ auto lod = tensor.lod(); // std::vector<Vector<size_t>>
+ if (lod.size() > 0) {
+ e.WriteUint64(VarMsg::kLodLevelFieldNumber, lod.size());
+
+ for (auto& each : lod) {
+ e.WriteVarlengthBeginning(VarMsg::kLodFieldNumber,
+ 2 + // tag + varintlength of submessage
+ 1 + // kLodDataFieldNumber
+ each.size());
+ // auto copied from GPU
+ for (auto& d : each) {
+ e.WriteUint64(VarMsg::LodData::kLodDataFieldNumber, d);
}
}
- if (platform::is_gpu_place(ctx.GetPlace())) {
+ }
+ if (platform::is_gpu_place(ctx.GetPlace())) {
#ifdef PADDLE_WITH_CUDA
- PADDLE_ENFORCE(platform::is_gpu_place(tensor.place()));
+ PADDLE_ENFORCE(platform::is_gpu_place(tensor.place()));
+ platform::CPUPlace cpu;
+ auto& gpu_dev_ctx = static_cast<const platform::CUDADeviceContext&>(ctx);
+ auto copy_size = tensor.numel() * framework::SizeOfType(tensor.type());
+ payload = memory::Alloc(cpu, copy_size);
+
+ memory::Copy(cpu, payload,
+ boost::get<platform::CUDAPlace>(tensor.place()),
+ reinterpret_cast<const void*>(tensor.data<void>()),
+ copy_size, gpu_dev_ctx.stream());
+ ctx.Wait();
+ destroy_callback = [](void* backing) {
platform::CPUPlace cpu;
- auto& gpu_dev_ctx =
- static_cast<const platform::CUDADeviceContext&>(ctx);
- auto copy_size = tensor.numel() * framework::SizeOfType(tensor.type());
- payload = memory::Alloc(cpu, copy_size);
-
- memory::Copy(cpu, payload,
- boost::get<platform::CUDAPlace>(tensor.place()),
- reinterpret_cast<const void*>(tensor.data<void>()),
- copy_size, gpu_dev_ctx.stream());
- ctx.Wait();
- destroy_callback = [](void* backing) {
- platform::CPUPlace cpu;
- memory::Free(cpu, backing);
- };
+ memory::Free(cpu, backing);
+ };
#endif
- } else {
- payload = tensor.data<void>();
- }
- payload_size = tensor.numel() * framework::SizeOfType(tensor.type());
- e.WriteVarlengthBeginning(VarMsg::kSerializedFieldNumber, payload_size);
- } break;
- case framework::proto::VarType_Type_SELECTED_ROWS: {
- // TODO(typhoonzero): selectedrows implement should not use unique_ptr
- auto* slr = var->GetMutable<framework::SelectedRows>();
- e.WriteUint64(VarMsg::kDataTypeFieldNumber,
- framework::ToDataType(slr->value().type()));
- for (auto& dim : framework::vectorize(slr->value().dims())) {
- e.WriteUint64(VarMsg::kDimsFieldNumber, dim);
- }
- e.WriteUint64(VarMsg::kLodLevelFieldNumber, 0);
- e.WriteUint64(VarMsg::kSlrHeightFieldNumber, slr->height());
- auto* tensor = slr->mutable_value();
- if (platform::is_gpu_place(ctx.GetPlace())) {
+ } else {
+ payload = tensor.data<void>();
+ }
+ payload_size = tensor.numel() * framework::SizeOfType(tensor.type());
+ e.WriteVarlengthBeginning(VarMsg::kSerializedFieldNumber, payload_size);
+ } else if (var->IsType<framework::SelectedRows>()) {
+ // ===========================SELECTED
+ // ROWS==================================
+ // TODO(typhoonzero): selectedrows implement should not use unique_ptr
+ auto* slr = var->GetMutable<framework::SelectedRows>();
+ e.WriteUint64(VarMsg::kDataTypeFieldNumber,
+ framework::ToDataType(slr->value().type()));
+ for (auto& dim : framework::vectorize(slr->value().dims())) {
+ e.WriteUint64(VarMsg::kDimsFieldNumber, dim);
+ }
+ e.WriteUint64(VarMsg::kLodLevelFieldNumber, 0);
+ e.WriteUint64(VarMsg::kSlrHeightFieldNumber, slr->height());
+ auto* tensor = slr->mutable_value();
+ if (platform::is_gpu_place(ctx.GetPlace())) {
#ifdef PADDLE_WITH_CUDA
+ platform::CPUPlace cpu;
+ auto& gpu_dev_ctx = static_cast<const platform::CUDADeviceContext&>(ctx);
+ auto copy_size = tensor->numel() * framework::SizeOfType(tensor->type());
+ payload = memory::Alloc(cpu, copy_size);
+ memory::Copy(cpu, payload,
+ boost::get<platform::CUDAPlace>(tensor->place()),
+ reinterpret_cast<const void*>(tensor->data<void>()),
+ copy_size, gpu_dev_ctx.stream());
+ ctx.Wait();
+ destroy_callback = [](void* backing) {
platform::CPUPlace cpu;
- auto& gpu_dev_ctx =
- static_cast<const platform::CUDADeviceContext&>(ctx);
- auto copy_size =
- tensor->numel() * framework::SizeOfType(tensor->type());
- payload = memory::Alloc(cpu, copy_size);
- memory::Copy(cpu, payload,
- boost::get<platform::CUDAPlace>(tensor->place()),
- reinterpret_cast<const void*>(tensor->data<void>()),
- copy_size, gpu_dev_ctx.stream());
- ctx.Wait();
- destroy_callback = [](void* backing) {
- platform::CPUPlace cpu;
- memory::Free(cpu, backing);
- };
+ memory::Free(cpu, backing);
+ };
#endif
- } else {
- payload = slr->mutable_value()->data<void>();
- }
- payload_size = tensor->numel() * framework::SizeOfType(tensor->type());
- e.WriteVarlengthBeginning(VarMsg::kSerializedFieldNumber, payload_size);
- } break;
- case framework::proto::VarType_Type_RAW: {
- e.WriteVarlengthBeginning(VarMsg::kSerializedFieldNumber,
- NCCL_UNIQUE_ID_BYTES);
- ncclUniqueId* uid = var->GetMutable<ncclUniqueId>();
- e.WriteRawBytes(std::string(uid->internal, NCCL_UNIQUE_ID_BYTES));
- } break;
- default:
- PADDLE_THROW("Serialize does not support type: %s",
- typeid(var->Type()).name());
- break;
+ } else {
+ payload = slr->mutable_value()->data<void>();
+ }
+ payload_size = tensor->numel() * framework::SizeOfType(tensor->type());
+ e.WriteVarlengthBeginning(VarMsg::kSerializedFieldNumber, payload_size);
+ } else if (var->IsType<ncclUniqueId>()) {
+ // ===========================NCCL ID==================================
+ e.WriteVarlengthBeginning(VarMsg::kSerializedFieldNumber,
+ NCCL_UNIQUE_ID_BYTES);
+ ncclUniqueId* uid = var->GetMutable<ncclUniqueId>();
+ e.WriteRawBytes(std::string(uid->internal, NCCL_UNIQUE_ID_BYTES));
+ } else {
+ PADDLE_THROW("Serialize does not support type: %s",
+ typeid(var->Type()).name());
}
- if (framework::ToVarType(var->Type()) == framework::proto::VarType_Type_RAW) {
+ if (var->IsType<ncclUniqueId>()) {
// for serialize NCCL_ID
::grpc::Slice slices(e.size());
memcpy(const_cast<uint8_t*>(slices.begin()), e.data(), e.size());
diff --git a/paddle/fluid/operators/detail/variable_response.cc b/paddle/fluid/operators/detail/variable_response.cc
index 81d755f5fc..64fd84736d 100644
--- a/paddle/fluid/operators/detail/variable_response.cc
+++ b/paddle/fluid/operators/detail/variable_response.cc
@@ -371,19 +371,26 @@ int VariableResponse::Parse(Source* source) {
meta_.type() == sendrecv::NCCL_ID) &&
meta_.varname() != "",
"meta info should be got first!");
+ int length = 0;
+ if (wt != WIRETYPE_LENGTH_DELIMITED ||
+ !ReadVarintSizeAsInt(&input, &length)) {
+ return tag;
+ }
+
if (meta_.type() == sendrecv::NCCL_ID) {
+ VLOG(3) << "parse nccl id request";
auto* var = scope_->FindVar(meta_.varname());
if (var != nullptr) {
+ VLOG(3) << "parse nccl id: length " << length;
ncclUniqueId* id = var->GetMutable<ncclUniqueId>();
- memcpy(id->internal, meta_.serialized().c_str(),
- meta_.serialized().size());
+ if (!ReadRaw(&input, *dev_ctx_, platform::CPUPlace(), id->internal,
+ length)) {
+ return tag;
+ }
+ // memcpy(id->internal, meta_.serialized().c_str(),
+ // meta_.serialized().size());
}
- }
-
- int length = 0;
- if (wt != WIRETYPE_LENGTH_DELIMITED ||
- !ReadVarintSizeAsInt(&input, &length)) {
- return tag;
+ break;
}
framework::DDim dims = GetDims(meta_.dims());
diff --git a/paddle/fluid/operators/gen_nccl_id_op.cc b/paddle/fluid/operators/gen_nccl_id_op.cc
index afb228fa6f..8d28be35a8 100644
--- a/paddle/fluid/operators/gen_nccl_id_op.cc
+++ b/paddle/fluid/operators/gen_nccl_id_op.cc
@@ -37,7 +37,8 @@ class GenNCCLIdOp : public framework::OperatorBase {
void RunImpl(const framework::Scope& scope,
const platform::Place& dev_place) const override {
platform::DeviceContextPool& pool = platform::DeviceContextPool::Instance();
- auto& dev_ctx = *pool.Get(dev_place);
+ // put nccl id in CPUPlace
+ auto& dev_ctx = *pool.Get(platform::CPUPlace());
int trainer_id = Attr<int>("trainer_id");
framework::Scope& local_scope = scope.NewScope();
@@ -60,9 +61,11 @@ class GenNCCLIdOp : public framework::OperatorBase {
Attr<std::vector<std::string>>("endpoint_list");
detail::RPCClient client;
for (auto& ep : endpoint_list) {
+ VLOG(3) << "sending nccl id to " << ep;
client.AsyncSendVariable(ep, dev_ctx, *scope, "NCCLID");
}
client.Wait();
+ VLOG(3) << "sending completed...";
}
void GetIdByServer(framework::Scope* scope,
@@ -78,9 +81,14 @@ class GenNCCLIdOp : public framework::OperatorBase {
server_thread_.reset(new std::thread(std::bind(
&detail::AsyncGRPCServer::RunSyncUpdate, rpc_service_.get())));
-
+ rpc_service_->SetCond(0);
+ VLOG(3) << "start getting nccl id from trainer 0...";
auto recv = rpc_service_->Get();
- rpc_service_->ShutDown();
+ VLOG(3) << "got nccl id and stop server...";
+ // rpc_service_->SetCond(1);
+ // rpc_service_->ShutDown();
+ rpc_service->Push(LISTEN_TERMINATE_MESSAGE);
+ VLOG(3) << "rpc server stopped";
// TODO(wuyi): reinit nccl communicators
}
From c6a6d87f9693e4ce6296134a89a2ec2a7f596eda Mon Sep 17 00:00:00 2001
From: Yu Yang <yuyang18@baidu.com>
Date: Mon, 7 May 2018 16:21:55 +0800
Subject: [PATCH 013/195] Rewrite Matmul, make code cleaner
---
paddle/fluid/operators/math/blas.cc | 39 ++-
paddle/fluid/operators/math/blas.h | 33 ++
paddle/fluid/operators/math/matmul.h | 149 ---------
paddle/fluid/operators/matmul_op.cc | 134 ++------
paddle/fluid/operators/matmul_op.h | 286 +++++++++---------
.../fluid/tests/unittests/test_matmul_op.py | 35 ++-
6 files changed, 258 insertions(+), 418 deletions(-)
delete mode 100644 paddle/fluid/operators/math/matmul.h
diff --git a/paddle/fluid/operators/math/blas.cc b/paddle/fluid/operators/math/blas.cc
index 3eeb77546b..7427ceac60 100644
--- a/paddle/fluid/operators/math/blas.cc
+++ b/paddle/fluid/operators/math/blas.cc
@@ -13,10 +13,47 @@
// limitations under the License.
#include "paddle/fluid/operators/math/blas.h"
+
+#include <utility>
namespace paddle {
namespace operators {
namespace math {
-// Do nothing. Blas is a header only library.
+MatDim GetMatDim(const framework::DDim& dim, int num_flatten_cols, bool trans) {
+ MatDim retv;
+ if (num_flatten_cols > 1) {
+ auto flatten_dim = framework::flatten_to_2d(dim, num_flatten_cols);
+ retv.height_ = flatten_dim[0];
+ retv.width_ = flatten_dim[1];
+ } else {
+ if (dim.size() == 1) {
+ retv.height_ = 1;
+ retv.width_ = dim[0];
+ } else if (dim.size() == 2) {
+ retv.height_ = dim[0];
+ retv.width_ = dim[1];
+ } else {
+ if (dim.size() == 3) {
+ retv.batch_size_ = dim[0];
+ retv.height_ = dim[1];
+ retv.width_ = dim[2];
+ } else {
+ auto dim_vec = framework::vectorize(dim);
+ retv.batch_size_ = 1;
+ for (size_t i = 0; i < dim_vec.size() - 2; ++i) {
+ retv.batch_size_ *= dim_vec[i];
+ retv.height_ = dim_vec[dim_vec.size() - 2];
+ retv.width_ = dim_vec[dim_vec.size() - 1];
+ }
+ }
+ retv.stride_ = retv.height_ * retv.width_;
+ }
+ }
+ if (trans) {
+ std::swap(retv.width_, retv.height_);
+ }
+ retv.trans_ = trans;
+ return retv;
+}
} // namespace math
} // namespace operators
} // namespace paddle
diff --git a/paddle/fluid/operators/math/blas.h b/paddle/fluid/operators/math/blas.h
index 5cd2f855d1..cca967f33f 100644
--- a/paddle/fluid/operators/math/blas.h
+++ b/paddle/fluid/operators/math/blas.h
@@ -46,6 +46,17 @@ namespace paddle {
namespace operators {
namespace math {
+struct MatDim {
+ int64_t height_;
+ int64_t width_;
+ int64_t stride_{0};
+ int64_t batch_size_{0};
+ bool trans_;
+};
+
+extern MatDim GetMatDim(const framework::DDim& tensor, int num_flatten_cols,
+ bool trans);
+
template <typename DeviceContext>
class Blas {
public:
@@ -90,6 +101,28 @@ class Blas {
int K, T alpha, const T* A, const T* B, T beta, T* C,
int batchCount, int64_t strideA, int64_t strideB) const;
+ template <typename T>
+ void MatMul(const framework::Tensor& mat_a, const MatDim& dim_a,
+ const framework::Tensor& mat_b, const MatDim& dim_b, T alpha,
+ framework::Tensor* mat_out, T beta) const {
+ PADDLE_ENFORCE_EQ(dim_a.width_, dim_b.height_);
+ CBLAS_TRANSPOSE transA = !dim_a.trans_ ? CblasNoTrans : CblasTrans;
+ CBLAS_TRANSPOSE transB = !dim_b.trans_ ? CblasNoTrans : CblasTrans;
+ if (dim_a.batch_size_ == 0 && dim_b.batch_size_ == 0) {
+ this->template GEMM<T>(transA, transB, dim_a.height_, dim_b.width_,
+ dim_a.width_, alpha, mat_a.data<T>(),
+ mat_b.data<T>(), beta, mat_out->data<T>());
+ } else {
+ PADDLE_ENFORCE(dim_a.batch_size_ == dim_b.batch_size_ ||
+ dim_a.batch_size_ == 0 || dim_b.batch_size_ == 0);
+ this->template BatchedGEMM<T>(
+ transA, transB, dim_a.height_, dim_b.width_, dim_a.width_, alpha,
+ mat_a.data<T>(), mat_b.data<T>(), beta, mat_out->data<T>(),
+ dim_a.batch_size_ == 0 ? dim_b.batch_size_ : dim_a.batch_size_,
+ dim_a.stride_, dim_b.stride_);
+ }
+ }
+
private:
const DeviceContext& context_;
};
diff --git a/paddle/fluid/operators/math/matmul.h b/paddle/fluid/operators/math/matmul.h
deleted file mode 100644
index 87fd38a324..0000000000
--- a/paddle/fluid/operators/math/matmul.h
+++ /dev/null
@@ -1,149 +0,0 @@
-/* Copyright (c) 2017 PaddlePaddle Authors. All Rights Reserved.
-
-Licensed under the Apache License, Version 2.0 (the "License");
-you may not use this file except in compliance with the License.
-You may obtain a copy of the License at
-
- http://www.apache.org/licenses/LICENSE-2.0
-
-Unless required by applicable law or agreed to in writing, software
-distributed under the License is distributed on an "AS IS" BASIS,
-WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-See the License for the specific language governing permissions and
-limitations under the License. */
-
-#pragma once
-#include <algorithm>
-#include <vector>
-#include "paddle/fluid/operators/math/blas.h"
-
-namespace paddle {
-namespace operators {
-namespace math {
-
-// Implements the logic of numpy matmul:
-// https://docs.scipy.org/doc/numpy-1.13.0/reference/generated/numpy.matmul.html
-//
-// but allowing also for a, b to be transposed
-//
-// Both a & b can be 1- to 3-dimensional. Higher rank tensors are not supported
-// yet.
-template <typename DeviceContext, typename T>
-class MatMulFunctor {
- public:
- void operator()(const DeviceContext& context, const framework::Tensor& a,
- bool trans_a, const framework::Tensor& b, bool trans_b,
- T alpha, framework::Tensor* out, T beta) {
- auto dim_a = a.dims();
- auto dim_b = b.dims();
-
- PADDLE_ENFORCE(a.place() == b.place() && b.place() == out->place(),
- "Tensors must all be in the same place.");
- PADDLE_ENFORCE_GE(dim_a.size(), 1,
- "Input tensor a must be at least 1-dimensional.");
- PADDLE_ENFORCE_GE(dim_b.size(), 1,
- "Input tensor b must be at least 1-dimensional.");
-
- std::vector<int64_t> out_dim;
- int64_t batch_count = 1;
- if (dim_a.size() > 3) {
- PADDLE_ENFORCE(dim_b.size() == dim_a.size(),
- "The dimensions of X and Y must be the same, and both of "
- "them should be %d-dimensional.",
- dim_b.size());
- // The first rank-2 dimensions are accumulated on the batch_count, and the
- // last two dimensions are used for matrix multiplication.
- for (int j = 0; j < dim_a.size() - 2; ++j) {
- PADDLE_ENFORCE_EQ(dim_b[j], dim_a[j],
- "The %d-th dimension of X and Y must be the same.",
- j);
- out_dim.push_back(dim_a[j]);
- batch_count *= dim_a[j];
- }
- }
-
- int M = 0, N = 0, kA = 0, kB = 0, batchCountA = 0, batchCountB = 0,
- strideA = 0, strideB = 0;
-
- switch (dim_a.size()) {
- case 1:
- // similar to np.matmul:
- // prepend dimension 1 (no transpose) or append dimension 1 (transpose)
- M = trans_a ? dim_a[0] : 1;
- kA = trans_a ? 1 : dim_a[0];
- break;
- case 2:
- M = trans_a ? dim_a[1] : dim_a[0];
- kA = trans_a ? dim_a[0] : dim_a[1];
- break;
- case 3:
- batchCountA = dim_a[0];
- M = trans_a ? dim_a[2] : dim_a[1];
- kA = trans_a ? dim_a[1] : dim_a[2];
- strideA = M * kA;
- break;
- default:
- batchCountA = batch_count;
- size_t mat_s = dim_a.size() - 2;
- M = trans_a ? dim_a[mat_s + 1] : dim_a[mat_s];
- kA = trans_a ? dim_a[mat_s] : dim_a[mat_s + 1];
- strideA = M * kA;
- }
-
- switch (dim_b.size()) {
- case 1:
- // similar to np.matmul:
- // append dimension 1 (no transpose) or prepend dimension 1 (transpose)
- kB = trans_b ? 1 : dim_b[0];
- N = trans_b ? dim_b[0] : 1;
- break;
- case 2:
- kB = trans_b ? dim_b[1] : dim_b[0];
- N = trans_b ? dim_b[0] : dim_b[1];
- break;
- case 3:
- batchCountB = dim_b[0];
- kB = trans_b ? dim_b[2] : dim_b[1];
- N = trans_b ? dim_b[1] : dim_b[2];
- strideB = kB * N;
- break;
- default:
- batchCountB = batch_count;
- size_t mat_s = dim_b.size() - 2;
- kB = trans_b ? dim_b[mat_s + 1] : dim_b[mat_s];
- N = trans_b ? dim_b[mat_s] : dim_b[mat_s + 1];
- strideB = kB * N;
- }
-
- PADDLE_ENFORCE_EQ(
- kA, kB,
- "First matrix's width must be equal with second matrix's height.");
- if (batchCountA && batchCountB) {
- PADDLE_ENFORCE_EQ(
- batchCountA, batchCountB,
- "When input tensors a and b are both batched, they must have the "
- "same batch dimension.");
- }
- int batchCount = std::max(batchCountA, batchCountB);
-
- CBLAS_TRANSPOSE transA = (trans_a == false) ? CblasNoTrans : CblasTrans;
- CBLAS_TRANSPOSE transB = (trans_b == false) ? CblasNoTrans : CblasTrans;
-
- auto blas = GetBlas<DeviceContext, T>(context);
-
- if (!batchCount) {
- // regular matrix multiplication
- blas.GEMM(transA, transB, M, N, kA, alpha, a.data<T>(), b.data<T>(), beta,
- out->data<T>());
- } else {
- // batched matrix multiplication
- blas.BatchedGEMM(transA, transB, M, N, kA, alpha, a.data<T>(),
- b.data<T>(), beta, out->data<T>(), batchCount, strideA,
- strideB);
- }
- }
-};
-
-} // namespace math
-} // namespace operators
-} // namespace paddle
diff --git a/paddle/fluid/operators/matmul_op.cc b/paddle/fluid/operators/matmul_op.cc
index e5d33fbc36..c285d461e8 100644
--- a/paddle/fluid/operators/matmul_op.cc
+++ b/paddle/fluid/operators/matmul_op.cc
@@ -36,121 +36,39 @@ class MatMulOp : public framework::OperatorWithKernel {
auto dim_x = context->GetInputDim("X");
auto dim_y = context->GetInputDim("Y");
- bool transpose_x = context->Attrs().Get<bool>("transpose_X");
- bool transpose_y = context->Attrs().Get<bool>("transpose_Y");
-
- PADDLE_ENFORCE_GE(dim_x.size(), 1,
- "Input tensor X must be at least 1-dimensional.");
- PADDLE_ENFORCE_GE(dim_y.size(), 1,
- "Input tensor Y must be at least 1-dimensional.");
-
- std::vector<int64_t> out_dim;
- int64_t batch_count = 1;
- if (dim_x.size() > 3) {
- PADDLE_ENFORCE_EQ(
- dim_y.size(), dim_x.size(),
- "The dimensions of X and Y must be the same, and both of "
- "them should be %d-dimensional.",
- dim_x.size());
-
- // The first rank-2 dimensions are accumulated on the batch_count, and the
- // last two dimensions are used for matrix multiplication.
- for (int j = 0; j < dim_x.size() - 2; ++j) {
- PADDLE_ENFORCE_EQ(dim_y[j], dim_x[j],
- "The %d-th dimension of X and Y must be the same.",
- j);
- out_dim.push_back(dim_x[j]);
- batch_count *= dim_x[j];
- }
- }
- int M = 0, N = 0, KX = 0, KY = 0, batchCountX = 0, batchCountY = 0;
- bool remove_initial_dim = false, remove_final_dim = false;
-
- switch (dim_x.size()) {
- case 1:
- if (transpose_x) {
- M = dim_x[0];
- KX = 1;
- } else {
- M = 1;
- KX = dim_x[0];
- remove_initial_dim = true;
- }
- break;
- case 2:
- M = transpose_x ? dim_x[1] : dim_x[0];
- KX = transpose_x ? dim_x[0] : dim_x[1];
- break;
- case 3:
- batchCountX = dim_x[0];
- M = transpose_x ? dim_x[2] : dim_x[1];
- KX = transpose_x ? dim_x[1] : dim_x[2];
- break;
- default:
- batchCountX = batch_count;
- size_t mat_s = dim_x.size() - 2;
- M = transpose_x ? dim_x[mat_s + 1] : dim_x[mat_s];
- KX = transpose_x ? dim_x[mat_s] : dim_x[mat_s + 1];
- break;
- }
+ auto mat_dim_x = math::GetMatDim(GetXDim(dim_x), 0,
+ context->Attrs().Get<bool>("transpose_X"));
+ auto mat_dim_y = math::GetMatDim(GetYDim(dim_y), 0,
+ context->Attrs().Get<bool>("transpose_Y"));
- switch (dim_y.size()) {
- case 1:
- if (transpose_y) {
- N = dim_y[0];
- KY = 1;
- } else {
- N = 1;
- KY = dim_y[0];
- remove_final_dim = true;
- }
- break;
- case 2:
- KY = transpose_y ? dim_y[1] : dim_y[0];
- N = transpose_y ? dim_y[0] : dim_y[1];
- break;
- case 3:
- batchCountY = dim_y[0];
- KY = transpose_y ? dim_y[2] : dim_y[1];
- N = transpose_y ? dim_y[1] : dim_y[2];
- break;
- default:
- batchCountY = batch_count;
- size_t mat_s = dim_y.size() - 2;
- KY = transpose_y ? dim_y[mat_s + 1] : dim_y[mat_s];
- N = transpose_y ? dim_y[mat_s] : dim_y[mat_s + 1];
+ PADDLE_ENFORCE_EQ(mat_dim_x.width_, mat_dim_y.height_);
+ PADDLE_ENFORCE(mat_dim_x.batch_size_ == mat_dim_y.batch_size_ ||
+ mat_dim_x.batch_size_ == 0 || mat_dim_y.batch_size_ == 0);
+ std::vector<int64_t> dim_out;
+ if (mat_dim_x.batch_size_ != 0) {
+ dim_out = framework::vectorize(dim_x);
+ dim_out[dim_out.size() - 2] = mat_dim_x.height_;
+ dim_out[dim_out.size() - 1] = mat_dim_y.width_;
+ } else if (mat_dim_y.batch_size_ != 0) {
+ dim_out = framework::vectorize(dim_y);
+ dim_out[dim_out.size() - 2] = mat_dim_x.height_;
+ dim_out[dim_out.size() - 1] = mat_dim_y.width_;
+ } else {
+ dim_out = {mat_dim_x.height_, mat_dim_y.width_};
}
- PADDLE_ENFORCE_EQ(
- KX, KY,
- "First matrix's width must be equal with second matrix's height.");
- if (batchCountX && batchCountY) {
- PADDLE_ENFORCE_EQ(
- batchCountX, batchCountY,
- "When Input(X) and Input(Y) are both three dimensional, they "
- "must have the same batch dimension.");
+ if (dim_x.size() == 1 && dim_out[dim_out.size() - 2] == 1) {
+ std::swap(dim_out[dim_out.size() - 2], dim_out[dim_out.size() - 1]);
+ dim_out.resize(dim_out.size() - 1);
}
- int batchCount = std::max(batchCountX, batchCountY);
- std::vector<int64_t> dim_out;
- if (batchCount) {
- if (dim_x.size() > 3) {
- dim_out.insert(dim_out.begin(), out_dim.begin(), out_dim.end());
- } else {
- dim_out.push_back(batchCount);
- }
+ if (dim_y.size() == 1 && dim_out[dim_out.size() - 1] == 1) {
+ dim_out.resize(dim_out.size() - 1);
}
- if (!remove_initial_dim) {
- dim_out.push_back(M);
- }
- if (!remove_final_dim) {
- dim_out.push_back(N);
- }
- if (dim_out.size() == 0) {
- // We don't support 0-dimensional Tensors (scalars), so instead
- // treat the output as a Tensor of shape (1, ) in this case.
- dim_out.push_back(1);
+
+ if (dim_out.empty()) {
+ dim_out = {1};
}
context->SetOutputDim("Out", framework::make_ddim(dim_out));
context->ShareLoD("X", /*->*/ "Out");
diff --git a/paddle/fluid/operators/matmul_op.h b/paddle/fluid/operators/matmul_op.h
index f2e9cfdcdb..7b484d124a 100644
--- a/paddle/fluid/operators/matmul_op.h
+++ b/paddle/fluid/operators/matmul_op.h
@@ -15,55 +15,56 @@ limitations under the License. */
#pragma once
#include <algorithm>
#include <functional>
+#include <utility>
#include <vector>
#include "paddle/fluid/framework/op_registry.h"
+#include "paddle/fluid/operators/detail/safe_ref.h"
+#include "paddle/fluid/operators/math/blas.h"
#include "paddle/fluid/operators/math/math_function.h"
-#include "paddle/fluid/operators/math/matmul.h"
namespace paddle {
namespace operators {
-namespace matmul_detail {
+inline framework::DDim GetXDim(const framework::DDim& x_dim) {
+ if (x_dim.size() > 1) {
+ return x_dim;
+ }
+ return framework::make_ddim({1, x_dim[0]});
+}
-using Tensor = framework::Tensor;
-using DDim = framework::DDim;
-using framework::make_ddim;
-using framework::vectorize;
+inline framework::DDim GetYDim(const framework::DDim& y_dim) {
+ if (y_dim.size() > 1) {
+ return y_dim;
+ }
+ return framework::make_ddim({y_dim[0], 1});
+}
template <typename DeviceContext, typename T>
class MatMulKernel : public framework::OpKernel<T> {
public:
void Compute(const framework::ExecutionContext& context) const override {
- const Tensor& x = *context.Input<Tensor>("X");
- const Tensor& y = *context.Input<Tensor>("Y");
- Tensor* out = context.Output<Tensor>("Out");
+ auto& x =
+ detail::Ref(context.Input<framework::Tensor>("X"), "Cannot find X");
+ auto& y =
+ detail::Ref(context.Input<framework::Tensor>("Y"), "Cannot find Y");
+ auto* out = context.Output<framework::Tensor>("Out");
out->mutable_data<T>(context.GetPlace());
- bool transpose_x = context.Attr<bool>("transpose_X");
- bool transpose_y = context.Attr<bool>("transpose_Y");
- math::MatMulFunctor<DeviceContext, T>()(
- context.template device_context<DeviceContext>(), x, transpose_x, y,
- transpose_y, T(1), out, T(0));
+ auto blas = math::GetBlas<DeviceContext, T>(context);
+ auto mat_dim_a = math::GetMatDim(GetXDim(x.dims()), 0,
+ context.Attr<bool>("transpose_X"));
+ auto mat_dim_b = math::GetMatDim(GetYDim(y.dims()), 0,
+ context.Attr<bool>("transpose_Y"));
+ blas.MatMul(x, mat_dim_a, y, mat_dim_b, T(1), out, T(0));
}
};
-template <typename T>
-inline Tensor Reshape(const Tensor& input, const DDim& dims) {
- Tensor output;
- output.ShareDataWith(input);
- output.Resize(dims);
- return output;
-}
-
// Reshape a rank-3 tensor from P x M x N to (P * M) x N.
// Identity op if the tensor is not of rank 3.
-template <typename T>
-Tensor CombineBatchAndM(const Tensor& input) {
- Tensor output;
- output.ShareDataWith(input);
+inline framework::Tensor CombineBatchAndM(const framework::Tensor& input) {
+ auto output = input;
auto in_dims = input.dims();
if (in_dims.size() == 3) {
- std::vector<int64_t> out_dims = {in_dims[0] * in_dims[1], in_dims[2]};
- output.Resize(make_ddim(out_dims));
+ output.Resize({in_dims[0] * in_dims[1], in_dims[2]});
}
return output;
}
@@ -72,23 +73,57 @@ Tensor CombineBatchAndM(const Tensor& input) {
// (Warning: This requires transposing data and writes into new memory.)
// Identity op if the tensor is not of rank 3.
template <typename DeviceContext, typename T>
-Tensor CombineBatchAndN(const DeviceContext& context, const Tensor& input) {
- Tensor output;
+inline framework::Tensor CombineBatchAndN(const DeviceContext& context,
+ const framework::Tensor& input) {
auto in_dims = input.dims();
- if (in_dims.size() == 3) {
- output.Resize({in_dims[1], in_dims[0], in_dims[2]});
- output.mutable_data<T>(context.GetPlace());
- std::vector<int> axis = {1, 0, 2};
- math::Transpose<DeviceContext, T, 3> trans;
- trans(context, input, &output, axis);
- std::vector<int64_t> out_dims = {in_dims[1], in_dims[0] * in_dims[2]};
- output.Resize({in_dims[1], in_dims[0] * in_dims[2]});
- } else {
- output.ShareDataWith(input);
+ if (in_dims.size() != 3) {
+ return input;
}
+ framework::Tensor output;
+ output.Resize({in_dims[1], in_dims[0], in_dims[2]});
+ output.mutable_data<T>(context.GetPlace());
+ std::vector<int> axis = {1, 0, 2};
+ math::Transpose<DeviceContext, T, 3> trans;
+ trans(context, input, &output, axis);
+ output.Resize({in_dims[1], in_dims[0] * in_dims[2]});
+
return output;
}
+inline void NormalizeTensorShape(framework::Tensor* x,
+ const math::MatDim& mat_dim_x) {
+ int64_t h, w;
+ h = mat_dim_x.height_;
+ w = mat_dim_x.width_;
+ if (mat_dim_x.trans_) {
+ std::swap(w, h);
+ }
+ if (mat_dim_x.batch_size_) {
+ x->Resize({mat_dim_x.batch_size_, h, w});
+ } else {
+ x->Resize({h, w});
+ }
+}
+
+inline void NormalizeXYOutTensorShape(framework::Tensor* x,
+ framework::Tensor* y,
+ framework::Tensor* out, bool trans_a,
+ bool trans_b) {
+ auto x_dim = GetXDim(x->dims());
+ auto y_dim = GetYDim(y->dims());
+ auto mat_dim_x = math::GetMatDim(x_dim, 0, trans_a);
+ auto mat_dim_y = math::GetMatDim(y_dim, 0, trans_b);
+ if (mat_dim_x.batch_size_ == 0 && mat_dim_y.batch_size_ == 0) {
+ out->Resize({mat_dim_x.height_, mat_dim_y.width_});
+ } else {
+ out->Resize({std::max(mat_dim_x.batch_size_, mat_dim_y.batch_size_),
+ mat_dim_x.height_, mat_dim_y.width_});
+ }
+
+ NormalizeTensorShape(x, mat_dim_x);
+ NormalizeTensorShape(y, mat_dim_y);
+}
+
// Using dimensional constraints on matrix multiplication, it is
// straight-forward to check the following table for when X and Y
// are both matrices.
@@ -117,128 +152,91 @@ Tensor CombineBatchAndN(const DeviceContext& context, const Tensor& input) {
template <typename DeviceContext, typename T>
class MatMulGradKernel : public framework::OpKernel<T> {
public:
+ void MatMul(const framework::ExecutionContext& context,
+ const framework::Tensor& a, bool trans_a,
+ const framework::Tensor& b, bool trans_b,
+ framework::Tensor* out) const {
+ out->mutable_data<T>(context.GetPlace());
+ auto blas = math::GetBlas<DeviceContext, T>(context);
+ auto mat_dim_a = math::GetMatDim(a.dims(), 0, trans_a);
+ auto mat_dim_b = math::GetMatDim(b.dims(), 0, trans_b);
+ blas.MatMul(a, mat_dim_a, b, mat_dim_b, T(1), out, T(0));
+ }
+
+ void CalcInputGrad(const framework::ExecutionContext& context,
+ const framework::Tensor& a, bool trans_a,
+ bool is_combine_m_a, const framework::Tensor& b,
+ bool trans_b, bool is_combine_m_b,
+ framework::Tensor* out) const {
+ if (out == nullptr) return;
+ bool need_combine = (a.dims().size() == 3 || b.dims().size() == 3) &&
+ out->dims().size() == 2;
+ if (!need_combine) {
+ MatMul(context, a, trans_a, b, trans_b, out);
+ } else {
+ auto& ctx = context.template device_context<DeviceContext>();
+ MatMul(
+ context, is_combine_m_a ? CombineBatchAndM(a)
+ : CombineBatchAndN<DeviceContext, T>(ctx, a),
+ trans_a, is_combine_m_b ? CombineBatchAndM(b)
+ : CombineBatchAndN<DeviceContext, T>(ctx, b),
+ trans_b, out);
+ }
+ }
+
void Compute(const framework::ExecutionContext& context) const override {
- const Tensor& x = *context.Input<Tensor>("X");
- const Tensor& y = *context.Input<Tensor>("Y");
- const Tensor& dout = *context.Input<Tensor>(framework::GradVarName("Out"));
- Tensor* dx = context.Output<Tensor>(framework::GradVarName("X"));
- Tensor* dy = context.Output<Tensor>(framework::GradVarName("Y"));
+ auto x = *context.Input<framework::Tensor>("X");
+ auto y = *context.Input<framework::Tensor>("Y");
+ auto dout =
+ *context.Input<framework::Tensor>(framework::GradVarName("Out"));
+ auto* dx = context.Output<framework::Tensor>(framework::GradVarName("X"));
+ auto* dy = context.Output<framework::Tensor>(framework::GradVarName("Y"));
bool transpose_x = context.Attr<bool>("transpose_X");
bool transpose_y = context.Attr<bool>("transpose_Y");
- std::vector<int64_t> x_dims = vectorize(x.dims());
- std::vector<int64_t> y_dims = vectorize(y.dims());
-
- // If X is a vector, reshape it to a matrix.
- if (x_dims.size() == 1) {
- x_dims.insert(x_dims.begin(), 1);
- }
-
- // If Y is a vector, reshape it to a matrix.
- if (y_dims.size() == 1) {
- y_dims.push_back(1);
+ NormalizeXYOutTensorShape(&x, &y, &dout, transpose_x, transpose_y);
+ framework::DDim dx_dims;
+ if (dx) {
+ dx_dims = dx->dims();
+ if (dx_dims != x.dims()) {
+ dx->Resize(x.dims());
+ }
}
- int batch_count = 0;
- // The first rank-2 dimensions are accumulated on the batch_count, and the
- // last two dimensions are used for matrix multiplication.
- if (x_dims.size() > 3) {
- batch_count = accumulate(x_dims.begin(), x_dims.end() - 2, 1,
- std::multiplies<int>());
- }
- // Fix the dOut dimensions.
- int M = 0, N = 0, batchCountX = 0, batchCountY = 0;
-
- switch (x_dims.size()) {
- case 2:
- M = transpose_x ? x_dims[1] : x_dims[0];
- break;
- case 3:
- batchCountX = x_dims[0];
- M = transpose_x ? x_dims[2] : x_dims[1];
- break;
- default:
- batchCountX = batch_count;
- size_t mat_s = x_dims.size() - 2;
- M = transpose_x ? x_dims[mat_s + 1] : x_dims[mat_s];
+ framework::DDim dy_dims;
+ if (dy) {
+ dy_dims = dy->dims();
+ if (dy_dims != y.dims()) {
+ dy->Resize(y.dims());
+ }
}
- switch (y_dims.size()) {
- case 2:
- N = transpose_y ? y_dims[0] : y_dims[1];
- break;
- case 3:
- batchCountY = y_dims[0];
- N = transpose_y ? y_dims[1] : y_dims[2];
- break;
- default:
- batchCountY = batch_count;
- size_t mat_s = y_dims.size() - 2;
- N = transpose_y ? y_dims[mat_s] : y_dims[mat_s + 1];
- }
- if (batchCountX && batchCountY) {
- PADDLE_ENFORCE_EQ(
- batchCountX, batchCountY,
- "When Input(X) and Input(Y) are both three dimensional, they "
- "must have the same batch dimension.");
- }
- int batchCount = std::max(batchCountX, batchCountY);
- std::vector<int64_t> dout_dims = {M, N};
- if (batchCount) {
- if (x_dims.size() > 3) {
- dout_dims.insert(dout_dims.begin(), x_dims.begin(), x_dims.end() - 2);
- } else {
- dout_dims.insert(dout_dims.begin(), batchCount);
- }
+ if (transpose_x && transpose_y) {
+ CalcInputGrad(context, y, true, true, dout, true, false, dx);
+ CalcInputGrad(context, dout, true, true, x, true, false, dy);
+ } else if (transpose_x && !transpose_y) {
+ CalcInputGrad(context, y, false, false, dout, true, false, dx);
+ CalcInputGrad(context, x, false, false, dout, false, true, dy);
+ } else if (!transpose_x && transpose_y) {
+ CalcInputGrad(context, dout, false, false, y, false, true, dx);
+ CalcInputGrad(context, dout, true, true, x, false, true, dy);
+ } else {
+ CalcInputGrad(context, dout, false, false, y, true, false, dx);
+ CalcInputGrad(context, x, true, true, dout, false, true, dy);
}
- Tensor X = Reshape<T>(x, make_ddim(x_dims));
- Tensor Y = Reshape<T>(y, make_ddim(y_dims));
- Tensor dOut = Reshape<T>(dout, make_ddim(dout_dims));
- auto& dev_ctx = context.template device_context<DeviceContext>();
if (dx) {
- dx->mutable_data<T>(context.GetPlace());
- const Tensor& dOut_for_dX =
- (x_dims.size() == 2 && y_dims.size() == 3)
- ? CombineBatchAndN<DeviceContext, T>(dev_ctx, dOut)
- : dOut;
- if (x_dims.size() == 2 && y_dims.size() == 3) {
- Y = transpose_y ? CombineBatchAndM<T>(Y)
- : CombineBatchAndN<DeviceContext, T>(dev_ctx, Y);
- }
- if (transpose_x) {
- math::MatMulFunctor<DeviceContext, T>()(
- dev_ctx, Y, transpose_y, dOut_for_dX, transpose_x, T(1), dx, T(0));
- } else {
- math::MatMulFunctor<DeviceContext, T>()(
- dev_ctx, dOut_for_dX, transpose_x, Y, !transpose_y, T(1), dx, T(0));
+ if (dx_dims != x.dims()) {
+ dx->Resize(dx_dims);
}
}
-
if (dy) {
- dy->mutable_data<T>(context.GetPlace());
- const Tensor& dOut_for_dY = (y_dims.size() == 2 && x_dims.size() == 3)
- ? CombineBatchAndM<T>(dOut)
- : dOut;
- if (y_dims.size() == 2 && x_dims.size() == 3) {
- X = transpose_x ? CombineBatchAndN<DeviceContext, T>(dev_ctx, X)
- : CombineBatchAndM<T>(X);
- dOut = CombineBatchAndM<T>(dOut);
- }
- if (transpose_y) {
- math::MatMulFunctor<DeviceContext, T>()(
- dev_ctx, dOut_for_dY, transpose_y, X, transpose_x, T(1), dy, T(0));
- } else {
- math::MatMulFunctor<DeviceContext, T>()(
- dev_ctx, X, !transpose_x, dOut_for_dY, transpose_y, T(1), dy, T(0));
+ if (dy_dims != y.dims()) {
+ dy->Resize(dy_dims);
}
}
}
};
-} // namespace matmul_detail
-
-using matmul_detail::MatMulKernel;
-using matmul_detail::MatMulGradKernel;
} // namespace operators
} // namespace paddle
diff --git a/python/paddle/fluid/tests/unittests/test_matmul_op.py b/python/paddle/fluid/tests/unittests/test_matmul_op.py
index 44ac468389..cae2c8fa87 100644
--- a/python/paddle/fluid/tests/unittests/test_matmul_op.py
+++ b/python/paddle/fluid/tests/unittests/test_matmul_op.py
@@ -111,21 +111,24 @@ class Generator(object):
# Generate test cases for all possibilities
-for dim_X in [1, 2, 3]:
- for dim_Y in [1, 2, 3]:
- for transpose_X in [False, True]:
- for transpose_Y in [False, True]:
- test_name = (
- 'TestMatMulOp_dimX_{}_dim_Y_{}_transX_{}_transY_{}'.format(
- dim_X, dim_Y, transpose_X, transpose_Y))
- shape_X, shape_Y = generate_compatible_shapes(
- dim_X, dim_Y, transpose_X, transpose_Y)
- globals()[test_name] = type(test_name, (Generator, OpTest), {
- 'shape_X': shape_X,
- 'shape_Y': shape_Y,
- 'transpose_X': transpose_X,
- 'transpose_Y': transpose_Y,
- })
+def inject_test(dim_x, dim_y, trans_x, trans_y):
+ test_name = ('TestMatMulOp_dimX_{}_dim_Y_{}_transX_{}_transY_{}'.format(
+ dim_x, dim_y, trans_x, trans_y))
+ shape_x, shape_y = generate_compatible_shapes(dim_x, dim_y, trans_x,
+ trans_y)
+ globals()[test_name] = type(test_name, (Generator, OpTest), {
+ 'shape_X': shape_x,
+ 'shape_Y': shape_y,
+ 'transpose_X': trans_x,
+ 'transpose_Y': trans_y,
+ })
+
+
+for dim_X in (1, 2, 3):
+ for dim_Y in (1, 2, 3):
+ for transose_x in (False, True):
+ for transose_y in (False, True):
+ inject_test(dim_X, dim_Y, transose_x, transose_y)
# Test case n-dim
@@ -149,7 +152,7 @@ def generate_compatible_shapes(dim, transpose_X, transpose_Y):
return shape_X, shape_Y
-# Test case n-dim
+# # Test case n-dim
for dim in [4]:
for transpose_X in [False, True]:
for transpose_Y in [False, True]:
From 17009d0627a97274299249e3680f58d6e2270ff7 Mon Sep 17 00:00:00 2001
From: typhoonzero <typhoonzero1986@gmail.com>
Date: Mon, 7 May 2018 17:10:53 +0800
Subject: [PATCH 014/195] workable version
---
paddle/fluid/operators/CMakeLists.txt | 1 +
paddle/fluid/operators/test_send_nccl_id.cc | 88 +++++++++++++++++++++
paddle/fluid/platform/nccl_helper.h | 7 +-
python/paddle/fluid/parallel_executor.py | 5 ++
4 files changed, 98 insertions(+), 3 deletions(-)
create mode 100644 paddle/fluid/operators/test_send_nccl_id.cc
diff --git a/paddle/fluid/operators/CMakeLists.txt b/paddle/fluid/operators/CMakeLists.txt
index ad0732131c..2b8df6c35f 100644
--- a/paddle/fluid/operators/CMakeLists.txt
+++ b/paddle/fluid/operators/CMakeLists.txt
@@ -205,6 +205,7 @@ if(WITH_DISTRIBUTE)
set_source_files_properties(send_barrier_op.cc PROPERTIES COMPILE_FLAGS ${DISTRIBUTE_COMPILE_FLAGS})
set_source_files_properties(send_recv_op_test.cc PROPERTIES COMPILE_FLAGS ${DISTRIBUTE_COMPILE_FLAGS})
cc_test(test_send_recv SRCS send_recv_op_test.cc DEPS prefetch_op send_op listen_and_serv_op sum_op executor)
+ cc_test(test_send_nccl_id SRCS test_send_nccl_id.cc DEPS send_op listen_and_serv_op executor)
else()
set(DEPS_OPS ${DEPS_OPS} send_op prefetch_op recv_op listen_and_serv_op send_vars_op send_barrier_op gen_nccl_id_op)
endif()
diff --git a/paddle/fluid/operators/test_send_nccl_id.cc b/paddle/fluid/operators/test_send_nccl_id.cc
new file mode 100644
index 0000000000..7a8b425665
--- /dev/null
+++ b/paddle/fluid/operators/test_send_nccl_id.cc
@@ -0,0 +1,88 @@
+/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License. */
+
+#include <unistd.h>
+#include <string>
+#include <thread> // NOLINT
+
+#include "gtest/gtest.h"
+#include "paddle/fluid/framework/op_registry.h"
+#include "paddle/fluid/framework/operator.h"
+#include "paddle/fluid/framework/program_desc.h"
+#include "paddle/fluid/operators/detail/grpc_client.h"
+#include "paddle/fluid/operators/listen_and_serv_op.h"
+#include "paddle/fluid/operators/math/math_function.h"
+#include "paddle/fluid/operators/math/selected_rows_functor.h"
+#include "paddle/fluid/string/printf.h"
+
+USE_NO_KERNEL_OP(listen_and_serv);
+
+namespace f = paddle::framework;
+namespace p = paddle::platform;
+namespace m = paddle::operators::math;
+namespace detail = paddle::operators::detail;
+namespace string = paddle::string;
+
+std::unique_ptr<detail::AsyncGRPCServer> rpc_service;
+
+void StartServer() {
+ f::Scope scope;
+ p::CPUPlace place;
+ scope.Var("NCCLID");
+ p::DeviceContextPool& pool = p::DeviceContextPool::Instance();
+ auto& dev_ctx = *pool.Get(p::CPUPlace());
+
+ rpc_service.reset(new detail::AsyncGRPCServer("127.0.0.1:0", true));
+
+ f::ProgramDesc empty_program;
+ f::Executor executor(dev_ctx.GetPlace());
+ rpc_service->SetScope(&scope);
+ rpc_service->SetDevCtx(&dev_ctx);
+ rpc_service->SetProgram(&empty_program);
+ rpc_service->SetExecutor(&executor);
+
+ std::thread server_thread(
+ std::bind(&detail::AsyncGRPCServer::RunSyncUpdate, rpc_service.get()));
+ rpc_service->SetCond(0);
+ auto recv = rpc_service->Get();
+ LOG(INFO) << "got nccl id and stop server...";
+ rpc_service->ShutDown();
+ server_thread.join();
+}
+
+TEST(SendNcclId, Normal) {
+ std::thread server_thread(StartServer);
+ // wait server to start
+ sleep(2);
+
+ f::Scope scope;
+ p::CPUPlace place;
+ p::DeviceContextPool& pool = p::DeviceContextPool::Instance();
+ auto& dev_ctx = *pool.Get(p::CPUPlace());
+
+ auto var = scope.Var("NCCLID");
+ // var->SetType(f::proto::VarType_Type_RAW);
+ auto id = var->GetMutable<ncclUniqueId>();
+ p::dynload::ncclGetUniqueId(id);
+
+ int port = rpc_service->GetSelectedPort();
+ std::string ep = string::Sprintf("127.0.0.1:%d", port);
+ detail::RPCClient client;
+
+ client.AsyncSendVariable(ep, dev_ctx, scope, "NCCLID");
+ client.Wait();
+ server_thread.join();
+ auto* ptr = rpc_service.release();
+ delete ptr;
+}
diff --git a/paddle/fluid/platform/nccl_helper.h b/paddle/fluid/platform/nccl_helper.h
index f3c4c92afa..094c47007e 100644
--- a/paddle/fluid/platform/nccl_helper.h
+++ b/paddle/fluid/platform/nccl_helper.h
@@ -14,6 +14,7 @@
#pragma once
+#include <stdio.h>
#include <thread> // NOLINT
#include <typeindex>
#include <vector>
@@ -100,13 +101,13 @@ struct NCCLContextMap {
}
} else {
PADDLE_ENFORCE_GT(node_count, 0);
- PADDLE_ENFORCE_EQ(node_count % places.size(), 0,
- "must have same number of GPUs on each node");
+ // TODO(wuyi): need to ensure each node have same number of GPUs
{
- std::lock_guard<std::mutex> guard(NCCLGroupGuard::NCCLMutex());
int nranks = node_count * order_.size();
+ NCCLGroupGuard gurad;
for (auto &gpu_id : order_) {
int rank = trainer_id * order_.size() + gpu_id;
+ VLOG(3) << "init nccl rank: " << rank << " nranks: " << nranks;
PADDLE_ENFORCE(cudaSetDevice(gpu_id));
PADDLE_ENFORCE(platform::dynload::ncclCommInitRank(
comms.get() + gpu_id, nranks, *nccl_id, rank));
diff --git a/python/paddle/fluid/parallel_executor.py b/python/paddle/fluid/parallel_executor.py
index 50ec438bee..bd92ac548d 100644
--- a/python/paddle/fluid/parallel_executor.py
+++ b/python/paddle/fluid/parallel_executor.py
@@ -53,6 +53,11 @@ class ParallelExecutor(object):
gradients of each device and scaled gradients would be
aggregated. Otherwise, a customized scale value should be fed
to the network.
+ num_nodes(int, default 0): If greater than 0, NCCL will be
+ initialized with multpile rank of nodes, each node should have
+ same number of GPUs. Distributed training will be enabled then.
+ trainer_id(int, default 0): Must use together with num_nodes.
+ trainer_id is the "rank" of current node starts from 0.
Returns:
A ParallelExecutor object.
From 0f86397d812e89fc96c31ef573d0f938fac24b09 Mon Sep 17 00:00:00 2001
From: typhoonzero <typhoonzero1986@gmail.com>
Date: Mon, 7 May 2018 19:11:50 +0800
Subject: [PATCH 015/195] fix build
---
paddle/fluid/operators/detail/sendrecvop_utils.cc | 10 ++++++++--
paddle/fluid/operators/detail/variable_response.cc | 11 +++++++----
2 files changed, 15 insertions(+), 6 deletions(-)
diff --git a/paddle/fluid/operators/detail/sendrecvop_utils.cc b/paddle/fluid/operators/detail/sendrecvop_utils.cc
index 207ea3cb8b..bde418a45a 100644
--- a/paddle/fluid/operators/detail/sendrecvop_utils.cc
+++ b/paddle/fluid/operators/detail/sendrecvop_utils.cc
@@ -14,7 +14,9 @@ limitations under the License. */
#include "paddle/fluid/operators/detail/sendrecvop_utils.h"
+#ifdef PADDLE_WITH_CUDA
#include <nccl.h>
+#endif
#include <sys/time.h>
#include <thread> // NOLINT
@@ -51,10 +53,12 @@ void SerializeToByteBuffer(const std::string& name, framework::Variable* var,
e.WriteUint64(VarMsg::kTypeFieldNumber, 0);
} else if (var->IsType<framework::SelectedRows>()) {
e.WriteUint64(VarMsg::kTypeFieldNumber, 1);
+#ifdef PADDLE_WITH_CUDA
} else if (var->IsType<ncclUniqueId>()) {
// NOTE: sendrecv only support RAW type for NCCL_ID
VLOG(3) << "serilizing: setting var type nccl id";
e.WriteUint64(VarMsg::kTypeFieldNumber, 2);
+#endif
}
if (!out_name.empty()) {
@@ -141,17 +145,19 @@ void SerializeToByteBuffer(const std::string& name, framework::Variable* var,
}
payload_size = tensor->numel() * framework::SizeOfType(tensor->type());
e.WriteVarlengthBeginning(VarMsg::kSerializedFieldNumber, payload_size);
+#ifdef PADDLE_WITH_CUDA
} else if (var->IsType<ncclUniqueId>()) {
// ===========================NCCL ID==================================
e.WriteVarlengthBeginning(VarMsg::kSerializedFieldNumber,
NCCL_UNIQUE_ID_BYTES);
ncclUniqueId* uid = var->GetMutable<ncclUniqueId>();
e.WriteRawBytes(std::string(uid->internal, NCCL_UNIQUE_ID_BYTES));
+#endif
} else {
PADDLE_THROW("Serialize does not support type: %s",
typeid(var->Type()).name());
}
-
+#ifdef PADDLE_WITH_CUDA
if (var->IsType<ncclUniqueId>()) {
// for serialize NCCL_ID
::grpc::Slice slices(e.size());
@@ -160,7 +166,7 @@ void SerializeToByteBuffer(const std::string& name, framework::Variable* var,
msg->Swap(&tmp);
return;
}
-
+#endif
// steal reference of tensor data
::grpc::Slice slices[4]; // metadata, tensor, rows meta, rows
int num_slices = 2; // only SelectedRows have rows buffer
diff --git a/paddle/fluid/operators/detail/variable_response.cc b/paddle/fluid/operators/detail/variable_response.cc
index 64fd84736d..9cf6dd90fc 100644
--- a/paddle/fluid/operators/detail/variable_response.cc
+++ b/paddle/fluid/operators/detail/variable_response.cc
@@ -17,6 +17,9 @@
#include <string>
#include <utility>
#include <vector>
+#ifdef PADDLE_WITH_CUDA
+#include <nccl.h>
+#endif
#include "paddle/fluid/operators/detail/send_recv.pb.h"
#include "paddle/fluid/operators/detail/sendrecvop_utils.h"
@@ -378,19 +381,19 @@ int VariableResponse::Parse(Source* source) {
}
if (meta_.type() == sendrecv::NCCL_ID) {
- VLOG(3) << "parse nccl id request";
+#ifdef PADDLE_WITH_CUDA
auto* var = scope_->FindVar(meta_.varname());
if (var != nullptr) {
- VLOG(3) << "parse nccl id: length " << length;
ncclUniqueId* id = var->GetMutable<ncclUniqueId>();
if (!ReadRaw(&input, *dev_ctx_, platform::CPUPlace(), id->internal,
length)) {
return tag;
}
- // memcpy(id->internal, meta_.serialized().c_str(),
- // meta_.serialized().size());
}
break;
+#else
+ PADDLE_THROW("Not compiled with CUDA!");
+#endif
}
framework::DDim dims = GetDims(meta_.dims());
From 55218dafbc6831da485b63c4180cd44d8dc8c8ef Mon Sep 17 00:00:00 2001
From: Yao Cheng <chengyao@pku.edu.cn>
Date: Tue, 8 May 2018 10:38:57 +0800
Subject: [PATCH 016/195] add prependAllocatedop
---
paddle/fluid/framework/block_desc.cc | 5 +++++
paddle/fluid/framework/block_desc.h | 2 ++
2 files changed, 7 insertions(+)
diff --git a/paddle/fluid/framework/block_desc.cc b/paddle/fluid/framework/block_desc.cc
index d72b64700f..90cbe7ae13 100644
--- a/paddle/fluid/framework/block_desc.cc
+++ b/paddle/fluid/framework/block_desc.cc
@@ -135,6 +135,11 @@ OpDesc *BlockDesc::PrependOp() {
return ops_.front().get();
}
+void BlockDesc::PrependAllocatedOp(std::unique_ptr<OpDesc> &&op_desc) {
+ need_update_ = true;
+ ops_.emplace_front(std::move(op_desc));
+}
+
void BlockDesc::RemoveOp(size_t s, size_t e) {
if (ops_.begin() + s == ops_.end() || ops_.begin() + e == ops_.end()) {
return;
diff --git a/paddle/fluid/framework/block_desc.h b/paddle/fluid/framework/block_desc.h
index 3bd90f3890..5325583b19 100644
--- a/paddle/fluid/framework/block_desc.h
+++ b/paddle/fluid/framework/block_desc.h
@@ -87,6 +87,8 @@ class BlockDesc {
OpDesc *PrependOp();
+ void PrependAllocatedOp(std::unique_ptr<OpDesc> &&op_desc);
+
void RemoveOp(size_t s, size_t e);
std::vector<OpDesc *> AllOps() const;
From 0a13d3c67a7be24cb541b964b99b42ce851de618 Mon Sep 17 00:00:00 2001
From: Yu Yang <yuyang18@baidu.com>
Date: Tue, 8 May 2018 11:16:36 +0800
Subject: [PATCH 017/195] Move MatMul to blas_impl.h
Rename MatDim to MatDescriptor
---
paddle/fluid/operators/math/blas.cc | 5 +++--
paddle/fluid/operators/math/blas.h | 29 +++++--------------------
paddle/fluid/operators/math/blas_impl.h | 25 +++++++++++++++++++++
paddle/fluid/operators/matmul_op.h | 2 +-
4 files changed, 35 insertions(+), 26 deletions(-)
diff --git a/paddle/fluid/operators/math/blas.cc b/paddle/fluid/operators/math/blas.cc
index 7427ceac60..3e09ef7a24 100644
--- a/paddle/fluid/operators/math/blas.cc
+++ b/paddle/fluid/operators/math/blas.cc
@@ -18,8 +18,9 @@
namespace paddle {
namespace operators {
namespace math {
-MatDim GetMatDim(const framework::DDim& dim, int num_flatten_cols, bool trans) {
- MatDim retv;
+MatDescriptor GetMatDim(const framework::DDim& dim, int num_flatten_cols,
+ bool trans) {
+ MatDescriptor retv;
if (num_flatten_cols > 1) {
auto flatten_dim = framework::flatten_to_2d(dim, num_flatten_cols);
retv.height_ = flatten_dim[0];
diff --git a/paddle/fluid/operators/math/blas.h b/paddle/fluid/operators/math/blas.h
index cca967f33f..0c0794125a 100644
--- a/paddle/fluid/operators/math/blas.h
+++ b/paddle/fluid/operators/math/blas.h
@@ -46,7 +46,7 @@ namespace paddle {
namespace operators {
namespace math {
-struct MatDim {
+struct MatDescriptor {
int64_t height_;
int64_t width_;
int64_t stride_{0};
@@ -54,8 +54,8 @@ struct MatDim {
bool trans_;
};
-extern MatDim GetMatDim(const framework::DDim& tensor, int num_flatten_cols,
- bool trans);
+extern MatDescriptor GetMatDim(const framework::DDim& tensor,
+ int num_flatten_cols, bool trans);
template <typename DeviceContext>
class Blas {
@@ -102,26 +102,9 @@ class Blas {
int batchCount, int64_t strideA, int64_t strideB) const;
template <typename T>
- void MatMul(const framework::Tensor& mat_a, const MatDim& dim_a,
- const framework::Tensor& mat_b, const MatDim& dim_b, T alpha,
- framework::Tensor* mat_out, T beta) const {
- PADDLE_ENFORCE_EQ(dim_a.width_, dim_b.height_);
- CBLAS_TRANSPOSE transA = !dim_a.trans_ ? CblasNoTrans : CblasTrans;
- CBLAS_TRANSPOSE transB = !dim_b.trans_ ? CblasNoTrans : CblasTrans;
- if (dim_a.batch_size_ == 0 && dim_b.batch_size_ == 0) {
- this->template GEMM<T>(transA, transB, dim_a.height_, dim_b.width_,
- dim_a.width_, alpha, mat_a.data<T>(),
- mat_b.data<T>(), beta, mat_out->data<T>());
- } else {
- PADDLE_ENFORCE(dim_a.batch_size_ == dim_b.batch_size_ ||
- dim_a.batch_size_ == 0 || dim_b.batch_size_ == 0);
- this->template BatchedGEMM<T>(
- transA, transB, dim_a.height_, dim_b.width_, dim_a.width_, alpha,
- mat_a.data<T>(), mat_b.data<T>(), beta, mat_out->data<T>(),
- dim_a.batch_size_ == 0 ? dim_b.batch_size_ : dim_a.batch_size_,
- dim_a.stride_, dim_b.stride_);
- }
- }
+ void MatMul(const framework::Tensor& mat_a, const MatDescriptor& dim_a,
+ const framework::Tensor& mat_b, const MatDescriptor& dim_b,
+ T alpha, framework::Tensor* mat_out, T beta) const;
private:
const DeviceContext& context_;
diff --git a/paddle/fluid/operators/math/blas_impl.h b/paddle/fluid/operators/math/blas_impl.h
index 7360cc0a90..577cbe3beb 100644
--- a/paddle/fluid/operators/math/blas_impl.h
+++ b/paddle/fluid/operators/math/blas_impl.h
@@ -180,6 +180,31 @@ void Blas<platform::CPUDeviceContext>::BatchedGEMM(
#endif
}
+template <typename DeviceContext>
+template <typename T>
+void Blas<DeviceContext>::MatMul(const framework::Tensor &mat_a,
+ const MatDescriptor &dim_a,
+ const framework::Tensor &mat_b,
+ const MatDescriptor &dim_b, T alpha,
+ framework::Tensor *mat_out, T beta) const {
+ PADDLE_ENFORCE_EQ(dim_a.width_, dim_b.height_);
+ CBLAS_TRANSPOSE transA = !dim_a.trans_ ? CblasNoTrans : CblasTrans;
+ CBLAS_TRANSPOSE transB = !dim_b.trans_ ? CblasNoTrans : CblasTrans;
+ if (dim_a.batch_size_ == 0 && dim_b.batch_size_ == 0) {
+ this->template GEMM<T>(transA, transB, dim_a.height_, dim_b.width_,
+ dim_a.width_, alpha, mat_a.data<T>(),
+ mat_b.data<T>(), beta, mat_out->data<T>());
+ } else {
+ PADDLE_ENFORCE(dim_a.batch_size_ == dim_b.batch_size_ ||
+ dim_a.batch_size_ == 0 || dim_b.batch_size_ == 0);
+ this->template BatchedGEMM<T>(
+ transA, transB, dim_a.height_, dim_b.width_, dim_a.width_, alpha,
+ mat_a.data<T>(), mat_b.data<T>(), beta, mat_out->data<T>(),
+ dim_a.batch_size_ == 0 ? dim_b.batch_size_ : dim_a.batch_size_,
+ dim_a.stride_, dim_b.stride_);
+ }
+}
+
} // namespace math
} // namespace operators
} // namespace paddle
diff --git a/paddle/fluid/operators/matmul_op.h b/paddle/fluid/operators/matmul_op.h
index 7b484d124a..9bf39026ff 100644
--- a/paddle/fluid/operators/matmul_op.h
+++ b/paddle/fluid/operators/matmul_op.h
@@ -91,7 +91,7 @@ inline framework::Tensor CombineBatchAndN(const DeviceContext& context,
}
inline void NormalizeTensorShape(framework::Tensor* x,
- const math::MatDim& mat_dim_x) {
+ const math::MatDescriptor& mat_dim_x) {
int64_t h, w;
h = mat_dim_x.height_;
w = mat_dim_x.width_;
From fcd31d616173610ca6daeb96fa0a7eea923701dc Mon Sep 17 00:00:00 2001
From: Yu Yang <yuyang18@baidu.com>
Date: Tue, 8 May 2018 13:19:29 +0800
Subject: [PATCH 018/195] Follow comments and polish code names
---
paddle/fluid/operators/math/blas.cc | 34 ++-
paddle/fluid/operators/math/blas.h | 37 +++-
paddle/fluid/operators/matmul_op.cc | 280 ++++++++++++++++++++++++-
paddle/fluid/operators/matmul_op.cu.cc | 22 --
paddle/fluid/operators/matmul_op.h | 242 ---------------------
5 files changed, 323 insertions(+), 292 deletions(-)
delete mode 100644 paddle/fluid/operators/matmul_op.cu.cc
delete mode 100644 paddle/fluid/operators/matmul_op.h
diff --git a/paddle/fluid/operators/math/blas.cc b/paddle/fluid/operators/math/blas.cc
index 3e09ef7a24..6a143b3c05 100644
--- a/paddle/fluid/operators/math/blas.cc
+++ b/paddle/fluid/operators/math/blas.cc
@@ -18,34 +18,26 @@
namespace paddle {
namespace operators {
namespace math {
-MatDescriptor GetMatDim(const framework::DDim& dim, int num_flatten_cols,
- bool trans) {
+MatDescriptor CreateMatrixDescriptor(const framework::DDim &tensor_dim,
+ int num_flatten_cols, bool trans) {
+ PADDLE_ENFORCE_GT(tensor_dim.size(), 1);
MatDescriptor retv;
if (num_flatten_cols > 1) {
- auto flatten_dim = framework::flatten_to_2d(dim, num_flatten_cols);
+ auto flatten_dim = framework::flatten_to_2d(tensor_dim, num_flatten_cols);
retv.height_ = flatten_dim[0];
retv.width_ = flatten_dim[1];
} else {
- if (dim.size() == 1) {
- retv.height_ = 1;
- retv.width_ = dim[0];
- } else if (dim.size() == 2) {
- retv.height_ = dim[0];
- retv.width_ = dim[1];
+ if (tensor_dim.size() == 2) {
+ retv.height_ = tensor_dim[0];
+ retv.width_ = tensor_dim[1];
} else {
- if (dim.size() == 3) {
- retv.batch_size_ = dim[0];
- retv.height_ = dim[1];
- retv.width_ = dim[2];
- } else {
- auto dim_vec = framework::vectorize(dim);
- retv.batch_size_ = 1;
- for (size_t i = 0; i < dim_vec.size() - 2; ++i) {
- retv.batch_size_ *= dim_vec[i];
- retv.height_ = dim_vec[dim_vec.size() - 2];
- retv.width_ = dim_vec[dim_vec.size() - 1];
- }
+ auto dim_vec = framework::vectorize(tensor_dim);
+ retv.batch_size_ = 1;
+ for (size_t i = 0; i < dim_vec.size() - 2; ++i) {
+ retv.batch_size_ *= dim_vec[i];
}
+ retv.height_ = dim_vec[dim_vec.size() - 2];
+ retv.width_ = dim_vec[dim_vec.size() - 1];
retv.stride_ = retv.height_ * retv.width_;
}
}
diff --git a/paddle/fluid/operators/math/blas.h b/paddle/fluid/operators/math/blas.h
index 0c0794125a..dabde43850 100644
--- a/paddle/fluid/operators/math/blas.h
+++ b/paddle/fluid/operators/math/blas.h
@@ -46,6 +46,25 @@ namespace paddle {
namespace operators {
namespace math {
+/**
+ * Matrix Descriptor of a memory buffer.
+ *
+ * It is used for Blas::MatMul. MatMul operator can be batched.
+ * if Mat A is [BatchSize, H, W], Mat B is [BatchSize, H, W]. It will be a
+ * `batch_size` times of GEMM. The batched GEMM could be faster base on the
+ * implementation of the blas library. The batch size could be zero. If any
+ * matrix of `matmul` has a batch size, the will be a batched GEMM, too. e.g.,
+ * Mat A is [BatchSize, H1, W2], and Mat B [H2, W2], The result matrix wil be
+ * [BatchSize, H1, W2]
+ *
+ * The boolean flag, `trans`, describe the memory is the transpose of matrix or
+ * not. If the trans is true, the last two dims of matrix are transposed. The
+ * memory layout of the matrix is [Width, Height] or [BatchSize, Width, Height].
+ *
+ * The MatDescriptor is not only the dimension or shape of a matrix, it also
+ * contains the layout, stride of matrix. It is clearer to have a structure than
+ * reuse `DDim`.
+ */
struct MatDescriptor {
int64_t height_;
int64_t width_;
@@ -54,8 +73,22 @@ struct MatDescriptor {
bool trans_;
};
-extern MatDescriptor GetMatDim(const framework::DDim& tensor,
- int num_flatten_cols, bool trans);
+/**
+ * Create Matrix Descriptor from a tensor dim, num_flatten_cols, and transpose
+ * flag
+ *
+ * @param tensor_dim: The dimension of the tensor. The rank of this dimension
+ * must larger than 1.
+ *
+ * @param num_flatten_cols: Reshape a tensor to a matrix. The matrix's first
+ * dimension(column length) will be the product of tensor's first `num_col_dims`
+ * dimensions. If num_flatten_cols is zero, the first N-2 dimension will be the
+ * batch_size of descriptor.
+ *
+ * @param trans: True if the matrix is transposed.
+ */
+extern MatDescriptor CreateMatrixDescriptor(const framework::DDim& tensor_dim,
+ int num_flatten_cols, bool trans);
template <typename DeviceContext>
class Blas {
diff --git a/paddle/fluid/operators/matmul_op.cc b/paddle/fluid/operators/matmul_op.cc
index c285d461e8..da21b8ad7d 100644
--- a/paddle/fluid/operators/matmul_op.cc
+++ b/paddle/fluid/operators/matmul_op.cc
@@ -12,14 +12,257 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
-#include "paddle/fluid/operators/matmul_op.h"
#include <algorithm>
+#include <utility>
#include <vector>
+#include "paddle/fluid/framework/op_registry.h"
+#include "paddle/fluid/operators/detail/safe_ref.h"
+#include "paddle/fluid/operators/math/blas.h"
namespace paddle {
namespace operators {
+/**
+ * Get row matrix shape from a vector shape. If the rank of x_dim > 1, the
+ * original x_dim is returned.
+ */
+static framework::DDim RowMatrixFromVector(const framework::DDim& x_dim) {
+ if (x_dim.size() > 1) {
+ return x_dim;
+ }
+ return framework::make_ddim({1, x_dim[0]});
+}
+
+/**
+ * Get column matrix shape from a vector shape. If the ran of y_dim > 1, the
+ * original y_dim is returned.
+ */
+static framework::DDim ColumnMatrixFromVector(const framework::DDim& y_dim) {
+ if (y_dim.size() > 1) {
+ return y_dim;
+ }
+ return framework::make_ddim({y_dim[0], 1});
+}
+
+template <typename DeviceContext, typename T>
+class MatMulKernel : public framework::OpKernel<T> {
+ public:
+ void Compute(const framework::ExecutionContext& context) const override {
+ auto& x =
+ detail::Ref(context.Input<framework::Tensor>("X"), "Cannot find X");
+ auto& y =
+ detail::Ref(context.Input<framework::Tensor>("Y"), "Cannot find Y");
+ auto* out = context.Output<framework::Tensor>("Out");
+ out->mutable_data<T>(context.GetPlace());
+
+ auto blas = math::GetBlas<DeviceContext, T>(context);
+ auto mat_dim_a = math::CreateMatrixDescriptor(
+ RowMatrixFromVector(x.dims()), 0, context.Attr<bool>("transpose_X"));
+ auto mat_dim_b = math::CreateMatrixDescriptor(
+ ColumnMatrixFromVector(y.dims()), 0, context.Attr<bool>("transpose_Y"));
+ blas.MatMul(x, mat_dim_a, y, mat_dim_b, T(1), out, T(0));
+ }
+};
+
+// Reshape a rank-3 tensor from P x M x N to (P * M) x N.
+// Identity op if the tensor is not of rank 3.
+static framework::Tensor FoldInitDims(const framework::Tensor& input) {
+ auto output = input;
+ auto in_dims = input.dims();
+ if (in_dims.size() == 3) {
+ output.Resize({in_dims[0] * in_dims[1], in_dims[2]});
+ }
+ return output;
+}
+
+// Reshape a rank-3 tensor from P x M x N to M x (P * N).
+// (Warning: This requires transposing data and writes into new memory.)
+// Identity op if the tensor is not of rank 3.
+template <typename DeviceContext, typename T>
+static framework::Tensor FoldHeadAndLastDims(const DeviceContext& context,
+ const framework::Tensor& input) {
+ auto in_dims = input.dims();
+ if (in_dims.size() != 3) {
+ return input;
+ }
+ framework::Tensor output;
+ output.Resize({in_dims[1], in_dims[0], in_dims[2]});
+ output.mutable_data<T>(context.GetPlace());
+ std::vector<int> axis = {1, 0, 2};
+ math::Transpose<DeviceContext, T, 3> trans;
+ trans(context, input, &output, axis);
+ output.Resize({in_dims[1], in_dims[0] * in_dims[2]});
-using framework::Tensor;
+ return output;
+}
+
+/**
+ * Reshape a tensor to 3-D or 2-D tensor by matrix descriptor.
+ *
+ * The shape would be [BatchSize, H, W] or [H, W].
+ * If transposed, `H,W` will be swapped.
+ */
+static void ReshapeTensorIntoMatrixSequence(
+ framework::Tensor* x, const math::MatDescriptor& descriptor) {
+ int64_t h, w;
+ h = descriptor.height_;
+ w = descriptor.width_;
+ if (descriptor.trans_) {
+ std::swap(w, h);
+ }
+ if (descriptor.batch_size_) {
+ x->Resize({descriptor.batch_size_, h, w});
+ } else {
+ x->Resize({h, w});
+ }
+}
+
+/**
+ * Reshape the x,y,out tensor to 3-D or 2-D tensor by matrix descriptor
+ * Out = matmul(x, y)
+ *
+ * This method will first calculate X,Y matrix sequence, and then calculate
+ * the out shape.
+ *
+ * Assume X = [BatchSize, H1, W1], Y = [BatchSize, H2, W2]
+ * The out = [BatchSize, H1, W2]
+ *
+ * If there is no batch size in `X` and `Y`, the out will be [H1, W2]
+ * If any of `X` and `Y` has batch size BatchSize, the out will have the
+ * BatchSize.
+ */
+static void ReshapeXYOutIntoMatrixSequence(framework::Tensor* x,
+ framework::Tensor* y,
+ framework::Tensor* out, bool trans_x,
+ bool trans_y) {
+ auto x_dim = RowMatrixFromVector(x->dims());
+ auto y_dim = ColumnMatrixFromVector(y->dims());
+ auto mat_dim_x = math::CreateMatrixDescriptor(x_dim, 0, trans_x);
+ auto mat_dim_y = math::CreateMatrixDescriptor(y_dim, 0, trans_y);
+ if (mat_dim_x.batch_size_ == 0 && mat_dim_y.batch_size_ == 0) {
+ out->Resize({mat_dim_x.height_, mat_dim_y.width_});
+ } else {
+ out->Resize({std::max(mat_dim_x.batch_size_, mat_dim_y.batch_size_),
+ mat_dim_x.height_, mat_dim_y.width_});
+ }
+
+ ReshapeTensorIntoMatrixSequence(x, mat_dim_x);
+ ReshapeTensorIntoMatrixSequence(y, mat_dim_y);
+}
+
+// Using dimensional constraints on matrix multiplication, it is
+// straight-forward to check the following table for when X and Y
+// are both matrices.
+//
+// transpose_X | False | True | False | True
+// transpose_Y | False | False | True | True
+// -----------+----------+----------+----------+-----------
+// dX = | dOut Y^T | Y dOut^T | dOut Y | Y^T dOut^T
+// dY = | X^T dOut | X dOut | dOut^T X | dOut^T X^T
+//
+// When X is a vector of size K, we treat it instead as a matrix of shape
+// (1, K). Similarly, when Y is a vector of size K, we treat it instead as
+// a matrix of shape (K, 1).
+//
+// When X and Y are both 3-dimensional tensors, then the first dimension
+// the batch dimension can be ignored and the exact same formulas apply
+// as for two matrices.
+//
+// Finally, when, e.g., X is a 3-dimensional tensor but Y is a matrix, we end
+// up with formulas like
+//
+// dY_{ij} = \sum_{p, m} X_{pmi} dOut_{pmj}
+//
+// To handle this sort of scenario, we reshape X : P x M x K, dOut: P x M x N
+// to X: (P * M) x K, dOut: (P * M) x N.
+template <typename DeviceContext, typename T>
+class MatMulGradKernel : public framework::OpKernel<T> {
+ public:
+ void MatMul(const framework::ExecutionContext& context,
+ const framework::Tensor& a, bool trans_a,
+ const framework::Tensor& b, bool trans_b,
+ framework::Tensor* out) const {
+ out->mutable_data<T>(context.GetPlace());
+ auto blas = math::GetBlas<DeviceContext, T>(context);
+ auto mat_dim_a = math::CreateMatrixDescriptor(a.dims(), 0, trans_a);
+ auto mat_dim_b = math::CreateMatrixDescriptor(b.dims(), 0, trans_b);
+ blas.MatMul(a, mat_dim_a, b, mat_dim_b, T(1), out, T(0));
+ }
+
+ void CalcInputGrad(const framework::ExecutionContext& context,
+ const framework::Tensor& a, bool trans_a,
+ bool is_fold_init_dims_a, const framework::Tensor& b,
+ bool trans_b, bool is_fold_init_dims_b,
+ framework::Tensor* out) const {
+ if (out == nullptr) return;
+ bool need_combine = (a.dims().size() == 3 || b.dims().size() == 3) &&
+ out->dims().size() == 2;
+ if (!need_combine) {
+ MatMul(context, a, trans_a, b, trans_b, out);
+ } else {
+ auto& ctx = context.template device_context<DeviceContext>();
+ MatMul(context, is_fold_init_dims_a
+ ? FoldInitDims(a)
+ : FoldHeadAndLastDims<DeviceContext, T>(ctx, a),
+ trans_a, is_fold_init_dims_b
+ ? FoldInitDims(b)
+ : FoldHeadAndLastDims<DeviceContext, T>(ctx, b),
+ trans_b, out);
+ }
+ }
+
+ void Compute(const framework::ExecutionContext& context) const override {
+ auto x = *context.Input<framework::Tensor>("X");
+ auto y = *context.Input<framework::Tensor>("Y");
+ auto dout =
+ *context.Input<framework::Tensor>(framework::GradVarName("Out"));
+ auto* dx = context.Output<framework::Tensor>(framework::GradVarName("X"));
+ auto* dy = context.Output<framework::Tensor>(framework::GradVarName("Y"));
+ bool transpose_x = context.Attr<bool>("transpose_X");
+ bool transpose_y = context.Attr<bool>("transpose_Y");
+
+ ReshapeXYOutIntoMatrixSequence(&x, &y, &dout, transpose_x, transpose_y);
+ framework::DDim dx_dims;
+ if (dx) {
+ dx_dims = dx->dims();
+ if (dx_dims != x.dims()) {
+ dx->Resize(x.dims());
+ }
+ }
+
+ framework::DDim dy_dims;
+ if (dy) {
+ dy_dims = dy->dims();
+ if (dy_dims != y.dims()) {
+ dy->Resize(y.dims());
+ }
+ }
+
+ if (transpose_x && transpose_y) {
+ CalcInputGrad(context, y, true, true, dout, true, false, dx);
+ CalcInputGrad(context, dout, true, true, x, true, false, dy);
+ } else if (transpose_x) {
+ CalcInputGrad(context, y, false, false, dout, true, false, dx);
+ CalcInputGrad(context, x, false, false, dout, false, true, dy);
+ } else if (transpose_y) {
+ CalcInputGrad(context, dout, false, false, y, false, true, dx);
+ CalcInputGrad(context, dout, true, true, x, false, true, dy);
+ } else {
+ CalcInputGrad(context, dout, false, false, y, true, false, dx);
+ CalcInputGrad(context, x, true, true, dout, false, true, dy);
+ }
+
+ if (dx) {
+ if (dx_dims != x.dims()) {
+ dx->Resize(dx_dims);
+ }
+ }
+ if (dy) {
+ if (dy_dims != y.dims()) {
+ dy->Resize(dy_dims);
+ }
+ }
+ }
+};
class MatMulOp : public framework::OperatorWithKernel {
public:
@@ -37,9 +280,11 @@ class MatMulOp : public framework::OperatorWithKernel {
auto dim_x = context->GetInputDim("X");
auto dim_y = context->GetInputDim("Y");
- auto mat_dim_x = math::GetMatDim(GetXDim(dim_x), 0,
+ auto mat_dim_x =
+ math::CreateMatrixDescriptor(RowMatrixFromVector(dim_x), 0,
context->Attrs().Get<bool>("transpose_X"));
- auto mat_dim_y = math::GetMatDim(GetYDim(dim_y), 0,
+ auto mat_dim_y =
+ math::CreateMatrixDescriptor(ColumnMatrixFromVector(dim_y), 0,
context->Attrs().Get<bool>("transpose_Y"));
PADDLE_ENFORCE_EQ(mat_dim_x.width_, mat_dim_y.height_);
@@ -151,15 +396,40 @@ class MatMulOpGrad : public framework::OperatorWithKernel {
}
};
+class MatMulOpGradMaker : public framework::SingleGradOpDescMaker {
+ public:
+ using framework::SingleGradOpDescMaker::SingleGradOpDescMaker;
+
+ protected:
+ std::unique_ptr<framework::OpDesc> Apply() const override {
+ auto* retv = new framework::OpDesc();
+ retv->SetType("matmul_grad");
+ retv->SetInput("X", Input("X"));
+ retv->SetInput("Y", Input("Y"));
+ retv->SetInput(framework::GradVarName("Out"), OutputGrad("Out"));
+ retv->SetOutput(framework::GradVarName("X"), InputGrad("X"));
+ retv->SetOutput(framework::GradVarName("Y"), InputGrad("Y"));
+ retv->SetAttrMap(Attrs());
+ return std::unique_ptr<framework::OpDesc>(retv);
+ }
+};
} // namespace operators
} // namespace paddle
namespace ops = paddle::operators;
REGISTER_OPERATOR(matmul, ops::MatMulOp, ops::MatMulOpMaker,
- paddle::framework::DefaultGradOpDescMaker<true>);
+ ops::MatMulOpGradMaker);
REGISTER_OPERATOR(matmul_grad, ops::MatMulOpGrad);
REGISTER_OP_CPU_KERNEL(
matmul, ops::MatMulKernel<paddle::platform::CPUDeviceContext, float>);
REGISTER_OP_CPU_KERNEL(
matmul_grad,
ops::MatMulGradKernel<paddle::platform::CPUDeviceContext, float>);
+
+#ifdef PADDLE_WITH_CUDA
+REGISTER_OP_CUDA_KERNEL(
+ matmul, ops::MatMulKernel<paddle::platform::CUDADeviceContext, float>);
+REGISTER_OP_CUDA_KERNEL(
+ matmul_grad,
+ ops::MatMulGradKernel<paddle::platform::CUDADeviceContext, float>);
+#endif
diff --git a/paddle/fluid/operators/matmul_op.cu.cc b/paddle/fluid/operators/matmul_op.cu.cc
deleted file mode 100644
index e021bbe645..0000000000
--- a/paddle/fluid/operators/matmul_op.cu.cc
+++ /dev/null
@@ -1,22 +0,0 @@
-/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved.
-
-Licensed under the Apache License, Version 2.0 (the "License");
-you may not use this file except in compliance with the License.
-You may obtain a copy of the License at
-
- http://www.apache.org/licenses/LICENSE-2.0
-
-Unless required by applicable law or agreed to in writing, software
-distributed under the License is distributed on an "AS IS" BASIS,
-WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-See the License for the specific language governing permissions and
-limitations under the License. */
-
-#include "paddle/fluid/operators/matmul_op.h"
-
-namespace ops = paddle::operators;
-REGISTER_OP_CUDA_KERNEL(
- matmul, ops::MatMulKernel<paddle::platform::CUDADeviceContext, float>);
-REGISTER_OP_CUDA_KERNEL(
- matmul_grad,
- ops::MatMulGradKernel<paddle::platform::CUDADeviceContext, float>);
diff --git a/paddle/fluid/operators/matmul_op.h b/paddle/fluid/operators/matmul_op.h
deleted file mode 100644
index 9bf39026ff..0000000000
--- a/paddle/fluid/operators/matmul_op.h
+++ /dev/null
@@ -1,242 +0,0 @@
-/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved.
-
-Licensed under the Apache License, Version 2.0 (the "License");
-you may not use this file except in compliance with the License.
-You may obtain a copy of the License at
-
- http://www.apache.org/licenses/LICENSE-2.0
-
-Unless required by applicable law or agreed to in writing, software
-distributed under the License is distributed on an "AS IS" BASIS,
-WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-See the License for the specific language governing permissions and
-limitations under the License. */
-
-#pragma once
-#include <algorithm>
-#include <functional>
-#include <utility>
-#include <vector>
-#include "paddle/fluid/framework/op_registry.h"
-#include "paddle/fluid/operators/detail/safe_ref.h"
-#include "paddle/fluid/operators/math/blas.h"
-#include "paddle/fluid/operators/math/math_function.h"
-
-namespace paddle {
-namespace operators {
-inline framework::DDim GetXDim(const framework::DDim& x_dim) {
- if (x_dim.size() > 1) {
- return x_dim;
- }
- return framework::make_ddim({1, x_dim[0]});
-}
-
-inline framework::DDim GetYDim(const framework::DDim& y_dim) {
- if (y_dim.size() > 1) {
- return y_dim;
- }
- return framework::make_ddim({y_dim[0], 1});
-}
-
-template <typename DeviceContext, typename T>
-class MatMulKernel : public framework::OpKernel<T> {
- public:
- void Compute(const framework::ExecutionContext& context) const override {
- auto& x =
- detail::Ref(context.Input<framework::Tensor>("X"), "Cannot find X");
- auto& y =
- detail::Ref(context.Input<framework::Tensor>("Y"), "Cannot find Y");
- auto* out = context.Output<framework::Tensor>("Out");
- out->mutable_data<T>(context.GetPlace());
-
- auto blas = math::GetBlas<DeviceContext, T>(context);
- auto mat_dim_a = math::GetMatDim(GetXDim(x.dims()), 0,
- context.Attr<bool>("transpose_X"));
- auto mat_dim_b = math::GetMatDim(GetYDim(y.dims()), 0,
- context.Attr<bool>("transpose_Y"));
- blas.MatMul(x, mat_dim_a, y, mat_dim_b, T(1), out, T(0));
- }
-};
-
-// Reshape a rank-3 tensor from P x M x N to (P * M) x N.
-// Identity op if the tensor is not of rank 3.
-inline framework::Tensor CombineBatchAndM(const framework::Tensor& input) {
- auto output = input;
- auto in_dims = input.dims();
- if (in_dims.size() == 3) {
- output.Resize({in_dims[0] * in_dims[1], in_dims[2]});
- }
- return output;
-}
-
-// Reshape a rank-3 tensor from P x M x N to M x (P * N).
-// (Warning: This requires transposing data and writes into new memory.)
-// Identity op if the tensor is not of rank 3.
-template <typename DeviceContext, typename T>
-inline framework::Tensor CombineBatchAndN(const DeviceContext& context,
- const framework::Tensor& input) {
- auto in_dims = input.dims();
- if (in_dims.size() != 3) {
- return input;
- }
- framework::Tensor output;
- output.Resize({in_dims[1], in_dims[0], in_dims[2]});
- output.mutable_data<T>(context.GetPlace());
- std::vector<int> axis = {1, 0, 2};
- math::Transpose<DeviceContext, T, 3> trans;
- trans(context, input, &output, axis);
- output.Resize({in_dims[1], in_dims[0] * in_dims[2]});
-
- return output;
-}
-
-inline void NormalizeTensorShape(framework::Tensor* x,
- const math::MatDescriptor& mat_dim_x) {
- int64_t h, w;
- h = mat_dim_x.height_;
- w = mat_dim_x.width_;
- if (mat_dim_x.trans_) {
- std::swap(w, h);
- }
- if (mat_dim_x.batch_size_) {
- x->Resize({mat_dim_x.batch_size_, h, w});
- } else {
- x->Resize({h, w});
- }
-}
-
-inline void NormalizeXYOutTensorShape(framework::Tensor* x,
- framework::Tensor* y,
- framework::Tensor* out, bool trans_a,
- bool trans_b) {
- auto x_dim = GetXDim(x->dims());
- auto y_dim = GetYDim(y->dims());
- auto mat_dim_x = math::GetMatDim(x_dim, 0, trans_a);
- auto mat_dim_y = math::GetMatDim(y_dim, 0, trans_b);
- if (mat_dim_x.batch_size_ == 0 && mat_dim_y.batch_size_ == 0) {
- out->Resize({mat_dim_x.height_, mat_dim_y.width_});
- } else {
- out->Resize({std::max(mat_dim_x.batch_size_, mat_dim_y.batch_size_),
- mat_dim_x.height_, mat_dim_y.width_});
- }
-
- NormalizeTensorShape(x, mat_dim_x);
- NormalizeTensorShape(y, mat_dim_y);
-}
-
-// Using dimensional constraints on matrix multiplication, it is
-// straight-forward to check the following table for when X and Y
-// are both matrices.
-//
-// transpose_X | False | True | False | True
-// transpose_Y | False | False | True | True
-// -----------+----------+----------+----------+-----------
-// dX = | dOut Y^T | Y dOut^T | dOut Y | Y^T dOut^T
-// dY = | X^T dOut | X dOut | dOut^T X | dOut^T X^T
-//
-// When X is a vector of size K, we treat it instead as a matrix of shape
-// (1, K). Similarly, when Y is a vector of size K, we treat it instead as
-// a matrix of shape (K, 1).
-//
-// When X and Y are both 3-dimensional tensors, then the first dimension
-// the batch dimension can be ignored and the exact same formulas apply
-// as for two matrices.
-//
-// Finally, when, e.g., X is a 3-dimensional tensor but Y is a matrix, we end
-// up with formulas like
-//
-// dY_{ij} = \sum_{p, m} X_{pmi} dOut_{pmj}
-//
-// To handle this sort of scenario, we reshape X : P x M x K, dOut: P x M x N
-// to X: (P * M) x K, dOut: (P * M) x N.
-template <typename DeviceContext, typename T>
-class MatMulGradKernel : public framework::OpKernel<T> {
- public:
- void MatMul(const framework::ExecutionContext& context,
- const framework::Tensor& a, bool trans_a,
- const framework::Tensor& b, bool trans_b,
- framework::Tensor* out) const {
- out->mutable_data<T>(context.GetPlace());
- auto blas = math::GetBlas<DeviceContext, T>(context);
- auto mat_dim_a = math::GetMatDim(a.dims(), 0, trans_a);
- auto mat_dim_b = math::GetMatDim(b.dims(), 0, trans_b);
- blas.MatMul(a, mat_dim_a, b, mat_dim_b, T(1), out, T(0));
- }
-
- void CalcInputGrad(const framework::ExecutionContext& context,
- const framework::Tensor& a, bool trans_a,
- bool is_combine_m_a, const framework::Tensor& b,
- bool trans_b, bool is_combine_m_b,
- framework::Tensor* out) const {
- if (out == nullptr) return;
- bool need_combine = (a.dims().size() == 3 || b.dims().size() == 3) &&
- out->dims().size() == 2;
- if (!need_combine) {
- MatMul(context, a, trans_a, b, trans_b, out);
- } else {
- auto& ctx = context.template device_context<DeviceContext>();
- MatMul(
- context, is_combine_m_a ? CombineBatchAndM(a)
- : CombineBatchAndN<DeviceContext, T>(ctx, a),
- trans_a, is_combine_m_b ? CombineBatchAndM(b)
- : CombineBatchAndN<DeviceContext, T>(ctx, b),
- trans_b, out);
- }
- }
-
- void Compute(const framework::ExecutionContext& context) const override {
- auto x = *context.Input<framework::Tensor>("X");
- auto y = *context.Input<framework::Tensor>("Y");
- auto dout =
- *context.Input<framework::Tensor>(framework::GradVarName("Out"));
- auto* dx = context.Output<framework::Tensor>(framework::GradVarName("X"));
- auto* dy = context.Output<framework::Tensor>(framework::GradVarName("Y"));
- bool transpose_x = context.Attr<bool>("transpose_X");
- bool transpose_y = context.Attr<bool>("transpose_Y");
-
- NormalizeXYOutTensorShape(&x, &y, &dout, transpose_x, transpose_y);
- framework::DDim dx_dims;
- if (dx) {
- dx_dims = dx->dims();
- if (dx_dims != x.dims()) {
- dx->Resize(x.dims());
- }
- }
-
- framework::DDim dy_dims;
- if (dy) {
- dy_dims = dy->dims();
- if (dy_dims != y.dims()) {
- dy->Resize(y.dims());
- }
- }
-
- if (transpose_x && transpose_y) {
- CalcInputGrad(context, y, true, true, dout, true, false, dx);
- CalcInputGrad(context, dout, true, true, x, true, false, dy);
- } else if (transpose_x && !transpose_y) {
- CalcInputGrad(context, y, false, false, dout, true, false, dx);
- CalcInputGrad(context, x, false, false, dout, false, true, dy);
- } else if (!transpose_x && transpose_y) {
- CalcInputGrad(context, dout, false, false, y, false, true, dx);
- CalcInputGrad(context, dout, true, true, x, false, true, dy);
- } else {
- CalcInputGrad(context, dout, false, false, y, true, false, dx);
- CalcInputGrad(context, x, true, true, dout, false, true, dy);
- }
-
- if (dx) {
- if (dx_dims != x.dims()) {
- dx->Resize(dx_dims);
- }
- }
- if (dy) {
- if (dy_dims != y.dims()) {
- dy->Resize(dy_dims);
- }
- }
- }
-};
-
-} // namespace operators
-} // namespace paddle
From e97645c959ed5b0b5b3203df0173661c77e4e364 Mon Sep 17 00:00:00 2001
From: Yao Cheng <chengyao@pku.edu.cn>
Date: Tue, 8 May 2018 14:10:08 +0800
Subject: [PATCH 019/195] rm block_desc.h whitespace
---
paddle/fluid/framework/block_desc.h | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/paddle/fluid/framework/block_desc.h b/paddle/fluid/framework/block_desc.h
index 5325583b19..e9d98fc86f 100644
--- a/paddle/fluid/framework/block_desc.h
+++ b/paddle/fluid/framework/block_desc.h
@@ -88,7 +88,7 @@ class BlockDesc {
OpDesc *PrependOp();
void PrependAllocatedOp(std::unique_ptr<OpDesc> &&op_desc);
-
+
void RemoveOp(size_t s, size_t e);
std::vector<OpDesc *> AllOps() const;
From 89dcb0bd151313c758e539e5c90aa9b0cb53d27a Mon Sep 17 00:00:00 2001
From: Luo Tao <luotao02@baidu.com>
Date: Tue, 8 May 2018 13:32:54 +0800
Subject: [PATCH 020/195] refine EngineIOConverter, and use io_convert in
test_trt_activation_op
---
.../inference/tensorrt/convert/CMakeLists.txt | 2 +-
.../tensorrt/convert/io_converter.cc | 42 +++++++++----
.../inference/tensorrt/convert/io_converter.h | 53 ++++++++++------
.../tensorrt/convert/test_activation_op.cc | 39 +++++++-----
.../tensorrt/convert/test_io_converter.cc | 63 +++++++++++++------
paddle/fluid/inference/tensorrt/engine.cc | 1 -
6 files changed, 131 insertions(+), 69 deletions(-)
diff --git a/paddle/fluid/inference/tensorrt/convert/CMakeLists.txt b/paddle/fluid/inference/tensorrt/convert/CMakeLists.txt
index 3c5909c0be..bf494d921a 100644
--- a/paddle/fluid/inference/tensorrt/convert/CMakeLists.txt
+++ b/paddle/fluid/inference/tensorrt/convert/CMakeLists.txt
@@ -1,4 +1,4 @@
nv_test(test_op_converter SRCS test_op_converter.cc mul_op.cc conv2d_op.cc DEPS ${FLUID_CORE_MODULES})
-nv_test(test_trt_activation_op SRCS test_activation_op.cc ${ENGINE_FILE} activation_op.cc
+nv_test(test_trt_activation_op SRCS test_activation_op.cc io_converter.cc ${ENGINE_FILE} activation_op.cc
DEPS ${FLUID_CORE_MODULES} activation_op)
nv_test(test_io_converter SRCS test_io_converter.cc io_converter.cc DEPS dynload_cuda dynamic_loader lod_tensor)
diff --git a/paddle/fluid/inference/tensorrt/convert/io_converter.cc b/paddle/fluid/inference/tensorrt/convert/io_converter.cc
index 32e8631fde..13bc2b3759 100644
--- a/paddle/fluid/inference/tensorrt/convert/io_converter.cc
+++ b/paddle/fluid/inference/tensorrt/convert/io_converter.cc
@@ -23,26 +23,42 @@ namespace tensorrt {
using platform::is_gpu_place;
using platform::is_cpu_place;
-class DefaultInputConverter : public EngineInputConverter {
+class DefaultIOConverter : public EngineIOConverter {
public:
- DefaultInputConverter() {}
+ DefaultIOConverter() {}
// NOTE out is GPU memory.
virtual void operator()(const LoDTensor& in, void* out,
size_t max_size) override {
PADDLE_ENFORCE(out != nullptr);
- PADDLE_ENFORCE_LE(in.memory_size(), max_size);
+ PADDLE_ENFORCE(stream_ != nullptr);
const auto& place = in.place();
+ size_t size = in.memory_size();
+ PADDLE_ENFORCE_LE(size, max_size);
if (is_cpu_place(place)) {
- PADDLE_ENFORCE(stream_ != nullptr);
- PADDLE_ENFORCE_EQ(0,
- cudaMemcpyAsync(out, in.data<float>(), in.memory_size(),
- cudaMemcpyHostToDevice, *stream_));
-
+ PADDLE_ENFORCE_EQ(0, cudaMemcpyAsync(out, in.data<float>(), size,
+ cudaMemcpyHostToDevice, *stream_));
} else if (is_gpu_place(place)) {
- PADDLE_ENFORCE_EQ(0,
- cudaMemcpyAsync(out, in.data<float>(), in.memory_size(),
- cudaMemcpyHostToHost, *stream_));
-
+ PADDLE_ENFORCE_EQ(0, cudaMemcpyAsync(out, in.data<float>(), size,
+ cudaMemcpyHostToHost, *stream_));
+ } else {
+ PADDLE_THROW("Unknown device for converter");
+ }
+ cudaStreamSynchronize(*stream_);
+ }
+ // NOTE in is GPU memory.
+ virtual void operator()(const void* in, LoDTensor* out,
+ size_t max_size) override {
+ PADDLE_ENFORCE(in != nullptr);
+ PADDLE_ENFORCE(stream_ != nullptr);
+ const auto& place = out->place();
+ size_t size = out->memory_size();
+ PADDLE_ENFORCE_LE(size, max_size);
+ if (is_cpu_place(place)) {
+ PADDLE_ENFORCE_EQ(0, cudaMemcpyAsync(out->data<float>(), in, size,
+ cudaMemcpyDeviceToHost, *stream_));
+ } else if (is_gpu_place(place)) {
+ PADDLE_ENFORCE_EQ(0, cudaMemcpyAsync(out->data<float>(), in, size,
+ cudaMemcpyHostToHost, *stream_));
} else {
PADDLE_THROW("Unknown device for converter");
}
@@ -50,7 +66,7 @@ class DefaultInputConverter : public EngineInputConverter {
}
};
-REGISTER_TENSORRT_INPUT_CONVERTER(default, DefaultInputConverter);
+REGISTER_TENSORRT_IO_CONVERTER(default, DefaultIOConverter);
} // namespace tensorrt
} // namespace inference
diff --git a/paddle/fluid/inference/tensorrt/convert/io_converter.h b/paddle/fluid/inference/tensorrt/convert/io_converter.h
index 8972dae92b..71c48e085d 100644
--- a/paddle/fluid/inference/tensorrt/convert/io_converter.h
+++ b/paddle/fluid/inference/tensorrt/convert/io_converter.h
@@ -14,6 +14,7 @@ limitations under the License. */
#pragma once
+#include <string>
#include <unordered_map>
#include "paddle/fluid/framework/lod_tensor.h"
#include "paddle/fluid/inference/utils/singleton.h"
@@ -25,43 +26,57 @@ namespace tensorrt {
using framework::LoDTensor;
/*
- * Convert Input from Fluid to an Engine.
- * TensorRT's ITensor follows row major, NCHW. Fluid is also row major, so in
- * most cases just need to copy the data.
+ * Convert Input from Fluid to TensorRT Engine.
+ * Convert Output from TensorRT Engine to Fluid.
+ *
+ * Note that TensorRT's ITensor follows row major, NCHW. Fluid is also row
+ * major,
+ * so in the default case just need to copy the data.
*/
-class EngineInputConverter {
+class EngineIOConverter {
public:
- EngineInputConverter() {}
+ EngineIOConverter() {}
virtual void operator()(const LoDTensor& in, void* out, size_t max_size) {}
+ virtual void operator()(const void* in, LoDTensor* out, size_t max_size) {}
void SetStream(cudaStream_t* stream) { stream_ = stream; }
- static void Run(const std::string& in_op_type, const LoDTensor& in, void* out,
- size_t max_size, cudaStream_t* stream) {
+ static void ConvertInput(const std::string& op_type, const LoDTensor& in,
+ void* out, size_t max_size, cudaStream_t* stream) {
PADDLE_ENFORCE(stream != nullptr);
- auto* converter = Registry<EngineInputConverter>::Lookup(
- in_op_type, "default" /* default_type */);
+ auto* converter = Registry<EngineIOConverter>::Lookup(
+ op_type, "default" /* default_type */);
PADDLE_ENFORCE_NOT_NULL(converter);
converter->SetStream(stream);
(*converter)(in, out, max_size);
}
- virtual ~EngineInputConverter() {}
+ static void ConvertOutput(const std::string& op_type, const void* in,
+ LoDTensor* out, size_t max_size,
+ cudaStream_t* stream) {
+ PADDLE_ENFORCE(stream != nullptr);
+ auto* converter = Registry<EngineIOConverter>::Lookup(
+ op_type, "default" /* default_type */);
+ PADDLE_ENFORCE_NOT_NULL(converter);
+ converter->SetStream(stream);
+ (*converter)(in, out, max_size);
+ }
+
+ virtual ~EngineIOConverter() {}
protected:
cudaStream_t* stream_{nullptr};
};
+#define REGISTER_TENSORRT_IO_CONVERTER(op_type__, Converter__) \
+ struct trt_io_##op_type__##_converter { \
+ trt_io_##op_type__##_converter() { \
+ Registry<EngineIOConverter>::Register<Converter__>(#op_type__); \
+ } \
+ }; \
+ trt_io_##op_type__##_converter trt_io_##op_type__##_converter__;
+
} // namespace tensorrt
} // namespace inference
} // namespace paddle
-
-#define REGISTER_TENSORRT_INPUT_CONVERTER(in_op_type__, Converter__) \
- struct trt_input_##in_op_type__##_converter { \
- trt_input_##in_op_type__##_converter() { \
- ::paddle::inference::Registry<EngineInputConverter>::Register< \
- Converter__>(#in_op_type__); \
- } \
- }; \
- trt_input_##in_op_type__##_converter trt_input_##in_op_type__##_converter__;
diff --git a/paddle/fluid/inference/tensorrt/convert/test_activation_op.cc b/paddle/fluid/inference/tensorrt/convert/test_activation_op.cc
index 23e3435c21..c43f720212 100644
--- a/paddle/fluid/inference/tensorrt/convert/test_activation_op.cc
+++ b/paddle/fluid/inference/tensorrt/convert/test_activation_op.cc
@@ -16,6 +16,7 @@ limitations under the License. */
#include "paddle/fluid/framework/lod_tensor.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/framework/program_desc.h"
+#include "paddle/fluid/inference/tensorrt/convert/io_converter.h"
#include "paddle/fluid/inference/tensorrt/convert/op_converter.h"
#include "paddle/fluid/platform/device_context.h"
#include "paddle/fluid/platform/place.h"
@@ -26,7 +27,7 @@ namespace paddle {
namespace inference {
namespace tensorrt {
-void Compare(float input, float expect) {
+void Compare(const std::string op_type, float input, float expect) {
framework::Scope scope;
platform::CUDAPlace place;
platform::CUDADeviceContext ctx(place);
@@ -35,6 +36,7 @@ void Compare(float input, float expect) {
auto x_var = scope.Var("X");
auto x_tensor = x_var->GetMutable<framework::LoDTensor>();
x_tensor->Resize({1, 1});
+ x_tensor->mutable_data<float>(place);
std::vector<float> init;
init.push_back(input);
framework::TensorFromVector(init, ctx, x_tensor);
@@ -45,14 +47,15 @@ void Compare(float input, float expect) {
out_tensor->mutable_data<float>(place);
framework::OpDesc op_desc;
- op_desc.SetType("relu");
+ op_desc.SetType(op_type);
op_desc.SetInput("X", {"X"});
op_desc.SetOutput("Out", {"Out"});
- auto relu_op = framework::OpRegistry::CreateOp(op_desc);
+ auto op = framework::OpRegistry::CreateOp(op_desc);
// run fluid op
- relu_op->Run(scope, place);
+ op->Run(scope, place);
+ // get fluid output
std::vector<float> out1;
framework::TensorToVector(*out_tensor, ctx, &out1);
@@ -63,21 +66,27 @@ void Compare(float input, float expect) {
engine->InitNetwork();
engine->DeclareInput("X", nvinfer1::DataType::kFLOAT,
nvinfer1::DimsCHW{1, 1, 1});
-
+ // convert op
OpConverter op_converter;
op_converter.ConvertOp(op_desc, engine);
-
engine->DeclareOutput("Out");
engine->FreezeNetwork();
- engine->SetInputFromCPU("X", &input, 1 * sizeof(float));
- // run tensorrt op
+ // convert LoDTensor to ITensor
+ size_t size = x_tensor->memory_size();
+ EngineIOConverter::ConvertInput(op_type, *x_tensor, engine->buffer("X"), size,
+ &stream);
+ // run tensorrt Outp
engine->Execute(1);
-
- float out2;
- engine->GetOutputInCPU("Out", &out2, 1 * sizeof(float));
-
- ASSERT_EQ(out1[0], out2);
+ // convert ITensor to LoDTensor
+ EngineIOConverter::ConvertOutput(op_type, engine->buffer("Out"), out_tensor,
+ size, &stream);
+ // get tensorrt output
+ std::vector<float> out2;
+ framework::TensorToVector(*out_tensor, ctx, &out2);
+
+ // compare
+ ASSERT_EQ(out1[0], out2[0]);
ASSERT_EQ(out1[0], expect);
delete engine;
@@ -85,8 +94,8 @@ void Compare(float input, float expect) {
}
TEST(OpConverter, ConvertRelu) {
- Compare(1, 1); // relu(1) = 1
- Compare(-5, 0); // relu(-5) = 0
+ Compare("relu", 1, 1); // relu(1) = 1
+ Compare("relu", -5, 0); // relu(-5) = 0
}
} // namespace tensorrt
diff --git a/paddle/fluid/inference/tensorrt/convert/test_io_converter.cc b/paddle/fluid/inference/tensorrt/convert/test_io_converter.cc
index afcc516e6b..8f91309a0a 100644
--- a/paddle/fluid/inference/tensorrt/convert/test_io_converter.cc
+++ b/paddle/fluid/inference/tensorrt/convert/test_io_converter.cc
@@ -12,40 +12,63 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
+#include <gtest/gtest.h>
#include "paddle/fluid/framework/lod_tensor.h"
#include "paddle/fluid/inference/tensorrt/convert/io_converter.h"
-#include <gtest/gtest.h>
-
namespace paddle {
namespace inference {
namespace tensorrt {
-class EngineInputConverterTester : public ::testing::Test {
- public:
- void SetUp() override { tensor.Resize({10, 10}); }
+void IOConverterTester(const platform::DeviceContext& ctx) {
+ cudaStream_t stream;
+ ASSERT_EQ(0, cudaStreamCreate(&stream));
- framework::LoDTensor tensor;
-};
+ // init fluid in_tensor
+ framework::LoDTensor in_tensor;
+ in_tensor.Resize({10, 10});
+ auto place = ctx.GetPlace();
+ in_tensor.mutable_data<float>(place);
+ std::vector<float> init;
+ for (int64_t i = 0; i < 10 * 10; ++i) {
+ init.push_back(i);
+ }
+ framework::TensorFromVector(init, ctx, &in_tensor);
-TEST_F(EngineInputConverterTester, DefaultCPU) {
+ // init tensorrt buffer
void* buffer;
- tensor.mutable_data<float>(platform::CPUPlace());
- ASSERT_EQ(cudaMalloc(&buffer, tensor.memory_size()), 0);
+ size_t size = in_tensor.memory_size();
+ ASSERT_EQ(cudaMalloc(&buffer, size), 0);
- cudaStream_t stream;
- EngineInputConverter::Run("test", tensor, buffer, tensor.memory_size(),
- &stream);
+ // convert fluid in_tensor to tensorrt buffer
+ EngineIOConverter::ConvertInput("test", in_tensor, buffer, size, &stream);
+
+ // convert tensorrt buffer to fluid out_tensor
+ framework::LoDTensor out_tensor;
+ out_tensor.Resize({10, 10});
+ out_tensor.mutable_data<float>(place);
+ EngineIOConverter::ConvertOutput("test", buffer, &out_tensor, size, &stream);
+
+ // compare in_tensor and out_tensor
+ std::vector<float> result;
+ framework::TensorToVector(out_tensor, ctx, &result);
+ EXPECT_EQ(init.size(), result.size());
+ for (size_t i = 0; i < init.size(); i++) {
+ EXPECT_EQ(init[i], result[i]);
+ }
+ cudaStreamDestroy(stream);
}
-TEST_F(EngineInputConverterTester, DefaultGPU) {
- void* buffer;
- tensor.mutable_data<float>(platform::CUDAPlace());
- ASSERT_EQ(cudaMalloc(&buffer, tensor.memory_size()), 0);
+TEST(EngineIOConverterTester, DefaultCPU) {
+ platform::CPUPlace place;
+ platform::CPUDeviceContext ctx(place);
+ IOConverterTester(ctx);
+}
- cudaStream_t stream;
- EngineInputConverter::Run("test", tensor, buffer, tensor.memory_size(),
- &stream);
+TEST(EngineIOConverterTester, DefaultGPU) {
+ platform::CUDAPlace place;
+ platform::CUDADeviceContext ctx(place);
+ IOConverterTester(ctx);
}
} // namespace tensorrt
diff --git a/paddle/fluid/inference/tensorrt/engine.cc b/paddle/fluid/inference/tensorrt/engine.cc
index df123a5907..0a69ab9bdd 100644
--- a/paddle/fluid/inference/tensorrt/engine.cc
+++ b/paddle/fluid/inference/tensorrt/engine.cc
@@ -138,7 +138,6 @@ void*& TensorRTEngine::buffer(const std::string& name) {
void TensorRTEngine::SetInputFromCPU(const std::string& name, void* data,
size_t size) {
void* buf = buffer(name);
- cudaMemcpyAsync(buf, data, size, cudaMemcpyHostToDevice, *stream_);
PADDLE_ENFORCE_EQ(
0, cudaMemcpyAsync(buf, data, size, cudaMemcpyHostToDevice, *stream_));
}
From 0e78cb69fb13cce3250d5ba12c7b217418ae73cb Mon Sep 17 00:00:00 2001
From: Yu Yang <yuyang18@baidu.com>
Date: Tue, 8 May 2018 18:15:49 +0800
Subject: [PATCH 021/195] Clean OpProtoAndCheckerMaker
Do not use ctor
* Reduce line of codes.
* We can use virtual function for Maker now.
* The implementation does not care what maker holds, it is easier to
refactor later.
---
.../framework/data_device_transform_test.cu | 3 +-
paddle/fluid/framework/details/op_registry.h | 5 +-
paddle/fluid/framework/op_proto_maker.h | 20 ++--
paddle/fluid/framework/op_proto_maker_test.cc | 18 +--
paddle/fluid/framework/op_registry_test.cc | 13 +--
paddle/fluid/framework/operator_test.cc | 10 +-
.../framework/var_type_inference_test.cc | 3 +-
paddle/fluid/operators/CMakeLists.txt | 2 +
paddle/fluid/operators/accuracy_op.cc | 3 +-
paddle/fluid/operators/activation_op.cc | 61 ++++------
paddle/fluid/operators/adadelta_op.cc | 3 +-
paddle/fluid/operators/adagrad_op.cc | 3 +-
paddle/fluid/operators/adam_op.cc | 3 +-
paddle/fluid/operators/adamax_op.cc | 3 +-
.../fluid/operators/array_to_lod_tensor_op.cc | 3 +-
paddle/fluid/operators/assign_op.cc | 3 +-
paddle/fluid/operators/assign_value_op.cc | 3 +-
paddle/fluid/operators/auc_op.cc | 3 +-
.../fluid/operators/average_accumulates_op.cc | 3 +-
paddle/fluid/operators/batch_norm_op.cc | 3 +-
paddle/fluid/operators/batch_size_like.h | 3 +-
.../fluid/operators/beam_search_decode_op.cc | 3 +-
paddle/fluid/operators/beam_search_op.cc | 3 +-
paddle/fluid/operators/bilinear_interp_op.cc | 3 +-
.../operators/bilinear_tensor_product_op.cc | 3 +-
paddle/fluid/operators/bipartite_match_op.cc | 3 +-
paddle/fluid/operators/box_coder_op.cc | 3 +-
paddle/fluid/operators/cast_op.cc | 3 +-
paddle/fluid/operators/channel_close_op.cc | 3 +-
paddle/fluid/operators/channel_create_op.cc | 3 +-
paddle/fluid/operators/channel_recv_op.cc | 3 +-
paddle/fluid/operators/channel_send_op.cc | 3 +-
paddle/fluid/operators/chunk_eval_op.cc | 3 +-
paddle/fluid/operators/clip_by_norm_op.cc | 3 +-
paddle/fluid/operators/clip_op.cc | 3 +-
paddle/fluid/operators/compare_op.cc | 3 +-
paddle/fluid/operators/concat_op.cc | 3 +-
.../fluid/operators/conditional_block_op.cc | 3 +-
paddle/fluid/operators/conv_op.cc | 6 +-
paddle/fluid/operators/conv_op.h | 4 +-
paddle/fluid/operators/conv_shift_op.cc | 3 +-
paddle/fluid/operators/conv_transpose_op.cc | 8 +-
paddle/fluid/operators/conv_transpose_op.h | 4 +-
paddle/fluid/operators/cos_sim_op.cc | 3 +-
paddle/fluid/operators/crf_decoding_op.cc | 3 +-
paddle/fluid/operators/crop_op.cc | 3 +-
paddle/fluid/operators/cross_entropy_op.cc | 3 +-
paddle/fluid/operators/ctc_align_op.cc | 3 +-
paddle/fluid/operators/cumsum_op.cc | 3 +-
paddle/fluid/operators/decayed_adagrad_op.cc | 3 +-
paddle/fluid/operators/delete_var_op.cc | 3 +-
paddle/fluid/operators/detection_map_op.cc | 3 +-
paddle/fluid/operators/dropout_op.cc | 3 +-
paddle/fluid/operators/edit_distance_op.cc | 3 +-
paddle/fluid/operators/elementwise_add_op.cc | 20 +---
paddle/fluid/operators/elementwise_div_op.cc | 20 +---
paddle/fluid/operators/elementwise_max_op.cc | 19 +--
paddle/fluid/operators/elementwise_min_op.cc | 19 +--
paddle/fluid/operators/elementwise_mul_op.cc | 21 +---
paddle/fluid/operators/elementwise_op.h | 43 ++++---
paddle/fluid/operators/elementwise_pow_op.cc | 10 +-
paddle/fluid/operators/elementwise_sub_op.cc | 19 +--
paddle/fluid/operators/expand_op.cc | 3 +-
paddle/fluid/operators/fc_op.cc | 3 +-
paddle/fluid/operators/fc_op.h | 2 +-
paddle/fluid/operators/feed_op.cc | 3 +-
paddle/fluid/operators/fetch_op.cc | 3 +-
.../fill_constant_batch_size_like_op.cc | 3 +-
paddle/fluid/operators/fill_constant_op.cc | 3 +-
paddle/fluid/operators/fill_op.cc | 3 +-
paddle/fluid/operators/fill_zeros_like_op.cc | 3 +-
paddle/fluid/operators/ftrl_op.cc | 3 +-
paddle/fluid/operators/gather_op.cc | 3 +-
.../gaussian_random_batch_size_like_op.cc | 3 +-
paddle/fluid/operators/gaussian_random_op.cc | 3 +-
paddle/fluid/operators/get_places_op.cc | 3 +-
paddle/fluid/operators/go_op.cc | 3 +-
paddle/fluid/operators/gru_op.cc | 3 +-
paddle/fluid/operators/gru_unit_op.cc | 3 +-
paddle/fluid/operators/hinge_loss_op.cc | 3 +-
paddle/fluid/operators/huber_loss_op.cc | 3 +-
paddle/fluid/operators/im2sequence_op.cc | 3 +-
paddle/fluid/operators/increment_op.cc | 3 +-
paddle/fluid/operators/iou_similarity_op.cc | 3 +-
paddle/fluid/operators/is_empty_op.cc | 3 +-
paddle/fluid/operators/l1_norm_op.cc | 3 +-
paddle/fluid/operators/label_smooth_op.cc | 3 +-
paddle/fluid/operators/layer_norm_op.cc | 3 +-
paddle/fluid/operators/linear_chain_crf_op.cc | 3 +-
paddle/fluid/operators/listen_and_serv_op.cc | 3 +-
paddle/fluid/operators/load_combine_op.cc | 3 +-
paddle/fluid/operators/load_op.cc | 3 +-
paddle/fluid/operators/lod_array_length_op.cc | 3 +-
paddle/fluid/operators/lod_rank_table_op.cc | 3 +-
paddle/fluid/operators/lod_reset_op.cc | 3 +-
.../fluid/operators/lod_tensor_to_array_op.cc | 3 +-
paddle/fluid/operators/log_loss_op.cc | 3 +-
paddle/fluid/operators/logical_op.cc | 6 +-
.../fluid/operators/lookup_sparse_table_op.cc | 3 +-
paddle/fluid/operators/lookup_table_op.cc | 3 +-
paddle/fluid/operators/lrn_op.cc | 3 +-
paddle/fluid/operators/lstm_op.cc | 3 +-
paddle/fluid/operators/lstm_unit_op.cc | 3 +-
paddle/fluid/operators/lstmp_op.cc | 3 +-
paddle/fluid/operators/margin_rank_loss_op.cc | 3 +-
paddle/fluid/operators/matmul_op.cc | 3 +-
paddle/fluid/operators/max_sequence_len_op.cc | 3 +-
paddle/fluid/operators/maxout_op.cc | 3 +-
paddle/fluid/operators/mean_op.cc | 3 +-
paddle/fluid/operators/merge_lod_tensor_op.cc | 3 +-
.../fluid/operators/mine_hard_examples_op.cc | 3 +-
paddle/fluid/operators/minus_op.cc | 3 +-
.../fluid/operators/modified_huber_loss_op.cc | 3 +-
paddle/fluid/operators/momentum_op.cc | 3 +-
paddle/fluid/operators/mul_op.cc | 3 +-
paddle/fluid/operators/multiclass_nms_op.cc | 3 +-
paddle/fluid/operators/multiplex_op.cc | 3 +-
paddle/fluid/operators/nccl_op.cc | 12 +-
paddle/fluid/operators/nce_op.cc | 3 +-
paddle/fluid/operators/norm_op.cc | 3 +-
paddle/fluid/operators/one_hot_op.cc | 3 +-
paddle/fluid/operators/pad_op.cc | 3 +-
paddle/fluid/operators/parallel_do_op.cc | 3 +-
paddle/fluid/operators/pool_op.cc | 6 +-
paddle/fluid/operators/pool_op.h | 4 +-
paddle/fluid/operators/pool_with_index_op.cc | 6 +-
.../operators/positive_negative_pair_op.cc | 3 +-
paddle/fluid/operators/precision_recall_op.cc | 3 +-
paddle/fluid/operators/prefetch_op.cc | 3 +-
paddle/fluid/operators/prelu_op.cc | 3 +-
paddle/fluid/operators/print_op.cc | 3 +-
paddle/fluid/operators/prior_box_op.cc | 3 +-
paddle/fluid/operators/proximal_adagrad_op.cc | 3 +-
paddle/fluid/operators/proximal_gd_op.cc | 3 +-
paddle/fluid/operators/rank_loss_op.cc | 3 +-
paddle/fluid/operators/read_op.cc | 3 +-
.../reader/create_batch_reader_op.cc | 5 +-
.../reader/create_double_buffer_reader_op.cc | 7 +-
.../reader/create_multi_pass_reader_op.cc | 17 ++-
.../reader/create_random_data_generator_op.cc | 5 +-
.../reader/create_recordio_file_reader_op.cc | 5 +-
.../reader/create_shuffle_reader_op.cc | 5 +-
.../reader/create_threaded_reader_op.cc | 15 ++-
.../fluid/operators/reader/open_files_op.cc | 7 +-
.../operators/reader/reader_op_registry.cc | 12 +-
.../operators/reader/reader_op_registry.h | 10 +-
paddle/fluid/operators/recurrent_op.cc | 3 +-
paddle/fluid/operators/recv_op.cc | 3 +-
paddle/fluid/operators/reduce_op.cc | 109 ++++--------------
.../reorder_lod_tensor_by_rank_op.cc | 4 +-
paddle/fluid/operators/reshape_op.cc | 3 +-
paddle/fluid/operators/rmsprop_op.cc | 3 +-
.../fluid/operators/rnn_memory_helper_op.cc | 6 +-
paddle/fluid/operators/roi_pool_op.cc | 3 +-
paddle/fluid/operators/row_conv_op.cc | 3 +-
paddle/fluid/operators/save_combine_op.cc | 3 +-
paddle/fluid/operators/save_op.cc | 3 +-
paddle/fluid/operators/scale_op.cc | 3 +-
paddle/fluid/operators/scatter_op.cc | 3 +-
paddle/fluid/operators/select_op.cc | 3 +-
paddle/fluid/operators/send_barrier_op.cc | 3 +-
paddle/fluid/operators/send_op.cc | 3 +-
paddle/fluid/operators/send_vars_op.cc | 3 +-
paddle/fluid/operators/sequence_concat_op.cc | 3 +-
paddle/fluid/operators/sequence_conv_op.cc | 3 +-
paddle/fluid/operators/sequence_erase_op.cc | 3 +-
paddle/fluid/operators/sequence_expand_op.cc | 3 +-
paddle/fluid/operators/sequence_pool_op.cc | 3 +-
paddle/fluid/operators/sequence_reshape_op.cc | 3 +-
paddle/fluid/operators/sequence_slice_op.cc | 3 +-
paddle/fluid/operators/sequence_softmax_op.cc | 3 +-
paddle/fluid/operators/sgd_op.cc | 3 +-
.../fluid/operators/shrink_rnn_memory_op.cc | 3 +-
.../sigmoid_cross_entropy_with_logits_op.cc | 4 +-
paddle/fluid/operators/sign_op.cc | 3 +-
paddle/fluid/operators/smooth_l1_loss_op.cc | 3 +-
paddle/fluid/operators/softmax_op.cc | 3 +-
.../softmax_with_cross_entropy_op.cc | 3 +-
paddle/fluid/operators/split_byref_op.cc | 3 +-
paddle/fluid/operators/split_ids_op.cc | 3 +-
paddle/fluid/operators/split_lod_tensor_op.cc | 3 +-
paddle/fluid/operators/split_op.cc | 3 +-
.../fluid/operators/split_selected_rows_op.cc | 3 +-
paddle/fluid/operators/spp_op.cc | 3 +-
.../fluid/operators/squared_l2_distance_op.cc | 3 +-
paddle/fluid/operators/squared_l2_norm_op.cc | 3 +-
paddle/fluid/operators/sum_op.cc | 3 +-
paddle/fluid/operators/target_assign_op.cc | 3 +-
.../operators/tensor_array_read_write_op.cc | 6 +-
paddle/fluid/operators/top_k_op.cc | 3 +-
paddle/fluid/operators/transpose_op.cc | 3 +-
.../uniform_random_batch_size_like_op.cc | 3 +-
paddle/fluid/operators/uniform_random_op.cc | 3 +-
paddle/fluid/operators/unpool_op.cc | 3 +-
paddle/fluid/operators/warpctc_op.cc | 3 +-
paddle/fluid/operators/while_op.cc | 3 +-
196 files changed, 332 insertions(+), 711 deletions(-)
diff --git a/paddle/fluid/framework/data_device_transform_test.cu b/paddle/fluid/framework/data_device_transform_test.cu
index df4caa45eb..a91fe5c99d 100644
--- a/paddle/fluid/framework/data_device_transform_test.cu
+++ b/paddle/fluid/framework/data_device_transform_test.cu
@@ -32,8 +32,7 @@ struct AddFunctor {
class OpKernelTestProtoAndCheckerMaker : public OpProtoAndCheckerMaker {
public:
- OpKernelTestProtoAndCheckerMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() {
AddInput("input", "input1 of test op");
AddOutput("output", "output of test op");
AddAttr<bool>("use_gpu", "force to use gpu kernel").SetDefault(false);
diff --git a/paddle/fluid/framework/details/op_registry.h b/paddle/fluid/framework/details/op_registry.h
index 06603db31e..1c4b059cd0 100644
--- a/paddle/fluid/framework/details/op_registry.h
+++ b/paddle/fluid/framework/details/op_registry.h
@@ -95,7 +95,10 @@ struct OpInfoFiller<T, kOpProtoAndCheckerMaker> {
void operator()(const char* op_type, OpInfo* info) const {
info->proto_ = new proto::OpProto;
info->checker_ = new OpAttrChecker();
- auto maker = T(info->proto_, info->checker_);
+ T maker;
+ maker.SetProto(info->proto_);
+ maker.SetChecker(info->checker_);
+ maker.Make();
maker.Validate();
info->proto_->set_type(op_type);
PADDLE_ENFORCE(
diff --git a/paddle/fluid/framework/op_proto_maker.h b/paddle/fluid/framework/op_proto_maker.h
index 0beb57ce16..cd56776cc6 100644
--- a/paddle/fluid/framework/op_proto_maker.h
+++ b/paddle/fluid/framework/op_proto_maker.h
@@ -23,20 +23,21 @@ namespace framework {
// this class not only make proto but also init attribute checkers.
class OpProtoAndCheckerMaker {
public:
- using OpProto = proto::OpProto;
- using OpAttrChecker = framework::OpAttrChecker;
- OpProtoAndCheckerMaker(OpProto* proto, OpAttrChecker* op_checker)
- : proto_(proto), op_checker_(op_checker) {}
+ virtual void Make() = 0;
virtual ~OpProtoAndCheckerMaker() {
PADDLE_ENFORCE(validated_, "should call Validate after build");
}
+ void SetProto(proto::OpProto* proto) { proto_ = proto; }
+
+ void SetChecker(OpAttrChecker* attr_checker) { op_checker_ = attr_checker; }
+
void Validate();
protected:
struct VariableBuilder {
- OpProto::Var* var_;
+ proto::OpProto::Var* var_;
VariableBuilder& AsDuplicable() {
var_->set_duplicable(true);
@@ -76,16 +77,9 @@ class OpProtoAndCheckerMaker {
private:
void CheckNoDuplicatedInOutAttrs();
- OpProto* proto_;
+ proto::OpProto* proto_;
OpAttrChecker* op_checker_;
bool validated_{false};
};
-
-class NOPMaker : public OpProtoAndCheckerMaker {
- public:
- NOPMaker(OpProto* proto, framework::OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {}
-};
-
} // namespace framework
} // namespace paddle
diff --git a/paddle/fluid/framework/op_proto_maker_test.cc b/paddle/fluid/framework/op_proto_maker_test.cc
index a8d8c6386a..9b5badbc81 100644
--- a/paddle/fluid/framework/op_proto_maker_test.cc
+++ b/paddle/fluid/framework/op_proto_maker_test.cc
@@ -18,9 +18,7 @@ limitations under the License. */
class TestAttrProtoMaker : public paddle::framework::OpProtoAndCheckerMaker {
public:
- TestAttrProtoMaker(paddle::framework::proto::OpProto* proto,
- paddle::framework::OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() {
AddAttr<float>("scale", "scale of test op");
AddAttr<float>("scale", "scale of test op");
}
@@ -29,15 +27,16 @@ class TestAttrProtoMaker : public paddle::framework::OpProtoAndCheckerMaker {
TEST(ProtoMaker, DuplicatedAttr) {
paddle::framework::proto::OpProto op_proto;
paddle::framework::OpAttrChecker op_checker;
- auto proto_maker = TestAttrProtoMaker(&op_proto, &op_checker);
+ TestAttrProtoMaker proto_maker;
+ proto_maker.SetProto(&op_proto);
+ proto_maker.SetChecker(&op_checker);
+ proto_maker.Make();
ASSERT_THROW(proto_maker.Validate(), paddle::platform::EnforceNotMet);
}
class TestInOutProtoMaker : public paddle::framework::OpProtoAndCheckerMaker {
public:
- TestInOutProtoMaker(paddle::framework::proto::OpProto* proto,
- paddle::framework::OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() {
AddInput("input", "input of test op");
AddInput("input", "input of test op");
}
@@ -46,6 +45,9 @@ class TestInOutProtoMaker : public paddle::framework::OpProtoAndCheckerMaker {
TEST(ProtoMaker, DuplicatedInOut) {
paddle::framework::proto::OpProto op_proto;
paddle::framework::OpAttrChecker op_checker;
- auto proto_maker = TestInOutProtoMaker(&op_proto, &op_checker);
+ TestAttrProtoMaker proto_maker;
+ proto_maker.SetProto(&op_proto);
+ proto_maker.SetChecker(&op_checker);
+ proto_maker.Make();
ASSERT_THROW(proto_maker.Validate(), paddle::platform::EnforceNotMet);
}
diff --git a/paddle/fluid/framework/op_registry_test.cc b/paddle/fluid/framework/op_registry_test.cc
index 6dc4cf261b..18b1649cc7 100644
--- a/paddle/fluid/framework/op_registry_test.cc
+++ b/paddle/fluid/framework/op_registry_test.cc
@@ -33,8 +33,7 @@ class CosineOp : public OperatorBase {
class CosineOpProtoAndCheckerMaker : public OpProtoAndCheckerMaker {
public:
- CosineOpProtoAndCheckerMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() {
AddInput("input", "input of cosine op");
AddOutput("output", "output of cosine op");
AddAttr<float>("scale", "scale of cosine op")
@@ -55,8 +54,7 @@ class MyTestOp : public OperatorBase {
class MyTestOpProtoAndCheckerMaker : public OpProtoAndCheckerMaker {
public:
- MyTestOpProtoAndCheckerMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() {
AddInput("input", "input of cosine op").AsDuplicable();
AddOutput("output", "output of cosine op").AsIntermediate();
auto my_checker = [](int i) {
@@ -212,10 +210,7 @@ namespace framework {
class OpKernelTestMaker : public OpProtoAndCheckerMaker {
public:
- OpKernelTestMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
- AddComment("NoGradOp, same input output. no Grad");
- }
+ void Make() { AddComment("NoGradOp, same input output. no Grad"); }
};
class OpWithKernelTest : public OperatorWithKernel {
@@ -275,9 +270,9 @@ TEST(OperatorRegistrar, CUDA) {
static int op_test_value = 0;
-using paddle::platform::DeviceContext;
using paddle::platform::CPUDeviceContext;
using paddle::platform::CUDADeviceContext;
+using paddle::platform::DeviceContext;
namespace paddle {
namespace framework {
diff --git a/paddle/fluid/framework/operator_test.cc b/paddle/fluid/framework/operator_test.cc
index 1bf8c81469..74043b5d79 100644
--- a/paddle/fluid/framework/operator_test.cc
+++ b/paddle/fluid/framework/operator_test.cc
@@ -46,8 +46,7 @@ class OpWithoutKernelTest : public OperatorBase {
class OpWithoutKernelCheckerMaker : public OpProtoAndCheckerMaker {
public:
- OpWithoutKernelCheckerMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() {
AddInput("input", "input of test op");
AddOutput("output", "output of test op");
AddAttr<float>("scale", "scale of cosine op");
@@ -98,8 +97,7 @@ namespace framework {
class OpKernelTestProtoAndCheckerMaker : public OpProtoAndCheckerMaker {
public:
- OpKernelTestProtoAndCheckerMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() {
AddInput("x", "input of test op");
AddOutput("y", "output of test op");
AddAttr<float>("scale", "scale of cosine op")
@@ -137,9 +135,7 @@ class CPUKernelTest : public OpKernel<float> {
class OpKernelTestMultiInputsProtoAndCheckerMaker
: public OpProtoAndCheckerMaker {
public:
- OpKernelTestMultiInputsProtoAndCheckerMaker(OpProto* proto,
- OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() {
AddInput("xs", "inputs of test op").AsDuplicable();
AddInput("k", "input of test op");
AddOutput("ys", "outputs of test op").AsDuplicable();
diff --git a/paddle/fluid/framework/var_type_inference_test.cc b/paddle/fluid/framework/var_type_inference_test.cc
index 9e33003b44..14b81ddfec 100644
--- a/paddle/fluid/framework/var_type_inference_test.cc
+++ b/paddle/fluid/framework/var_type_inference_test.cc
@@ -24,8 +24,7 @@ namespace framework {
class SumOpMaker : public OpProtoAndCheckerMaker {
public:
- SumOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() {
AddInput("X", "").AsDuplicable();
AddOutput("Out", "");
AddComment("");
diff --git a/paddle/fluid/operators/CMakeLists.txt b/paddle/fluid/operators/CMakeLists.txt
index 256aded8ca..fbeacb66ce 100644
--- a/paddle/fluid/operators/CMakeLists.txt
+++ b/paddle/fluid/operators/CMakeLists.txt
@@ -166,6 +166,8 @@ function(op_library TARGET)
# NOTE(*): activation use macro to regist the kernels, set use_op manually.
if(${TARGET} STREQUAL "activation")
file(APPEND ${pybind_file} "USE_OP(relu);\n")
+ elseif(${TARGET} STREQUAL "reduce")
+ file(APPEND ${pybind_file} "USE_OP(reduce_sum);\n")
else()
file(APPEND ${pybind_file} "USE_OP(${TARGET});\n")
endif()
diff --git a/paddle/fluid/operators/accuracy_op.cc b/paddle/fluid/operators/accuracy_op.cc
index ac10d759fe..42fcace179 100644
--- a/paddle/fluid/operators/accuracy_op.cc
+++ b/paddle/fluid/operators/accuracy_op.cc
@@ -63,8 +63,7 @@ class AccuracyOp : public framework::OperatorWithKernel {
class AccuracyOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- AccuracyOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
// TODO(typhoonzero): support both inference value and indices.
AddInput("Out", "The network output of topk (inferences)");
AddInput("Indices", "The the network output of topk (indices)");
diff --git a/paddle/fluid/operators/activation_op.cc b/paddle/fluid/operators/activation_op.cc
index 87ef55c50b..55482abdf0 100644
--- a/paddle/fluid/operators/activation_op.cc
+++ b/paddle/fluid/operators/activation_op.cc
@@ -19,19 +19,18 @@ limitations under the License. */
namespace paddle {
namespace operators {
-#define REGISTER_ACTIVATION_OP_MAKER(OP_NAME, OP_COMMENT) \
- class OP_NAME##OpMaker \
- : public ::paddle::framework::OpProtoAndCheckerMaker { \
- public: \
- OP_NAME##OpMaker(OpProto *proto, OpAttrChecker *op_checker) \
- : ::paddle::framework::OpProtoAndCheckerMaker(proto, op_checker) { \
- AddInput("X", "Input of " #OP_NAME "operator"); \
- AddOutput("Out", "Output of" #OP_NAME "operator"); \
- AddAttr<bool>("use_mkldnn", \
- "(bool, default false) Only used in mkldnn kernel") \
- .SetDefault(false); \
- AddComment(#OP_COMMENT); \
- } \
+#define REGISTER_ACTIVATION_OP_MAKER(OP_NAME, OP_COMMENT) \
+ class OP_NAME##OpMaker \
+ : public ::paddle::framework::OpProtoAndCheckerMaker { \
+ public: \
+ void Make() override { \
+ AddInput("X", "Input of " #OP_NAME "operator"); \
+ AddOutput("Out", "Output of" #OP_NAME "operator"); \
+ AddAttr<bool>("use_mkldnn", \
+ "(bool, default false) Only used in mkldnn kernel") \
+ .SetDefault(false); \
+ AddComment(#OP_COMMENT); \
+ } \
}
#define REGISTER_ACTIVATION_OP_GRAD_MAKER(OP_NAME, KERNEL_TYPE) \
@@ -204,8 +203,7 @@ $$out = \frac{x}{1 + |x|}$$
class LeakyReluOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- LeakyReluOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : framework::OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X", "Input of LeakyRelu operator");
AddOutput("Out", "Output of LeakyRelu operator");
AddAttr<float>("alpha", "The small negative slope").SetDefault(0.02f);
@@ -220,8 +218,7 @@ $out = \max(x, \alpha * x)$
class SoftShrinkOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- SoftShrinkOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : framework::OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X", "Input of Softshrink operator");
AddOutput("Out", "Output of Softshrink operator");
AddAttr<float>("lambda", "non-negative offset").SetDefault(0.5f);
@@ -242,8 +239,7 @@ $$
class HardShrinkOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- HardShrinkOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : framework::OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X", "Input of HardShrink operator");
AddOutput("Out", "Output of HardShrink operator");
AddAttr<float>("threshold", "The value of threshold for HardShrink")
@@ -265,8 +261,7 @@ $$
class BReluOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- BReluOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : framework::OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X", "Input of BRelu operator");
AddOutput("Out", "Output of BRelu operator");
AddAttr<float>("t_min", "The min marginal value of BRelu")
@@ -284,8 +279,7 @@ $out = \max(\min(x, t_{min}), t_{max})$
class SoftReluOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- SoftReluOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : framework::OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X", "Input of SoftRelu operator");
AddOutput("Out", "Output of SoftRelu operator");
AddAttr<float>("threshold", "The threshold value of SoftRelu")
@@ -301,8 +295,7 @@ $out = \ln(1 + \exp(\max(\min(x, threshold), threshold))$
class ELUOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- ELUOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : framework::OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X", "Input of ELU operator");
AddOutput("Out", "Output of ELU operator");
AddAttr<float>("alpha", "The alpha value of ELU").SetDefault(1.0f);
@@ -320,8 +313,7 @@ $out = \max(0, x) + \min(0, \alpha * (e^x - 1))$
class Relu6OpMaker : public framework::OpProtoAndCheckerMaker {
public:
- Relu6OpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : framework::OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X", "Input of Relu6 operator");
AddOutput("Out", "Output of Relu6 operator");
AddAttr<float>("threshold", "The threshold value of Relu6")
@@ -337,8 +329,7 @@ $out = \min(\max(0, x), 6)$
class PowOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- PowOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : framework::OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X", "Input of Pow operator");
AddOutput("Out", "Output of Pow operator");
AddAttr<float>("factor", "The exponential factor of Pow").SetDefault(1.0f);
@@ -353,8 +344,7 @@ $out = x^{factor}$
class STanhOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- STanhOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : framework::OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X", "Input of STanh operator");
AddOutput("Out", "Output of STanh operator");
AddAttr<float>("scale_a", "The scale parameter of a for the input")
@@ -372,8 +362,7 @@ $$out = b * \frac{e^{a * x} - e^{-a * x}}{e^{a * x} + e^{-a * x}}$$
class ThresholdedReluOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- ThresholdedReluOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : framework::OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X", "Input of ThresholdedRelu operator");
AddOutput("Out", "Output of ThresholdedRelu operator");
AddAttr<float>("threshold", "The threshold location of activation")
@@ -394,8 +383,7 @@ $$
class HardSigmoidOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- HardSigmoidOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : framework::OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X", "Input of HardSigmoid operator");
AddOutput("Out", "Output of HardSigmoid operator");
AddAttr<float>("slope", "Slope for linear approximation of sigmoid")
@@ -420,8 +408,7 @@ It is recommended to use the defaults for this activation.
class SwishOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- SwishOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : framework::OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X", "Input of Swish operator");
AddOutput("Out", "Output of Swish operator");
AddAttr<float>("beta", "Constant beta of swish operator").SetDefault(1.0f);
diff --git a/paddle/fluid/operators/adadelta_op.cc b/paddle/fluid/operators/adadelta_op.cc
index 7bdb3f274a..d1970515f5 100644
--- a/paddle/fluid/operators/adadelta_op.cc
+++ b/paddle/fluid/operators/adadelta_op.cc
@@ -66,8 +66,7 @@ class AdadeltaOp : public framework::OperatorWithKernel {
class AdadeltaOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- AdadeltaOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("Param", "(Tensor) Input parameter");
AddInput("Grad", "(Tensor) Input gradient");
AddInput("AvgSquaredGrad", "(Tensor) Input average of squared gradient");
diff --git a/paddle/fluid/operators/adagrad_op.cc b/paddle/fluid/operators/adagrad_op.cc
index 1227129429..a3ef9ad9f9 100644
--- a/paddle/fluid/operators/adagrad_op.cc
+++ b/paddle/fluid/operators/adagrad_op.cc
@@ -67,8 +67,7 @@ class AdagradOp : public framework::OperatorWithKernel {
class AdagradOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- AdagradOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("Param", "(Tensor) Input parameter");
AddInput("Grad", "(Tensor) Input gradient");
AddInput("Moment", "(Tensor) Second moment");
diff --git a/paddle/fluid/operators/adam_op.cc b/paddle/fluid/operators/adam_op.cc
index f12f0c6663..99b0239855 100644
--- a/paddle/fluid/operators/adam_op.cc
+++ b/paddle/fluid/operators/adam_op.cc
@@ -80,8 +80,7 @@ class AdamOp : public framework::OperatorWithKernel {
class AdamOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- AdamOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("Param", "(Tensor) Input parameter");
AddInput("Grad", "(Tensor) Input gradient");
AddInput("LearningRate", "(Tensor) Learning rate");
diff --git a/paddle/fluid/operators/adamax_op.cc b/paddle/fluid/operators/adamax_op.cc
index 608b855d58..32062574bc 100644
--- a/paddle/fluid/operators/adamax_op.cc
+++ b/paddle/fluid/operators/adamax_op.cc
@@ -74,8 +74,7 @@ class AdamaxOp : public framework::OperatorWithKernel {
class AdamaxOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- AdamaxOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("Param", "(Tensor) Input parameter");
AddInput("Grad", "(Tensor) Input gradient");
AddInput("LearningRate", "(Tensor) Learning rate");
diff --git a/paddle/fluid/operators/array_to_lod_tensor_op.cc b/paddle/fluid/operators/array_to_lod_tensor_op.cc
index 5db2e4540e..149226e92d 100644
--- a/paddle/fluid/operators/array_to_lod_tensor_op.cc
+++ b/paddle/fluid/operators/array_to_lod_tensor_op.cc
@@ -123,8 +123,7 @@ class ArrayToLoDTensorOp : public framework::OperatorBase {
class ArrayToLoDTensorOpProtoMaker : public framework::OpProtoAndCheckerMaker {
public:
- ArrayToLoDTensorOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X",
"(std::vector<LodTensor>) A vector of tensors that is going to "
"be casted to a big LoDTensor.");
diff --git a/paddle/fluid/operators/assign_op.cc b/paddle/fluid/operators/assign_op.cc
index d372213e1b..d9294048a9 100644
--- a/paddle/fluid/operators/assign_op.cc
+++ b/paddle/fluid/operators/assign_op.cc
@@ -94,8 +94,7 @@ class AssignOp : public framework::OperatorBase {
class AssignOpProtoMaker : public framework::OpProtoAndCheckerMaker {
public:
- AssignOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X",
"(LoDTensor, SelectedRows or LoDTensorArray) The input variable "
"could be LoDTensor, SelectedRows or LoDTensorArray.")
diff --git a/paddle/fluid/operators/assign_value_op.cc b/paddle/fluid/operators/assign_value_op.cc
index 993610fded..4ad6f3443d 100644
--- a/paddle/fluid/operators/assign_value_op.cc
+++ b/paddle/fluid/operators/assign_value_op.cc
@@ -45,8 +45,7 @@ class AssignValueOp : public framework::OperatorWithKernel {
class AssignValueOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- AssignValueOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddOutput("Out", "(Tensor) Output tensor of assign_value operator.");
AddAttr<std::vector<int>>("shape",
"(vector<int>) "
diff --git a/paddle/fluid/operators/auc_op.cc b/paddle/fluid/operators/auc_op.cc
index a168eaeab5..c9871a9fe6 100644
--- a/paddle/fluid/operators/auc_op.cc
+++ b/paddle/fluid/operators/auc_op.cc
@@ -50,8 +50,7 @@ class AucOp : public framework::OperatorWithKernel {
class AucOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- AucOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("Out",
"A floating point 2D tensor, values are in the range [0, 1]."
"Each row is sorted in descending order. This input should be the"
diff --git a/paddle/fluid/operators/average_accumulates_op.cc b/paddle/fluid/operators/average_accumulates_op.cc
index b21deaf925..25864e95d7 100644
--- a/paddle/fluid/operators/average_accumulates_op.cc
+++ b/paddle/fluid/operators/average_accumulates_op.cc
@@ -111,8 +111,7 @@ class AverageAccumulatesOp : public framework::OperatorWithKernel {
class AverageAccumulatesOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- AverageAccumulatesOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("param", "(Tensor), The parameter to be accumulated.");
AddInput("in_sum_1",
"(Tensor), A tensor used to store the parameter "
diff --git a/paddle/fluid/operators/batch_norm_op.cc b/paddle/fluid/operators/batch_norm_op.cc
index b4bd40d031..6ec8c9d18b 100644
--- a/paddle/fluid/operators/batch_norm_op.cc
+++ b/paddle/fluid/operators/batch_norm_op.cc
@@ -126,8 +126,7 @@ class BatchNormOp : public framework::OperatorWithKernel {
class BatchNormOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- BatchNormOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddAttr<bool>("is_test", "").SetDefault(false);
AddAttr<float>("momentum", "").SetDefault(0.9);
AddAttr<float>("epsilon", "")
diff --git a/paddle/fluid/operators/batch_size_like.h b/paddle/fluid/operators/batch_size_like.h
index dd51a11fbe..d01b7e4c8d 100644
--- a/paddle/fluid/operators/batch_size_like.h
+++ b/paddle/fluid/operators/batch_size_like.h
@@ -53,8 +53,7 @@ class BatchSizeLikeOp : public framework::OperatorWithKernel {
class BatchSizeLikeOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- BatchSizeLikeOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : framework::OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("Input",
"(Tensor) Tensor "
"whose input_dim_idx'th dimension specifies the batch_size");
diff --git a/paddle/fluid/operators/beam_search_decode_op.cc b/paddle/fluid/operators/beam_search_decode_op.cc
index 68fb988afd..c3dd22119d 100644
--- a/paddle/fluid/operators/beam_search_decode_op.cc
+++ b/paddle/fluid/operators/beam_search_decode_op.cc
@@ -134,8 +134,7 @@ class BeamSearchDecodeOp : public framework::OperatorBase {
class BeamSearchDecodeOpProtoMaker : public framework::OpProtoAndCheckerMaker {
public:
- BeamSearchDecodeOpProtoMaker(OpProto* proto, OpAttrChecker* op_checker)
- : framework::OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("Ids",
"(LodTensorArray)"
"score of the candidate words in each step");
diff --git a/paddle/fluid/operators/beam_search_op.cc b/paddle/fluid/operators/beam_search_op.cc
index cff097cca1..df0b50881f 100644
--- a/paddle/fluid/operators/beam_search_op.cc
+++ b/paddle/fluid/operators/beam_search_op.cc
@@ -197,8 +197,7 @@ std::string ItemToString(const BeamSearch::Item &item) {
class BeamSearchOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- BeamSearchOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
// inputs and outputs stored in proto
AddInput("pre_ids", "ids in previous step");
AddInput("ids", "a LoDTensor of shape of [None,k]");
diff --git a/paddle/fluid/operators/bilinear_interp_op.cc b/paddle/fluid/operators/bilinear_interp_op.cc
index 69f79bf93b..d46fda54e7 100644
--- a/paddle/fluid/operators/bilinear_interp_op.cc
+++ b/paddle/fluid/operators/bilinear_interp_op.cc
@@ -41,8 +41,7 @@ class BilinearInterpOp : public framework::OperatorWithKernel {
class BilinearInterpOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- BilinearInterpOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X",
"(Tensor) The input tensor of bilinear interpolation, "
"This is a 4-D tensor with shape of (N x C x h x w)");
diff --git a/paddle/fluid/operators/bilinear_tensor_product_op.cc b/paddle/fluid/operators/bilinear_tensor_product_op.cc
index e910ad92d1..8d261a118a 100644
--- a/paddle/fluid/operators/bilinear_tensor_product_op.cc
+++ b/paddle/fluid/operators/bilinear_tensor_product_op.cc
@@ -65,8 +65,7 @@ class BilinearTensorProductOp : public framework::OperatorWithKernel {
class BilinearTensorProductOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- BilinearTensorProductOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X", "The first input of bilinear_tensor_product operator.");
AddInput("Y", "The second input of bilinear_tensor_product operator.");
AddInput("Weight",
diff --git a/paddle/fluid/operators/bipartite_match_op.cc b/paddle/fluid/operators/bipartite_match_op.cc
index 1218d9fdc1..d437ad5c19 100644
--- a/paddle/fluid/operators/bipartite_match_op.cc
+++ b/paddle/fluid/operators/bipartite_match_op.cc
@@ -182,8 +182,7 @@ class BipartiteMatchKernel : public framework::OpKernel<T> {
class BipartiteMatchOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- BipartiteMatchOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput(
"DistMat",
"(LoDTensor or Tensor) this input is a 2-D LoDTensor with shape "
diff --git a/paddle/fluid/operators/box_coder_op.cc b/paddle/fluid/operators/box_coder_op.cc
index ec416f725e..ce9bf10dc3 100644
--- a/paddle/fluid/operators/box_coder_op.cc
+++ b/paddle/fluid/operators/box_coder_op.cc
@@ -60,8 +60,7 @@ class BoxCoderOp : public framework::OperatorWithKernel {
class BoxCoderOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- BoxCoderOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput(
"PriorBox",
"(Tensor, default Tensor<float>) "
diff --git a/paddle/fluid/operators/cast_op.cc b/paddle/fluid/operators/cast_op.cc
index dd0068d571..84660d042c 100644
--- a/paddle/fluid/operators/cast_op.cc
+++ b/paddle/fluid/operators/cast_op.cc
@@ -21,8 +21,7 @@ namespace operators {
class CastOpProtoMaker : public framework::OpProtoAndCheckerMaker {
public:
- CastOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X", "The input tensor of cast op");
AddOutput("Out", "The output tensor of cast op");
AddAttr<int>("out_dtype", "output data type");
diff --git a/paddle/fluid/operators/channel_close_op.cc b/paddle/fluid/operators/channel_close_op.cc
index 5892650c49..8e2db250a0 100644
--- a/paddle/fluid/operators/channel_close_op.cc
+++ b/paddle/fluid/operators/channel_close_op.cc
@@ -50,8 +50,7 @@ class ChannelCloseOpOpInferShape : public framework::InferShapeBase {
class ChannelCloseOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- ChannelCloseOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput(kChannel,
"The Channel Variable that should be closed by"
" the ChannelClose Op.");
diff --git a/paddle/fluid/operators/channel_create_op.cc b/paddle/fluid/operators/channel_create_op.cc
index b2fdfd0e1f..a7f59e4088 100644
--- a/paddle/fluid/operators/channel_create_op.cc
+++ b/paddle/fluid/operators/channel_create_op.cc
@@ -91,8 +91,7 @@ class ChannelCreateOpOpInferShape : public framework::InferShapeBase {
class ChannelCreateOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- ChannelCreateOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddOutput(kOutput,
"The object of a Channel type created by ChannelCreate Op.");
AddAttr<int>("capacity", "The size of the buffer of Channel.")
diff --git a/paddle/fluid/operators/channel_recv_op.cc b/paddle/fluid/operators/channel_recv_op.cc
index 25c5c3c95e..101015e837 100644
--- a/paddle/fluid/operators/channel_recv_op.cc
+++ b/paddle/fluid/operators/channel_recv_op.cc
@@ -72,8 +72,7 @@ class ChannelRecvOp : public framework::OperatorBase {
class ChannelRecvOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- ChannelRecvOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput(Channel,
"(Channel) A variable which \"receives\" the a value sent"
"to it by a channel_send op.")
diff --git a/paddle/fluid/operators/channel_send_op.cc b/paddle/fluid/operators/channel_send_op.cc
index 66d33617ed..67d6deb511 100644
--- a/paddle/fluid/operators/channel_send_op.cc
+++ b/paddle/fluid/operators/channel_send_op.cc
@@ -57,8 +57,7 @@ class ChannelSendOp : public framework::OperatorBase {
class ChannelSendOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- ChannelSendOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput(Channel,
"(Channel) A variable which \"sends\" the passed in value to "
"a listening receiver.")
diff --git a/paddle/fluid/operators/chunk_eval_op.cc b/paddle/fluid/operators/chunk_eval_op.cc
index 95440ff89e..62636bb2f9 100644
--- a/paddle/fluid/operators/chunk_eval_op.cc
+++ b/paddle/fluid/operators/chunk_eval_op.cc
@@ -66,8 +66,7 @@ class ChunkEvalOp : public framework::OperatorWithKernel {
class ChunkEvalOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- ChunkEvalOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("Inference",
"(Tensor, default: Tensor<int64_t>). "
"Predictions from the network.");
diff --git a/paddle/fluid/operators/clip_by_norm_op.cc b/paddle/fluid/operators/clip_by_norm_op.cc
index f43726b479..c87bded034 100644
--- a/paddle/fluid/operators/clip_by_norm_op.cc
+++ b/paddle/fluid/operators/clip_by_norm_op.cc
@@ -37,8 +37,7 @@ class ClipByNormOp : public framework::OperatorWithKernel {
class ClipByNormOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- ClipByNormOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X",
"(Tensor) The input of clip_by_norm op."
"The number of dimensions must be between [1, 9].");
diff --git a/paddle/fluid/operators/clip_op.cc b/paddle/fluid/operators/clip_op.cc
index c71139fc7c..a679f7e253 100644
--- a/paddle/fluid/operators/clip_op.cc
+++ b/paddle/fluid/operators/clip_op.cc
@@ -38,8 +38,7 @@ class ClipOp : public framework::OperatorWithKernel {
template <typename AttrType>
class ClipOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- ClipOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X",
"(Tensor)The input of clip op."
"The number of dimensions must be between [1, 9].");
diff --git a/paddle/fluid/operators/compare_op.cc b/paddle/fluid/operators/compare_op.cc
index 3a6a357e81..3a4819f3de 100644
--- a/paddle/fluid/operators/compare_op.cc
+++ b/paddle/fluid/operators/compare_op.cc
@@ -21,8 +21,7 @@ namespace operators {
template <typename OpComment>
class CompareOpProtoMaker : public framework::OpProtoAndCheckerMaker {
public:
- CompareOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
OpComment comment;
AddInput("X",
string::Sprintf("(LoDTensor) the left hand operand of %s operator",
diff --git a/paddle/fluid/operators/concat_op.cc b/paddle/fluid/operators/concat_op.cc
index 3bb3bd4eb1..38337f9aa5 100644
--- a/paddle/fluid/operators/concat_op.cc
+++ b/paddle/fluid/operators/concat_op.cc
@@ -63,8 +63,7 @@ class ConcatOp : public framework::OperatorWithKernel {
class ConcatOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- ConcatOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X", "Input tensors of concat operator.").AsDuplicable();
AddOutput("Out", "Output tensor of concat operator.");
AddAttr<int>("axis",
diff --git a/paddle/fluid/operators/conditional_block_op.cc b/paddle/fluid/operators/conditional_block_op.cc
index 27f74a789b..5984f80d04 100644
--- a/paddle/fluid/operators/conditional_block_op.cc
+++ b/paddle/fluid/operators/conditional_block_op.cc
@@ -108,8 +108,7 @@ class ConditionalBlockOp : public ConditionalOp {
class ConditionalBlockOpProtoMaker : public framework::OpProtoAndCheckerMaker {
public:
- ConditionalBlockOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X",
"The conditional variable of this operator. If X is empty, the "
"whole sub-block will not be executed.")
diff --git a/paddle/fluid/operators/conv_op.cc b/paddle/fluid/operators/conv_op.cc
index 92748993c3..697d914842 100644
--- a/paddle/fluid/operators/conv_op.cc
+++ b/paddle/fluid/operators/conv_op.cc
@@ -106,8 +106,7 @@ framework::OpKernelType ConvOp::GetExpectedKernelType(
library);
}
-Conv2DOpMaker::Conv2DOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+void Conv2DOpMaker::Make() {
AddInput(
"Input",
"(Tensor) The input tensor of convolution operator. "
@@ -200,8 +199,7 @@ $$
)DOC");
}
-Conv3DOpMaker::Conv3DOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+void Conv3DOpMaker::Make() {
AddInput(
"Input",
"(Tensor) The input tensor of convolution operator. "
diff --git a/paddle/fluid/operators/conv_op.h b/paddle/fluid/operators/conv_op.h
index c51898abb4..1c5c3443a5 100644
--- a/paddle/fluid/operators/conv_op.h
+++ b/paddle/fluid/operators/conv_op.h
@@ -60,12 +60,12 @@ inline bool IsExpand(const std::vector<int64_t>& filter_dim,
// operator implementations can reuse the code.
class Conv2DOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- Conv2DOpMaker(OpProto* proto, OpAttrChecker* op_checker);
+ void Make() override;
};
class Conv3DOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- Conv3DOpMaker(OpProto* proto, OpAttrChecker* op_checker);
+ void Make() override;
};
class ConvOp : public framework::OperatorWithKernel {
diff --git a/paddle/fluid/operators/conv_shift_op.cc b/paddle/fluid/operators/conv_shift_op.cc
index 82fdd30820..f2549e814d 100644
--- a/paddle/fluid/operators/conv_shift_op.cc
+++ b/paddle/fluid/operators/conv_shift_op.cc
@@ -75,8 +75,7 @@ class ConvShiftGradOp : public framework::OperatorWithKernel {
class ConvShiftOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- ConvShiftOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : framework::OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X",
"(Tensor, default Tensor<float>), a 2-D tensor with shape B x M, "
"where B is the batch size and M is the data dimension.");
diff --git a/paddle/fluid/operators/conv_transpose_op.cc b/paddle/fluid/operators/conv_transpose_op.cc
index d699dcafa4..c27c8e2731 100644
--- a/paddle/fluid/operators/conv_transpose_op.cc
+++ b/paddle/fluid/operators/conv_transpose_op.cc
@@ -84,9 +84,7 @@ framework::OpKernelType ConvTransposeOp::GetExpectedKernelType(
layout_, library_);
}
-Conv2DTransposeOpMaker::Conv2DTransposeOpMaker(OpProto* proto,
- OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+void Conv2DTransposeOpMaker::Make() {
AddInput(
"Input",
"(Tensor) The input tensor of convolution transpose operator. "
@@ -168,9 +166,7 @@ Example:
)DOC");
}
-Conv3DTransposeOpMaker::Conv3DTransposeOpMaker(OpProto* proto,
- OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+void Conv3DTransposeOpMaker::Make() {
AddInput("Input",
"(Tensor) The input tensor of convolution transpose operator."
"The format of input tensor is NCDHW. Where N is batch size, C is "
diff --git a/paddle/fluid/operators/conv_transpose_op.h b/paddle/fluid/operators/conv_transpose_op.h
index 9276e5bfef..2e62daa4fc 100644
--- a/paddle/fluid/operators/conv_transpose_op.h
+++ b/paddle/fluid/operators/conv_transpose_op.h
@@ -30,12 +30,12 @@ using DDim = framework::DDim;
// operator implementations can reuse the code.
class Conv2DTransposeOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- Conv2DTransposeOpMaker(OpProto* proto, OpAttrChecker* op_checker);
+ void Make() override;
};
class Conv3DTransposeOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- Conv3DTransposeOpMaker(OpProto* proto, OpAttrChecker* op_checker);
+ void Make() override;
};
class ConvTransposeOp : public framework::OperatorWithKernel {
diff --git a/paddle/fluid/operators/cos_sim_op.cc b/paddle/fluid/operators/cos_sim_op.cc
index 04ca878e68..046dd11910 100644
--- a/paddle/fluid/operators/cos_sim_op.cc
+++ b/paddle/fluid/operators/cos_sim_op.cc
@@ -62,8 +62,7 @@ class CosSimOp : public framework::OperatorWithKernel {
class CosSimOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- CosSimOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X", "The 1st input of cos_sim op.");
AddInput("Y", "The 2nd input of cos_sim op.");
AddOutput("Out", "The output of cos_sim op.");
diff --git a/paddle/fluid/operators/crf_decoding_op.cc b/paddle/fluid/operators/crf_decoding_op.cc
index a83013c428..40f43936db 100644
--- a/paddle/fluid/operators/crf_decoding_op.cc
+++ b/paddle/fluid/operators/crf_decoding_op.cc
@@ -18,8 +18,7 @@ namespace paddle {
namespace operators {
class CRFDecodingOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- CRFDecodingOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("Emission",
"(LoDTensor, default: LoDTensor<float>). A LoDTensor with shape "
"[N x D] where N is the size of the mini-batch and D is the total "
diff --git a/paddle/fluid/operators/crop_op.cc b/paddle/fluid/operators/crop_op.cc
index a8f1fbd529..669b3bbe9d 100644
--- a/paddle/fluid/operators/crop_op.cc
+++ b/paddle/fluid/operators/crop_op.cc
@@ -52,8 +52,7 @@ class CropOp : public framework::OperatorWithKernel {
class CropOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- CropOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X",
"The input of pad op. "
"The input should be a k-D tensor(k > 0 and k < 7).");
diff --git a/paddle/fluid/operators/cross_entropy_op.cc b/paddle/fluid/operators/cross_entropy_op.cc
index 2b2a9dc831..a3bec3da45 100644
--- a/paddle/fluid/operators/cross_entropy_op.cc
+++ b/paddle/fluid/operators/cross_entropy_op.cc
@@ -111,8 +111,7 @@ class CrossEntropyGradientOp : public framework::OperatorWithKernel {
class CrossEntropyOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- CrossEntropyOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X",
"(Tensor, default Tensor<float>), a 2-D tensor with shape [N x D],"
" where N is the batch size and D is the number of classes. "
diff --git a/paddle/fluid/operators/ctc_align_op.cc b/paddle/fluid/operators/ctc_align_op.cc
index 19e7649660..d2b440d9d2 100644
--- a/paddle/fluid/operators/ctc_align_op.cc
+++ b/paddle/fluid/operators/ctc_align_op.cc
@@ -44,8 +44,7 @@ class CTCAlignOp : public framework::OperatorWithKernel {
class CTCAlignOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- CTCAlignOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("Input",
"(LodTensor, default: LoDTensor<int>), Its shape is "
"[Lp, 1], where Lp is the sum of all input sequences' length.");
diff --git a/paddle/fluid/operators/cumsum_op.cc b/paddle/fluid/operators/cumsum_op.cc
index f7c516a0ba..92bb835e8f 100644
--- a/paddle/fluid/operators/cumsum_op.cc
+++ b/paddle/fluid/operators/cumsum_op.cc
@@ -29,8 +29,7 @@ class CumOp : public framework::OperatorWithKernel {
class CumsumOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- CumsumOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : framework::OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X", "Input of Cumsum operator");
AddOutput("Out", "Output of Cumsum operator");
AddAttr<int>("axis",
diff --git a/paddle/fluid/operators/decayed_adagrad_op.cc b/paddle/fluid/operators/decayed_adagrad_op.cc
index 5a1315fb2a..c0f2b49a04 100644
--- a/paddle/fluid/operators/decayed_adagrad_op.cc
+++ b/paddle/fluid/operators/decayed_adagrad_op.cc
@@ -62,8 +62,7 @@ class DecayedAdagradOp : public framework::OperatorWithKernel {
class DecayedAdagradOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- DecayedAdagradOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("Param", "(Tensor) Input parameter");
AddInput("Grad", "(Tensor) Input gradient");
AddInput("Moment", "(Tensor) Second moment");
diff --git a/paddle/fluid/operators/delete_var_op.cc b/paddle/fluid/operators/delete_var_op.cc
index 1fe9404c00..d7a9bfbc43 100644
--- a/paddle/fluid/operators/delete_var_op.cc
+++ b/paddle/fluid/operators/delete_var_op.cc
@@ -34,8 +34,7 @@ class DeleteVarOp : public framework::OperatorBase {
class DeleteVarOpInfoMaker : public framework::OpProtoAndCheckerMaker {
public:
- DeleteVarOpInfoMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X", "The input of delete op").AsDuplicable();
AddComment(R"DOC(
Delete Operator.
diff --git a/paddle/fluid/operators/detection_map_op.cc b/paddle/fluid/operators/detection_map_op.cc
index 38f43b6d03..0ccf701b61 100644
--- a/paddle/fluid/operators/detection_map_op.cc
+++ b/paddle/fluid/operators/detection_map_op.cc
@@ -78,8 +78,7 @@ class DetectionMAPOp : public framework::OperatorWithKernel {
class DetectionMAPOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- DetectionMAPOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("DetectRes",
"(LoDTensor) A 2-D LoDTensor with shape [M, 6] represents the "
"detections. Each row has 6 values: "
diff --git a/paddle/fluid/operators/dropout_op.cc b/paddle/fluid/operators/dropout_op.cc
index 4ed1b54884..07322e720f 100644
--- a/paddle/fluid/operators/dropout_op.cc
+++ b/paddle/fluid/operators/dropout_op.cc
@@ -37,8 +37,7 @@ class DropoutOp : public framework::OperatorWithKernel {
class DropoutOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- DropoutOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X", "The input of dropout op.");
AddOutput("Out", "The output of dropout op.");
AddOutput("Mask", "The random sampled dropout mask.").AsIntermediate();
diff --git a/paddle/fluid/operators/edit_distance_op.cc b/paddle/fluid/operators/edit_distance_op.cc
index c7f037d2df..de25a3dab5 100644
--- a/paddle/fluid/operators/edit_distance_op.cc
+++ b/paddle/fluid/operators/edit_distance_op.cc
@@ -49,8 +49,7 @@ class EditDistanceOp : public framework::OperatorWithKernel {
class EditDistanceOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- EditDistanceOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("Hyps",
"(2-D LoDTensor<int64_t>, 2nd dim. equal to 1) "
"The indices for hypothesis strings.");
diff --git a/paddle/fluid/operators/elementwise_add_op.cc b/paddle/fluid/operators/elementwise_add_op.cc
index 4aab54f602..d2c2053713 100644
--- a/paddle/fluid/operators/elementwise_add_op.cc
+++ b/paddle/fluid/operators/elementwise_add_op.cc
@@ -14,26 +14,8 @@ limitations under the License. */
#include "paddle/fluid/operators/elementwise_add_op.h"
#include "paddle/fluid/operators/elementwise_op.h"
-
-namespace paddle {
-namespace operators {
-class ElementwiseAddOpMaker : public ElementwiseOpMaker {
- public:
- ElementwiseAddOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : ElementwiseOpMaker(proto, op_checker) {
- SetComment("Add", "Out = X + Y");
- AddComment(comment_);
- }
-};
-} // namespace operators
-} // namespace paddle
-
namespace ops = paddle::operators;
-REGISTER_OPERATOR(elementwise_add, ops::ElementwiseOp,
- ops::ElementwiseAddOpMaker, ops::ElementwiseOpInferVarType,
- paddle::framework::DefaultGradOpDescMaker<true>);
-REGISTER_OPERATOR(elementwise_add_grad, ops::ElementwiseOpGrad);
-
+REGISTER_ELEMWISE_OP(elementwise_add, "Add", "Out = X + Y");
REGISTER_OP_CPU_KERNEL(
elementwise_add,
ops::ElementwiseAddKernel<paddle::platform::CPUDeviceContext, float>,
diff --git a/paddle/fluid/operators/elementwise_div_op.cc b/paddle/fluid/operators/elementwise_div_op.cc
index c7ddafcad1..824b1221e5 100644
--- a/paddle/fluid/operators/elementwise_div_op.cc
+++ b/paddle/fluid/operators/elementwise_div_op.cc
@@ -14,26 +14,8 @@ limitations under the License. */
#include "paddle/fluid/operators/elementwise_div_op.h"
#include "paddle/fluid/operators/elementwise_op.h"
-
-namespace paddle {
-namespace operators {
-class ElementwiseDivOpMaker : public ElementwiseOpMaker {
- public:
- ElementwiseDivOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : ElementwiseOpMaker(proto, op_checker) {
- SetComment("Div", "Out = X / Y");
- AddComment(comment_);
- }
-};
-
-} // namespace operators
-} // namespace paddle
-
namespace ops = paddle::operators;
-REGISTER_OPERATOR(elementwise_div, ops::ElementwiseOp,
- ops::ElementwiseDivOpMaker,
- paddle::framework::DefaultGradOpDescMaker<true>);
-REGISTER_OPERATOR(elementwise_div_grad, ops::ElementwiseOpGrad);
+REGISTER_ELEMWISE_OP(elementwise_div, "Div", "Out = X / Y");
REGISTER_OP_CPU_KERNEL(
elementwise_div,
ops::ElementwiseDivKernel<paddle::platform::CPUDeviceContext, float>,
diff --git a/paddle/fluid/operators/elementwise_max_op.cc b/paddle/fluid/operators/elementwise_max_op.cc
index a4fe386bb1..411671335a 100644
--- a/paddle/fluid/operators/elementwise_max_op.cc
+++ b/paddle/fluid/operators/elementwise_max_op.cc
@@ -14,25 +14,8 @@ limitations under the License. */
#include "paddle/fluid/operators/elementwise_max_op.h"
#include "paddle/fluid/operators/elementwise_op.h"
-
-namespace paddle {
-namespace operators {
-class ElementwiseMaxOpMaker : public ElementwiseOpMaker {
- public:
- ElementwiseMaxOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : ElementwiseOpMaker(proto, op_checker) {
- SetComment("Max", "Out = max(X, Y)");
- AddComment(comment_);
- }
-};
-} // namespace operators
-} // namespace paddle
-
namespace ops = paddle::operators;
-REGISTER_OPERATOR(elementwise_max, ops::ElementwiseOp,
- ops::ElementwiseMaxOpMaker,
- paddle::framework::DefaultGradOpDescMaker<true>);
-REGISTER_OPERATOR(elementwise_max_grad, ops::ElementwiseOpGrad);
+REGISTER_ELEMWISE_OP(elementwise_max, "Max", "Out = max(X, Y)");
REGISTER_OP_CPU_KERNEL(
elementwise_max,
ops::ElementwiseMaxKernel<paddle::platform::CPUDeviceContext, float>,
diff --git a/paddle/fluid/operators/elementwise_min_op.cc b/paddle/fluid/operators/elementwise_min_op.cc
index 68cd6ddb4a..816192083d 100644
--- a/paddle/fluid/operators/elementwise_min_op.cc
+++ b/paddle/fluid/operators/elementwise_min_op.cc
@@ -14,25 +14,8 @@ limitations under the License. */
#include "paddle/fluid/operators/elementwise_min_op.h"
#include "paddle/fluid/operators/elementwise_op.h"
-
-namespace paddle {
-namespace operators {
-class ElementwiseMinOpMaker : public ElementwiseOpMaker {
- public:
- ElementwiseMinOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : ElementwiseOpMaker(proto, op_checker) {
- SetComment("Max", "Out = min(X, Y)");
- AddComment(comment_);
- }
-};
-} // namespace operators
-} // namespace paddle
-
namespace ops = paddle::operators;
-REGISTER_OPERATOR(elementwise_min, ops::ElementwiseOp,
- ops::ElementwiseMinOpMaker,
- paddle::framework::DefaultGradOpDescMaker<true>);
-REGISTER_OPERATOR(elementwise_min_grad, ops::ElementwiseOpGrad);
+REGISTER_ELEMWISE_OP(elementwise_min, "Min", "Out = min(X, Y)");
REGISTER_OP_CPU_KERNEL(
elementwise_min,
ops::ElementwiseMinKernel<paddle::platform::CPUDeviceContext, float>,
diff --git a/paddle/fluid/operators/elementwise_mul_op.cc b/paddle/fluid/operators/elementwise_mul_op.cc
index 2dec27136a..ba343909bb 100644
--- a/paddle/fluid/operators/elementwise_mul_op.cc
+++ b/paddle/fluid/operators/elementwise_mul_op.cc
@@ -14,27 +14,8 @@ limitations under the License. */
#include "paddle/fluid/operators/elementwise_mul_op.h"
#include "paddle/fluid/operators/elementwise_op.h"
-
-namespace paddle {
-namespace operators {
-
-class ElementwiseMulOpMaker : public ElementwiseOpMaker {
- public:
- ElementwiseMulOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : ElementwiseOpMaker(proto, op_checker) {
- SetComment("Mul", "Out = X \\odot\\ Y");
- AddComment(comment_);
- }
-};
-
-} // namespace operators
-} // namespace paddle
-
namespace ops = paddle::operators;
-REGISTER_OPERATOR(elementwise_mul, ops::ElementwiseOp,
- ops::ElementwiseMulOpMaker,
- paddle::framework::DefaultGradOpDescMaker<true>);
-REGISTER_OPERATOR(elementwise_mul_grad, ops::ElementwiseOpGrad);
+REGISTER_ELEMWISE_OP(elementwise_mul, "Mul", "Out = X \\odot\\ Y");
REGISTER_OP_CPU_KERNEL(
elementwise_mul,
ops::ElementwiseMulKernel<paddle::platform::CPUDeviceContext, float>,
diff --git a/paddle/fluid/operators/elementwise_op.h b/paddle/fluid/operators/elementwise_op.h
index a33634ab25..d5b57cc252 100644
--- a/paddle/fluid/operators/elementwise_op.h
+++ b/paddle/fluid/operators/elementwise_op.h
@@ -54,8 +54,7 @@ class ElementwiseOpInferVarType : public framework::VarTypeInference {
class ElementwiseOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- ElementwiseOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() final {
AddInput("X", "(Tensor), The first input tensor of elementwise op.");
AddInput("Y", "(Tensor), The second input tensor of elementwise op.");
AddOutput("Out", "The output of elementwise op.");
@@ -64,12 +63,12 @@ class ElementwiseOpMaker : public framework::OpProtoAndCheckerMaker {
"for broadcasting Y onto X.")
.SetDefault(-1)
.EqualGreaterThan(-1);
- comment_ = R"DOC(
-Limited Elementwise {name} Operator.
+ AddComment(string::Sprintf(R"DOC(
+Limited Elementwise %s Operator.
The equation is:
-$${equation}$$
+$$%s$$
$X$ is a tensor of any dimension and the dimensions of tensor $Y$ must be
smaller than or equal to the dimensions of $X$.
@@ -100,26 +99,13 @@ For example
Either of the inputs $X$ and $Y$ or none can carry the LoD (Level of Details)
information. However, the output only shares the LoD information with input $X$.
-)DOC";
- AddComment(comment_);
+)DOC",
+ GetName(), GetEquation()));
}
protected:
- std::string comment_;
-
- void Replace(std::string* src, std::string from, std::string to) {
- std::size_t len_from = std::strlen(from.c_str());
- std::size_t len_to = std::strlen(to.c_str());
- for (std::size_t pos = src->find(from); pos != std::string::npos;
- pos = src->find(from, pos + len_to)) {
- src->replace(pos, len_from, to);
- }
- }
-
- void SetComment(std::string name, std::string equation) {
- Replace(&comment_, "{name}", name);
- Replace(&comment_, "{equation}", equation);
- }
+ virtual std::string GetName() const = 0;
+ virtual std::string GetEquation() const = 0;
};
class ElementwiseOpGrad : public framework::OperatorWithKernel {
@@ -152,3 +138,16 @@ class ElementwiseOpGrad : public framework::OperatorWithKernel {
};
} // namespace operators
} // namespace paddle
+
+#define REGISTER_ELEMWISE_OP(op_type, op_name, equation) \
+ class __ElemwiseOp##op_type##Maker__ \
+ : public ::paddle::operators::ElementwiseOpMaker { \
+ protected: \
+ virtual std::string GetName() const { return op_name; } \
+ virtual std::string GetEquation() const { return equation; } \
+ }; \
+ REGISTER_OPERATOR(op_type, ::paddle::operators::ElementwiseOp, \
+ __ElemwiseOp##op_type##Maker__, \
+ ::paddle::operators::ElementwiseOpInferVarType, \
+ ::paddle::framework::DefaultGradOpDescMaker<true>); \
+ REGISTER_OPERATOR(op_type##_grad, ::paddle::operators::ElementwiseOpGrad)
diff --git a/paddle/fluid/operators/elementwise_pow_op.cc b/paddle/fluid/operators/elementwise_pow_op.cc
index 60302c5e59..5fd6bde9ba 100644
--- a/paddle/fluid/operators/elementwise_pow_op.cc
+++ b/paddle/fluid/operators/elementwise_pow_op.cc
@@ -13,17 +13,15 @@ See the License for the specific language governing permissions and
limitations under the License. */
#include "paddle/fluid/operators/elementwise_pow_op.h"
+#include <string>
#include "paddle/fluid/operators/elementwise_op.h"
namespace paddle {
namespace operators {
class ElementwisePowOpMaker : public ElementwiseOpMaker {
- public:
- ElementwisePowOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : ElementwiseOpMaker(proto, op_checker) {
- SetComment("Pow", "Out = X ^ Y");
- AddComment(comment_);
- }
+ protected:
+ std::string GetName() const override { return "Pow"; }
+ std::string GetEquation() const override { return "Out = X ^ Y"; }
};
} // namespace operators
} // namespace paddle
diff --git a/paddle/fluid/operators/elementwise_sub_op.cc b/paddle/fluid/operators/elementwise_sub_op.cc
index 9d0598fc39..a7562b166b 100644
--- a/paddle/fluid/operators/elementwise_sub_op.cc
+++ b/paddle/fluid/operators/elementwise_sub_op.cc
@@ -14,25 +14,8 @@ limitations under the License. */
#include "paddle/fluid/operators/elementwise_sub_op.h"
#include "paddle/fluid/operators/elementwise_op.h"
-
-namespace paddle {
-namespace operators {
-class ElementwiseSubOpMaker : public ElementwiseOpMaker {
- public:
- ElementwiseSubOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : ElementwiseOpMaker(proto, op_checker) {
- SetComment("Sub", "Out = X - Y");
- AddComment(comment_);
- }
-};
-} // namespace operators
-} // namespace paddle
-
namespace ops = paddle::operators;
-REGISTER_OPERATOR(elementwise_sub, ops::ElementwiseOp,
- ops::ElementwiseSubOpMaker,
- paddle::framework::DefaultGradOpDescMaker<true>);
-REGISTER_OPERATOR(elementwise_sub_grad, ops::ElementwiseOpGrad);
+REGISTER_ELEMWISE_OP(elementwise_sub, "Sub", "Out = X - Y");
REGISTER_OP_CPU_KERNEL(
elementwise_sub,
ops::ElementwiseSubKernel<paddle::platform::CPUDeviceContext, float>,
diff --git a/paddle/fluid/operators/expand_op.cc b/paddle/fluid/operators/expand_op.cc
index 4ae91d074d..5ad0ec2513 100644
--- a/paddle/fluid/operators/expand_op.cc
+++ b/paddle/fluid/operators/expand_op.cc
@@ -56,8 +56,7 @@ class ExpandOp : public framework::OperatorWithKernel {
class ExpandOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- ExpandOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X",
"(Tensor, default Tensor<float>). A tensor with rank in [1, 6]."
"X is the input to be expanded.");
diff --git a/paddle/fluid/operators/fc_op.cc b/paddle/fluid/operators/fc_op.cc
index 45e4d5b2b8..8843a1c44b 100644
--- a/paddle/fluid/operators/fc_op.cc
+++ b/paddle/fluid/operators/fc_op.cc
@@ -72,8 +72,7 @@ framework::OpKernelType FCOpGrad::GetExpectedKernelType(
layout, library);
}
-FCOpMaker::FCOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+void FCOpMaker::Make() {
AddInput("Input", "(Tensor) The input tensor of fully connected operator. ");
AddInput("W", "(Tensor), The second input tensor of fc op.");
AddOutput("Out", "(Tensor) The output tensor of fully connected operator. ");
diff --git a/paddle/fluid/operators/fc_op.h b/paddle/fluid/operators/fc_op.h
index 70fa96440d..e1b780fc0c 100644
--- a/paddle/fluid/operators/fc_op.h
+++ b/paddle/fluid/operators/fc_op.h
@@ -45,7 +45,7 @@ class FCOpGrad : public framework::OperatorWithKernel {
class FCOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- FCOpMaker(OpProto* proto, OpAttrChecker* op_checker);
+ void Make() override;
};
} // namespace operators
diff --git a/paddle/fluid/operators/feed_op.cc b/paddle/fluid/operators/feed_op.cc
index debacf07c3..bcb3e63ed7 100644
--- a/paddle/fluid/operators/feed_op.cc
+++ b/paddle/fluid/operators/feed_op.cc
@@ -66,8 +66,7 @@ class FeedOp : public framework::OperatorBase {
class FeedOpInfoMaker : public framework::OpProtoAndCheckerMaker {
public:
- FeedOpInfoMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X", "The input of feed op");
AddOutput("Out", "The output of feed op");
AddAttr<int>("col", "(int) The column of feed");
diff --git a/paddle/fluid/operators/fetch_op.cc b/paddle/fluid/operators/fetch_op.cc
index 18deec5813..1640a2a22c 100644
--- a/paddle/fluid/operators/fetch_op.cc
+++ b/paddle/fluid/operators/fetch_op.cc
@@ -66,8 +66,7 @@ class FetchOp : public framework::OperatorBase {
class FetchOpInfoMaker : public framework::OpProtoAndCheckerMaker {
public:
- FetchOpInfoMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X", "The input of fetch op");
AddOutput("Out", "The output of fetch op");
AddAttr<int>("col", "(int) The column of fetch");
diff --git a/paddle/fluid/operators/fill_constant_batch_size_like_op.cc b/paddle/fluid/operators/fill_constant_batch_size_like_op.cc
index 72da80baaf..e6bcbecad6 100644
--- a/paddle/fluid/operators/fill_constant_batch_size_like_op.cc
+++ b/paddle/fluid/operators/fill_constant_batch_size_like_op.cc
@@ -31,8 +31,7 @@ class FillConstantBatchSizeLikeOp : public BatchSizeLikeOp {
class FillConstantBatchSizeLikeOpMaker : public BatchSizeLikeOpMaker {
public:
- FillConstantBatchSizeLikeOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : BatchSizeLikeOpMaker(proto, op_checker) {
+ void Make() override {
AddAttr<int>("dtype",
"(int, default 5 (FP32)) "
"Output data type")
diff --git a/paddle/fluid/operators/fill_constant_op.cc b/paddle/fluid/operators/fill_constant_op.cc
index 07e0a80f8d..130f18dde4 100644
--- a/paddle/fluid/operators/fill_constant_op.cc
+++ b/paddle/fluid/operators/fill_constant_op.cc
@@ -59,8 +59,7 @@ class FillConstantOp : public framework::OperatorBase {
class FillConstantOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- FillConstantOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : framework::OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddAttr<int>("dtype",
"(int, default 5 (FP32)) "
"Output data type")
diff --git a/paddle/fluid/operators/fill_op.cc b/paddle/fluid/operators/fill_op.cc
index ee8a2fc353..925dc19061 100644
--- a/paddle/fluid/operators/fill_op.cc
+++ b/paddle/fluid/operators/fill_op.cc
@@ -82,8 +82,7 @@ class FillOp : public framework::OperatorBase {
class FillOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- FillOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddComment(R"DOC(Fill operator
Fill an tensor with `value` and `shape`. The type of the tensor is specify by
diff --git a/paddle/fluid/operators/fill_zeros_like_op.cc b/paddle/fluid/operators/fill_zeros_like_op.cc
index 58c814ba64..d67bec36b3 100644
--- a/paddle/fluid/operators/fill_zeros_like_op.cc
+++ b/paddle/fluid/operators/fill_zeros_like_op.cc
@@ -33,8 +33,7 @@ class FillZerosLikeOp : public framework::OperatorWithKernel {
class FillZerosLikeOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- FillZerosLikeOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : framework::OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X", "The input of fill-zeros-like op.");
AddOutput("Out", "The variable will be filled up with zeros.");
AddComment(R"DOC(
diff --git a/paddle/fluid/operators/ftrl_op.cc b/paddle/fluid/operators/ftrl_op.cc
index cbdcce9beb..70ba25c213 100644
--- a/paddle/fluid/operators/ftrl_op.cc
+++ b/paddle/fluid/operators/ftrl_op.cc
@@ -64,8 +64,7 @@ class FTRLOp : public framework::OperatorWithKernel {
class FTRLOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- FTRLOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("Param",
"(Tensor, default Tensor<float>) "
"Input parameter value that has to be updated.");
diff --git a/paddle/fluid/operators/gather_op.cc b/paddle/fluid/operators/gather_op.cc
index 4c82f5c429..e21b572589 100644
--- a/paddle/fluid/operators/gather_op.cc
+++ b/paddle/fluid/operators/gather_op.cc
@@ -67,8 +67,7 @@ class GatherGradOp : public framework::OperatorWithKernel {
class GatherOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- GatherOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X", "The source input of gather op");
AddInput("Index", "The index input of gather op");
AddOutput("Out", "The output of gather op");
diff --git a/paddle/fluid/operators/gaussian_random_batch_size_like_op.cc b/paddle/fluid/operators/gaussian_random_batch_size_like_op.cc
index 53c706a83e..45064fc416 100644
--- a/paddle/fluid/operators/gaussian_random_batch_size_like_op.cc
+++ b/paddle/fluid/operators/gaussian_random_batch_size_like_op.cc
@@ -33,8 +33,7 @@ class GaussianRandomBatchSizeLikeOp : public BatchSizeLikeOp {
class GaussianRandomBatchSizeLikeOpMaker : public BatchSizeLikeOpMaker {
public:
- GaussianRandomBatchSizeLikeOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : BatchSizeLikeOpMaker(proto, op_checker) {
+ void Make() override {
AddAttr<float>("mean",
"(float, default 0.0) "
"mean of random tensor.")
diff --git a/paddle/fluid/operators/gaussian_random_op.cc b/paddle/fluid/operators/gaussian_random_op.cc
index 4d197637b3..815c1bb509 100644
--- a/paddle/fluid/operators/gaussian_random_op.cc
+++ b/paddle/fluid/operators/gaussian_random_op.cc
@@ -70,8 +70,7 @@ class GaussianRandomOp : public framework::OperatorWithKernel {
class GaussianRandomOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- GaussianRandomOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : framework::OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddOutput("Out", "Output matrix of gaussian random op");
AddAttr<std::vector<int>>("shape",
diff --git a/paddle/fluid/operators/get_places_op.cc b/paddle/fluid/operators/get_places_op.cc
index 0d7219ac5c..eafc364a15 100644
--- a/paddle/fluid/operators/get_places_op.cc
+++ b/paddle/fluid/operators/get_places_op.cc
@@ -78,8 +78,7 @@ class GetPlacesOp : public framework::OperatorBase {
class GetPlacesOpProtoMaker : public framework::OpProtoAndCheckerMaker {
public:
- GetPlacesOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddOutput("Out", "vector of Place");
AddAttr<int>("device_count", "device count").SetDefault(0);
AddAttr<std::string>("device_type", "device type")
diff --git a/paddle/fluid/operators/go_op.cc b/paddle/fluid/operators/go_op.cc
index b8e1556c23..48f9d967ad 100644
--- a/paddle/fluid/operators/go_op.cc
+++ b/paddle/fluid/operators/go_op.cc
@@ -89,8 +89,7 @@ class GoOp : public framework::OperatorBase {
class GoOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- GoOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput(kX,
"A set of variables, which are required by operators inside the "
"block of Go Op.")
diff --git a/paddle/fluid/operators/gru_op.cc b/paddle/fluid/operators/gru_op.cc
index 0a524c914d..5c74687882 100644
--- a/paddle/fluid/operators/gru_op.cc
+++ b/paddle/fluid/operators/gru_op.cc
@@ -71,8 +71,7 @@ class GRUOp : public framework::OperatorWithKernel {
class GRUOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- GRUOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("Input",
"(LoDTensor) The first input is a LodTensor, which supports "
"variable-time length input sequence. The underlying tensor in "
diff --git a/paddle/fluid/operators/gru_unit_op.cc b/paddle/fluid/operators/gru_unit_op.cc
index f8d1d44b54..82a808b01e 100644
--- a/paddle/fluid/operators/gru_unit_op.cc
+++ b/paddle/fluid/operators/gru_unit_op.cc
@@ -71,8 +71,7 @@ class GRUUnitOp : public framework::OperatorWithKernel {
class GRUUnitOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- GRUUnitOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("Input",
"(Tensor) Matrix with shape [batch_size, frame_size * 3] for the "
"input.");
diff --git a/paddle/fluid/operators/hinge_loss_op.cc b/paddle/fluid/operators/hinge_loss_op.cc
index 086b5a97de..69e7fa4490 100644
--- a/paddle/fluid/operators/hinge_loss_op.cc
+++ b/paddle/fluid/operators/hinge_loss_op.cc
@@ -46,8 +46,7 @@ class HingeLossOp : public framework::OperatorWithKernel {
template <typename AttrType>
class HingeLossOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- HingeLossOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("Logits",
"The input value (Logits) of Hinge loss op."
"Logits is a 2-D tensor with shape [batch_size, 1].");
diff --git a/paddle/fluid/operators/huber_loss_op.cc b/paddle/fluid/operators/huber_loss_op.cc
index 74d8e0e2b7..4ecd8634ff 100644
--- a/paddle/fluid/operators/huber_loss_op.cc
+++ b/paddle/fluid/operators/huber_loss_op.cc
@@ -45,8 +45,7 @@ class HuberLossOp : public framework::OperatorWithKernel {
template <typename AttrType>
class HuberLossOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- HuberLossOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X",
"The input value of huber loss op."
"X is a 2-D tensor with shape [batch_size, 1].");
diff --git a/paddle/fluid/operators/im2sequence_op.cc b/paddle/fluid/operators/im2sequence_op.cc
index 8c120eec86..0669661d22 100644
--- a/paddle/fluid/operators/im2sequence_op.cc
+++ b/paddle/fluid/operators/im2sequence_op.cc
@@ -54,8 +54,7 @@ class Im2SequenceOp : public framework::OperatorWithKernel {
class Im2SequenceOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- Im2SequenceOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X",
"(Tensor) The input tensor has NCHW format."
"N: batch size"
diff --git a/paddle/fluid/operators/increment_op.cc b/paddle/fluid/operators/increment_op.cc
index d8c97b27b3..f0ffc97066 100644
--- a/paddle/fluid/operators/increment_op.cc
+++ b/paddle/fluid/operators/increment_op.cc
@@ -47,8 +47,7 @@ class IncrementOp : public framework::OperatorWithKernel {
class IncrementOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- IncrementOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X", "(Tensor) The input tensor of increment operator");
AddOutput("Out", "(Tensor) The output tensor of increment operator.");
AddAttr<float>("step",
diff --git a/paddle/fluid/operators/iou_similarity_op.cc b/paddle/fluid/operators/iou_similarity_op.cc
index 4b78ec510d..007e0af7a5 100644
--- a/paddle/fluid/operators/iou_similarity_op.cc
+++ b/paddle/fluid/operators/iou_similarity_op.cc
@@ -42,8 +42,7 @@ class IOUSimilarityOp : public framework::OperatorWithKernel {
class IOUSimilarityOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- IOUSimilarityOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X",
"(LoDTensor, default LoDTensor<float>) "
"Box list X is a 2-D LoDTensor with shape [N, 4] holds N boxes, "
diff --git a/paddle/fluid/operators/is_empty_op.cc b/paddle/fluid/operators/is_empty_op.cc
index 2a7be90dab..d3f3ad9244 100644
--- a/paddle/fluid/operators/is_empty_op.cc
+++ b/paddle/fluid/operators/is_empty_op.cc
@@ -48,8 +48,7 @@ class IsEmptyOp : public framework::OperatorBase {
class IsEmptyOpProtoMaker : public framework::OpProtoAndCheckerMaker {
public:
- IsEmptyOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput(kInput, "(Tensor) Tensor which is to be checked.");
AddOutput(kOutput, "(Tensor) a boolean Tensor that indicate empty or not.");
AddComment(R"DOC(
diff --git a/paddle/fluid/operators/l1_norm_op.cc b/paddle/fluid/operators/l1_norm_op.cc
index 0c143b7c8a..bc115090ac 100644
--- a/paddle/fluid/operators/l1_norm_op.cc
+++ b/paddle/fluid/operators/l1_norm_op.cc
@@ -48,8 +48,7 @@ class L1NormGradOp : public framework::OperatorWithKernel {
class L1NormOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- L1NormOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : framework::OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X", "(Tensor) The input of l1_norm op.");
AddOutput("Out", "(Scalar) The output of l1_norm op.");
AddComment(R"DOC(
diff --git a/paddle/fluid/operators/label_smooth_op.cc b/paddle/fluid/operators/label_smooth_op.cc
index a73c626032..da59bd53bc 100644
--- a/paddle/fluid/operators/label_smooth_op.cc
+++ b/paddle/fluid/operators/label_smooth_op.cc
@@ -47,8 +47,7 @@ class LabelSmoothOp : public framework::OperatorWithKernel {
class LabelSmoothOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- LabelSmoothOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X",
"(LoDTensor) The input labels of LabelSmooth operator. This "
"input can be batched labels in one-hot encoding or output from "
diff --git a/paddle/fluid/operators/layer_norm_op.cc b/paddle/fluid/operators/layer_norm_op.cc
index de1056aef7..ab097d31e9 100644
--- a/paddle/fluid/operators/layer_norm_op.cc
+++ b/paddle/fluid/operators/layer_norm_op.cc
@@ -61,8 +61,7 @@ class LayerNormOp : public framework::OperatorWithKernel {
class LayerNormOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- LayerNormOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X", "(LoDTensor) The input tensor.");
AddInput("Scale",
"(Tensor, optional) Scale is a 1-dimensional tensor of size "
diff --git a/paddle/fluid/operators/linear_chain_crf_op.cc b/paddle/fluid/operators/linear_chain_crf_op.cc
index 2f29e377fd..e38525cd7f 100644
--- a/paddle/fluid/operators/linear_chain_crf_op.cc
+++ b/paddle/fluid/operators/linear_chain_crf_op.cc
@@ -19,8 +19,7 @@ namespace operators {
class LinearChainCRFOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- LinearChainCRFOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("Emission",
"(LoDTensor, default LoDTensor<float>) "
"A 2-D LoDTensor with shape [N x D], where N is the size of the "
diff --git a/paddle/fluid/operators/listen_and_serv_op.cc b/paddle/fluid/operators/listen_and_serv_op.cc
index 8acbf82025..a29e0cd52c 100644
--- a/paddle/fluid/operators/listen_and_serv_op.cc
+++ b/paddle/fluid/operators/listen_and_serv_op.cc
@@ -343,8 +343,7 @@ void ListenAndServOp::RunImpl(const framework::Scope &scope,
class ListenAndServOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- ListenAndServOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() {
AddInput("X", "(Tensor) Variables that server recv.").AsDuplicable();
AddComment(R"DOC(
ListenAndServ operator
diff --git a/paddle/fluid/operators/load_combine_op.cc b/paddle/fluid/operators/load_combine_op.cc
index e5353144e9..b5522dd246 100644
--- a/paddle/fluid/operators/load_combine_op.cc
+++ b/paddle/fluid/operators/load_combine_op.cc
@@ -77,8 +77,7 @@ class LoadCombineOp : public framework::OperatorBase {
class LoadCombineOpProtoMaker : public framework::OpProtoAndCheckerMaker {
public:
- LoadCombineOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddOutput(
"Out",
"(vector) The output LoDTensors that will be read from the input file.")
diff --git a/paddle/fluid/operators/load_op.cc b/paddle/fluid/operators/load_op.cc
index 6ffe0bec5e..15e6aa8139 100644
--- a/paddle/fluid/operators/load_op.cc
+++ b/paddle/fluid/operators/load_op.cc
@@ -64,8 +64,7 @@ class LoadOp : public framework::OperatorBase {
class LoadOpProtoMaker : public framework::OpProtoAndCheckerMaker {
public:
- LoadOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddOutput("Out", "(Tensor) The tensor need to be loaded");
AddAttr<std::string>("file_path",
"(string) "
diff --git a/paddle/fluid/operators/lod_array_length_op.cc b/paddle/fluid/operators/lod_array_length_op.cc
index e621240577..e4551b8ba6 100644
--- a/paddle/fluid/operators/lod_array_length_op.cc
+++ b/paddle/fluid/operators/lod_array_length_op.cc
@@ -40,8 +40,7 @@ class LoDArrayLengthOp : public framework::OperatorBase {
class LoDArrayLengthProtoMaker : public framework::OpProtoAndCheckerMaker {
public:
- LoDArrayLengthProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X", "(LoDTensorArray) The input tensor array.");
AddOutput("Out", "(Tensor) 1x1 CPU Tensor of length, int64_t");
AddComment(R"DOC(
diff --git a/paddle/fluid/operators/lod_rank_table_op.cc b/paddle/fluid/operators/lod_rank_table_op.cc
index 590b44e14f..166952fe23 100644
--- a/paddle/fluid/operators/lod_rank_table_op.cc
+++ b/paddle/fluid/operators/lod_rank_table_op.cc
@@ -38,8 +38,7 @@ class LoDRankTableOp : public framework::OperatorBase {
class LoDRankTableOpProtoMaker : public framework::OpProtoAndCheckerMaker {
public:
- LoDRankTableOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X",
"(LoDTensor) input lod tensor, must contain lod information.");
AddOutput("Out", "(LoDRankTable) The rank table of specific level.");
diff --git a/paddle/fluid/operators/lod_reset_op.cc b/paddle/fluid/operators/lod_reset_op.cc
index 92ebfc274b..0d4e84e850 100644
--- a/paddle/fluid/operators/lod_reset_op.cc
+++ b/paddle/fluid/operators/lod_reset_op.cc
@@ -47,8 +47,7 @@ class LoDResetOp : public framework::OperatorWithKernel {
class LoDResetOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- LoDResetOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X",
"(Tensor, LoDTensor) Input variable of LoDResetOp which "
"could be a Tensor or LoDTensor, where the data of output "
diff --git a/paddle/fluid/operators/lod_tensor_to_array_op.cc b/paddle/fluid/operators/lod_tensor_to_array_op.cc
index 543495ce4e..00ba5ce8ee 100644
--- a/paddle/fluid/operators/lod_tensor_to_array_op.cc
+++ b/paddle/fluid/operators/lod_tensor_to_array_op.cc
@@ -105,8 +105,7 @@ class LoDTensorToArrayOp : public framework::OperatorBase {
class LoDTensorToArrayOpProtoMaker : public framework::OpProtoAndCheckerMaker {
public:
- LoDTensorToArrayOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X", "");
AddInput("RankTable", "");
AddOutput("Out", "");
diff --git a/paddle/fluid/operators/log_loss_op.cc b/paddle/fluid/operators/log_loss_op.cc
index a8258a1afd..9d248e0321 100644
--- a/paddle/fluid/operators/log_loss_op.cc
+++ b/paddle/fluid/operators/log_loss_op.cc
@@ -46,8 +46,7 @@ class LogLossOp : public framework::OperatorWithKernel {
template <typename AttrType>
class LogLossOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- LogLossOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("Predicted",
"The input value (Predicted) of Log loss op."
"Predicted is a 2-D tensor with shape [batch_size, 1].");
diff --git a/paddle/fluid/operators/logical_op.cc b/paddle/fluid/operators/logical_op.cc
index 41aa00ee8a..db109f5cd0 100644
--- a/paddle/fluid/operators/logical_op.cc
+++ b/paddle/fluid/operators/logical_op.cc
@@ -21,8 +21,7 @@ namespace operators {
template <typename OpComment>
class BinaryLogicalOpProtoMaker : public framework::OpProtoAndCheckerMaker {
public:
- BinaryLogicalOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
OpComment comment;
AddInput("X",
string::Sprintf("(LoDTensor) Left hand operand of %s operator",
@@ -45,8 +44,7 @@ Each element of Out is calculated by %s
template <typename OpComment>
class UnaryLogicalOpProtoMaker : public framework::OpProtoAndCheckerMaker {
public:
- UnaryLogicalOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
OpComment comment;
AddInput("X", string::Sprintf("(LoDTensor) Operand of %s operator",
comment.type));
diff --git a/paddle/fluid/operators/lookup_sparse_table_op.cc b/paddle/fluid/operators/lookup_sparse_table_op.cc
index 66b626ed79..d07a819685 100644
--- a/paddle/fluid/operators/lookup_sparse_table_op.cc
+++ b/paddle/fluid/operators/lookup_sparse_table_op.cc
@@ -105,8 +105,7 @@ class LookupSparseTableOp : public framework::OperatorBase {
class LookupSparseTableOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- LookupSparseTableOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : framework::OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("W",
"(SelectedRows) The input represents embedding table, "
"which is a learnable parameter.");
diff --git a/paddle/fluid/operators/lookup_table_op.cc b/paddle/fluid/operators/lookup_table_op.cc
index 5e59bd1b17..bda4994322 100644
--- a/paddle/fluid/operators/lookup_table_op.cc
+++ b/paddle/fluid/operators/lookup_table_op.cc
@@ -58,8 +58,7 @@ class LookupTableOp : public framework::OperatorWithKernel {
class LookupTableOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- LookupTableOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("W",
"(Tensor) The input represents embedding tensors, "
"which is a learnable parameter.");
diff --git a/paddle/fluid/operators/lrn_op.cc b/paddle/fluid/operators/lrn_op.cc
index f5c0e47fda..52b9cd7fb7 100644
--- a/paddle/fluid/operators/lrn_op.cc
+++ b/paddle/fluid/operators/lrn_op.cc
@@ -169,8 +169,7 @@ class LRNOp : public framework::OperatorWithKernel {
template <typename T>
class LRNOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- LRNOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X",
"(Tensor) The input of LRN operator. "
"It must be a 4D tenor with NCHW format.");
diff --git a/paddle/fluid/operators/lstm_op.cc b/paddle/fluid/operators/lstm_op.cc
index 084ee1cfe6..4751e3e802 100644
--- a/paddle/fluid/operators/lstm_op.cc
+++ b/paddle/fluid/operators/lstm_op.cc
@@ -103,8 +103,7 @@ class LSTMOp : public framework::OperatorWithKernel {
class LSTMOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- LSTMOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("Input",
"(LoDTensor) the first input is a LodTensor, which support "
"variable-time length input sequence. The underlying tensor in "
diff --git a/paddle/fluid/operators/lstm_unit_op.cc b/paddle/fluid/operators/lstm_unit_op.cc
index e1157ef6c6..0895c58f5f 100644
--- a/paddle/fluid/operators/lstm_unit_op.cc
+++ b/paddle/fluid/operators/lstm_unit_op.cc
@@ -48,8 +48,7 @@ class LstmUnitOp : public framework::OperatorWithKernel {
class LstmUnitOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- LstmUnitOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X",
"Lstm unit only applies non-linear activations, please make sure"
"that linear tranformation has already been applied to `X`. "
diff --git a/paddle/fluid/operators/lstmp_op.cc b/paddle/fluid/operators/lstmp_op.cc
index f9261323f0..e398b51480 100644
--- a/paddle/fluid/operators/lstmp_op.cc
+++ b/paddle/fluid/operators/lstmp_op.cc
@@ -120,8 +120,7 @@ class LSTMPOp : public framework::OperatorWithKernel {
class LSTMPOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- LSTMPOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("Input",
"(LoDTensor) the input for sequence data, which supports "
"variable-time length input sequence. The underlying tensor in "
diff --git a/paddle/fluid/operators/margin_rank_loss_op.cc b/paddle/fluid/operators/margin_rank_loss_op.cc
index 0b41a3e1ff..b643ba9d7f 100644
--- a/paddle/fluid/operators/margin_rank_loss_op.cc
+++ b/paddle/fluid/operators/margin_rank_loss_op.cc
@@ -42,8 +42,7 @@ class MarginRankLossOp : public framework::OperatorWithKernel {
template <typename T>
class MarginRankLossOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- MarginRankLossOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X1",
"(2-D tensor with shape [batch_size x 1]) The score for "
"one item X1 to be ranked, from pairwise ranking model.");
diff --git a/paddle/fluid/operators/matmul_op.cc b/paddle/fluid/operators/matmul_op.cc
index e5d33fbc36..1888f610ae 100644
--- a/paddle/fluid/operators/matmul_op.cc
+++ b/paddle/fluid/operators/matmul_op.cc
@@ -159,8 +159,7 @@ class MatMulOp : public framework::OperatorWithKernel {
class MatMulOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- MatMulOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X", "The first input of MatMul op");
AddInput("Y", "The second input of MatMul op");
AddOutput("Out", "The output of MatMul op");
diff --git a/paddle/fluid/operators/max_sequence_len_op.cc b/paddle/fluid/operators/max_sequence_len_op.cc
index 4cd7c89b48..8e508b68ee 100644
--- a/paddle/fluid/operators/max_sequence_len_op.cc
+++ b/paddle/fluid/operators/max_sequence_len_op.cc
@@ -41,8 +41,7 @@ class MaxSeqenceLenOp : public framework::OperatorBase {
class MaxSeqenceLenOpProtoMaker : public framework::OpProtoAndCheckerMaker {
public:
- MaxSeqenceLenOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("RankTable", "The lod_rank_table.");
AddOutput("Out", "The max sequence length.");
AddComment(
diff --git a/paddle/fluid/operators/maxout_op.cc b/paddle/fluid/operators/maxout_op.cc
index e2bcba5a5e..058115cb62 100644
--- a/paddle/fluid/operators/maxout_op.cc
+++ b/paddle/fluid/operators/maxout_op.cc
@@ -22,8 +22,7 @@ using framework::Tensor;
class MaxOutOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- MaxOutOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput(
"X",
"(Tensor) The input tensor of maxout operator. "
diff --git a/paddle/fluid/operators/mean_op.cc b/paddle/fluid/operators/mean_op.cc
index a134796bfc..74477eb439 100644
--- a/paddle/fluid/operators/mean_op.cc
+++ b/paddle/fluid/operators/mean_op.cc
@@ -32,8 +32,7 @@ class MeanOp : public framework::OperatorWithKernel {
class MeanOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- MeanOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X", "The input of mean op");
AddOutput("Out", "The output of mean op");
AddComment(R"DOC(
diff --git a/paddle/fluid/operators/merge_lod_tensor_op.cc b/paddle/fluid/operators/merge_lod_tensor_op.cc
index 4ebf20cbba..a16861b3b7 100644
--- a/paddle/fluid/operators/merge_lod_tensor_op.cc
+++ b/paddle/fluid/operators/merge_lod_tensor_op.cc
@@ -121,8 +121,7 @@ class MergeLoDTensorOp : public framework::OperatorBase {
class MergeLoDTensorOpProtoMaker : public framework::OpProtoAndCheckerMaker {
public:
- MergeLoDTensorOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X",
"The input LoDTensor, contains complete lod information to "
"construct the output");
diff --git a/paddle/fluid/operators/mine_hard_examples_op.cc b/paddle/fluid/operators/mine_hard_examples_op.cc
index 277901cff4..d4a09bae3a 100644
--- a/paddle/fluid/operators/mine_hard_examples_op.cc
+++ b/paddle/fluid/operators/mine_hard_examples_op.cc
@@ -253,8 +253,7 @@ class MineHardExamplesOp : public framework::OperatorWithKernel {
class MineHardExamplesOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- MineHardExamplesOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput(
"ClsLoss",
"(Tensor, default Tensor<float>), The classification loss with shape "
diff --git a/paddle/fluid/operators/minus_op.cc b/paddle/fluid/operators/minus_op.cc
index a302b24560..34571a38a1 100644
--- a/paddle/fluid/operators/minus_op.cc
+++ b/paddle/fluid/operators/minus_op.cc
@@ -48,8 +48,7 @@ class MinusOp : public framework::OperatorWithKernel {
class MinusOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- MinusOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X", "The left tensor of minus operator.");
AddInput("Y", "The right tensor of minus operator.");
AddOutput("Out", "The output tensor of minus operator.");
diff --git a/paddle/fluid/operators/modified_huber_loss_op.cc b/paddle/fluid/operators/modified_huber_loss_op.cc
index 3a0fc74584..35db4c1ad1 100644
--- a/paddle/fluid/operators/modified_huber_loss_op.cc
+++ b/paddle/fluid/operators/modified_huber_loss_op.cc
@@ -39,8 +39,7 @@ class ModifiedHuberLossOp : public framework::OperatorWithKernel {
class ModifiedHuberLossOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- ModifiedHuberLossOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X",
"The input tensor of modified huber loss op. "
"X is 2-D tensor with shape [batch_size, 1].");
diff --git a/paddle/fluid/operators/momentum_op.cc b/paddle/fluid/operators/momentum_op.cc
index f13ec53905..dcd73e3c3e 100644
--- a/paddle/fluid/operators/momentum_op.cc
+++ b/paddle/fluid/operators/momentum_op.cc
@@ -62,8 +62,7 @@ class MomentumOp : public framework::OperatorWithKernel {
class MomentumOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- MomentumOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("Param",
"(Tensor, default Tensor<float>) "
"Input parameter that has to be updated");
diff --git a/paddle/fluid/operators/mul_op.cc b/paddle/fluid/operators/mul_op.cc
index 6903cf83b4..a43739463c 100644
--- a/paddle/fluid/operators/mul_op.cc
+++ b/paddle/fluid/operators/mul_op.cc
@@ -96,8 +96,7 @@ class MulOp : public framework::OperatorWithKernel {
class MulOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- MulOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X", "(Tensor), The first input tensor of mul op.");
AddInput("Y", "(Tensor), The second input tensor of mul op.");
AddOutput("Out", "(Tensor), The output tensor of mul op.");
diff --git a/paddle/fluid/operators/multiclass_nms_op.cc b/paddle/fluid/operators/multiclass_nms_op.cc
index a12b975326..60b93efdce 100644
--- a/paddle/fluid/operators/multiclass_nms_op.cc
+++ b/paddle/fluid/operators/multiclass_nms_op.cc
@@ -309,8 +309,7 @@ class MultiClassNMSKernel : public framework::OpKernel<T> {
class MultiClassNMSOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- MultiClassNMSOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("BBoxes",
"(Tensor) A 3-D Tensor with shape [N, M, 4] represents the "
"predicted locations of M bounding bboxes, N is the batch size. "
diff --git a/paddle/fluid/operators/multiplex_op.cc b/paddle/fluid/operators/multiplex_op.cc
index b698c1bf8a..a4363fd25d 100644
--- a/paddle/fluid/operators/multiplex_op.cc
+++ b/paddle/fluid/operators/multiplex_op.cc
@@ -61,8 +61,7 @@ class MultiplexOp : public framework::OperatorWithKernel {
class MultiplexOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- MultiplexOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("Ids", "The index tensor of multiplex operator.");
AddInput("X", "The candidate tensors of multiplex operator.")
.AsDuplicable();
diff --git a/paddle/fluid/operators/nccl_op.cc b/paddle/fluid/operators/nccl_op.cc
index 5e4ed886b1..0018139cb0 100644
--- a/paddle/fluid/operators/nccl_op.cc
+++ b/paddle/fluid/operators/nccl_op.cc
@@ -76,8 +76,7 @@ class NCCLInitOpShapeInference : public framework::InferShapeBase {
class NCCLInitOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- NCCLInitOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput(kParallelScopes, "The working place of parallel do.");
AddOutput("Communicator",
"Create Communicator for communicating between gpus");
@@ -118,8 +117,7 @@ class NCCLAllReduceOp : public framework::OperatorWithKernel {
// AllReduceOp
class NCCLAllReduceOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- NCCLAllReduceOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X", "The input of AllReduce op");
AddInput("Communicator", "Communicator for communicating between gpus");
AddOutput("Out", "The output of AllReduce op");
@@ -165,8 +163,7 @@ class NCCLReduceOp : public framework::OperatorWithKernel {
// ReduceOp
class NCCLReduceOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- NCCLReduceOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X", "The input of Reduce op");
AddInput("Communicator", "Communicator for communicating between gpus");
AddOutput("Out", "The output of Reduce op");
@@ -214,8 +211,7 @@ class NCCLBcastOp : public framework::OperatorWithKernel {
// BcastOp
class NCCLBcastOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- NCCLBcastOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X", "The input of BcastSend op");
AddInput("Communicator", "Communicator for communicating between gpus");
AddOutput("Out", "The output of Bcast");
diff --git a/paddle/fluid/operators/nce_op.cc b/paddle/fluid/operators/nce_op.cc
index 192bdf8ea5..06092e680a 100644
--- a/paddle/fluid/operators/nce_op.cc
+++ b/paddle/fluid/operators/nce_op.cc
@@ -75,8 +75,7 @@ class NCEOp : public framework::OperatorWithKernel {
class NCEOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- NCEOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("Input", "(Tensor) A tensor of shape [batch_size, dim].");
AddInput(
"Label",
diff --git a/paddle/fluid/operators/norm_op.cc b/paddle/fluid/operators/norm_op.cc
index 30a991224f..cdbc975c02 100644
--- a/paddle/fluid/operators/norm_op.cc
+++ b/paddle/fluid/operators/norm_op.cc
@@ -19,8 +19,7 @@ namespace operators {
template <typename AttrType>
class NormOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- NormOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput(
"X",
"(Tensor) The input tensor of norm operator. "
diff --git a/paddle/fluid/operators/one_hot_op.cc b/paddle/fluid/operators/one_hot_op.cc
index 1d42dfdd76..4fcb1d6993 100644
--- a/paddle/fluid/operators/one_hot_op.cc
+++ b/paddle/fluid/operators/one_hot_op.cc
@@ -46,8 +46,7 @@ class OneHotOp : public framework::OperatorWithKernel {
class OneHotOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- OneHotOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X",
"(LoDTensor, LoDTensor<int>) Input variable with rank at least 2. "
"The last dimension of X should be 1. Each value of X is an index "
diff --git a/paddle/fluid/operators/pad_op.cc b/paddle/fluid/operators/pad_op.cc
index d2a0106f80..d4b631a6f5 100644
--- a/paddle/fluid/operators/pad_op.cc
+++ b/paddle/fluid/operators/pad_op.cc
@@ -48,8 +48,7 @@ class PadOp : public framework::OperatorWithKernel {
class PadOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- PadOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X",
"The input of pad op. "
"The input should be a k-D tensor(k > 0 and k < 7)");
diff --git a/paddle/fluid/operators/parallel_do_op.cc b/paddle/fluid/operators/parallel_do_op.cc
index ae34fe2184..1012640d5e 100644
--- a/paddle/fluid/operators/parallel_do_op.cc
+++ b/paddle/fluid/operators/parallel_do_op.cc
@@ -196,8 +196,7 @@ class ParallelDoOp : public framework::OperatorBase {
class ParallelDoOpProtoMaker : public framework::OpProtoAndCheckerMaker {
public:
- ParallelDoOpProtoMaker(OpProto *proto, framework::OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput(kInputs, "").AsDuplicable();
AddInput(kParameters, "").AsDuplicable();
AddInput(kPlaces, "");
diff --git a/paddle/fluid/operators/pool_op.cc b/paddle/fluid/operators/pool_op.cc
index f2de075e0d..f4fb2b132f 100644
--- a/paddle/fluid/operators/pool_op.cc
+++ b/paddle/fluid/operators/pool_op.cc
@@ -135,8 +135,7 @@ framework::OpKernelType PoolOpGrad::GetExpectedKernelType(
library_);
}
-Pool2dOpMaker::Pool2dOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+void Pool2dOpMaker::Make() {
AddInput(
"X",
"(Tensor) The input tensor of pooling operator. "
@@ -229,8 +228,7 @@ Example:
)DOC");
}
-Pool3dOpMaker::Pool3dOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+void Pool3dOpMaker::Make() {
AddInput("X",
"(Tensor) The input tensor of pooling operator. "
"The format of input tensor is NCDHW, where N is batch size, C is "
diff --git a/paddle/fluid/operators/pool_op.h b/paddle/fluid/operators/pool_op.h
index a48127ea69..a63963ca92 100644
--- a/paddle/fluid/operators/pool_op.h
+++ b/paddle/fluid/operators/pool_op.h
@@ -50,12 +50,12 @@ class PoolOpGrad : public framework::OperatorWithKernel {
class Pool2dOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- Pool2dOpMaker(OpProto* proto, OpAttrChecker* op_checker);
+ void Make() override;
};
class Pool3dOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- Pool3dOpMaker(OpProto* proto, OpAttrChecker* op_checker);
+ void Make() override;
};
template <typename DeviceContext, typename T>
diff --git a/paddle/fluid/operators/pool_with_index_op.cc b/paddle/fluid/operators/pool_with_index_op.cc
index 848cd61b23..873706593e 100644
--- a/paddle/fluid/operators/pool_with_index_op.cc
+++ b/paddle/fluid/operators/pool_with_index_op.cc
@@ -100,8 +100,7 @@ class MaxPoolWithIndexOpGrad : public framework::OperatorWithKernel {
class MaxPool2dWithIndexOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- MaxPool2dWithIndexOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput(
"X",
"(Tensor) The input tensor of pooling operator. "
@@ -177,8 +176,7 @@ Example:
class MaxPool3dWithIndexOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- MaxPool3dWithIndexOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X",
"(Tensor) The input tensor of pooling operator. "
"The format of input tensor is NCDHW, where N is batch size, C is "
diff --git a/paddle/fluid/operators/positive_negative_pair_op.cc b/paddle/fluid/operators/positive_negative_pair_op.cc
index d237da25a0..4d865b7f17 100644
--- a/paddle/fluid/operators/positive_negative_pair_op.cc
+++ b/paddle/fluid/operators/positive_negative_pair_op.cc
@@ -95,8 +95,7 @@ class PositiveNegativePairOp : public framework::OperatorWithKernel {
class PositiveNegativePairOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- PositiveNegativePairOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("Score",
"(Tensor, float) Model Score on an item (with "
"respect to QueryID). It's a 2-D tensor with shape [batch_size, "
diff --git a/paddle/fluid/operators/precision_recall_op.cc b/paddle/fluid/operators/precision_recall_op.cc
index c34b0d072b..e7ce16f33f 100644
--- a/paddle/fluid/operators/precision_recall_op.cc
+++ b/paddle/fluid/operators/precision_recall_op.cc
@@ -90,8 +90,7 @@ class PrecisionRecallOp : public framework::OperatorWithKernel {
class PrecisionRecallOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- PrecisionRecallOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("MaxProbs",
"(Tensor, default Tensor<float>) A 2-D tensor with shape N x 1, "
"where N is the batch size. Each row contains the max probability "
diff --git a/paddle/fluid/operators/prefetch_op.cc b/paddle/fluid/operators/prefetch_op.cc
index f9ae01ab5d..4cfea958e8 100644
--- a/paddle/fluid/operators/prefetch_op.cc
+++ b/paddle/fluid/operators/prefetch_op.cc
@@ -64,8 +64,7 @@ class PrefetchOp : public framework::OperatorBase {
class PrefetchOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- PrefetchOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() {
AddInput("X", "(LoDTensor) Input Id variables to be sent").AsDuplicable();
AddOutput("RPCClient",
"(RPCClient) The RPC client object which will be"
diff --git a/paddle/fluid/operators/prelu_op.cc b/paddle/fluid/operators/prelu_op.cc
index a066b3e06e..db040509bc 100644
--- a/paddle/fluid/operators/prelu_op.cc
+++ b/paddle/fluid/operators/prelu_op.cc
@@ -38,8 +38,7 @@ class PReluOp : public framework::OperatorWithKernel {
class PReluOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- PReluOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X", "The input tensor of prelu operator.");
AddInput("Alpha", "The alpha weight of prelu operator.");
AddOutput("Out", "The output tensor of prelu operator.");
diff --git a/paddle/fluid/operators/print_op.cc b/paddle/fluid/operators/print_op.cc
index fafc7e54d7..db7634918a 100644
--- a/paddle/fluid/operators/print_op.cc
+++ b/paddle/fluid/operators/print_op.cc
@@ -209,8 +209,7 @@ class TensorPrintOp : public framework::OperatorBase {
class PrintOpProtoAndCheckMaker : public framework::OpProtoAndCheckerMaker {
public:
- PrintOpProtoAndCheckMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("In", "Input tensor to be displayed.");
AddAttr<int>("first_n", "Only log `first_n` number of times.");
AddAttr<std::string>("message", "A string message to print as a prefix.");
diff --git a/paddle/fluid/operators/prior_box_op.cc b/paddle/fluid/operators/prior_box_op.cc
index 058b13eeb8..a0b069da0d 100644
--- a/paddle/fluid/operators/prior_box_op.cc
+++ b/paddle/fluid/operators/prior_box_op.cc
@@ -79,8 +79,7 @@ class PriorBoxOp : public framework::OperatorWithKernel {
class PriorBoxOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- PriorBoxOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("Input",
"(Tensor, default Tensor<float>), "
"the input feature data of PriorBoxOp, The layout is NCHW.");
diff --git a/paddle/fluid/operators/proximal_adagrad_op.cc b/paddle/fluid/operators/proximal_adagrad_op.cc
index e057244c1e..8d8075d761 100644
--- a/paddle/fluid/operators/proximal_adagrad_op.cc
+++ b/paddle/fluid/operators/proximal_adagrad_op.cc
@@ -66,8 +66,7 @@ class ProximalAdagradOp : public framework::OperatorWithKernel {
class ProximalAdagradOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- ProximalAdagradOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("Param",
"(Tensor, default Tensor<float>) "
"Input parameter that has to be updated.");
diff --git a/paddle/fluid/operators/proximal_gd_op.cc b/paddle/fluid/operators/proximal_gd_op.cc
index ed14726318..baf9cbcba2 100644
--- a/paddle/fluid/operators/proximal_gd_op.cc
+++ b/paddle/fluid/operators/proximal_gd_op.cc
@@ -54,8 +54,7 @@ class ProximalGDOp : public framework::OperatorWithKernel {
class ProximalGDOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- ProximalGDOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("Param",
"(Tensor, default Tensor<float>) "
"Input parameter value that has to be updated.");
diff --git a/paddle/fluid/operators/rank_loss_op.cc b/paddle/fluid/operators/rank_loss_op.cc
index eb9ff8de3e..313cf01541 100644
--- a/paddle/fluid/operators/rank_loss_op.cc
+++ b/paddle/fluid/operators/rank_loss_op.cc
@@ -46,8 +46,7 @@ class RankLossOp : public framework::OperatorWithKernel {
class RankLossOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- RankLossOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("Label",
"(2-D Tensor with shape [batch_size x 1]) "
"The label indicating A ranked higher than B or not.");
diff --git a/paddle/fluid/operators/read_op.cc b/paddle/fluid/operators/read_op.cc
index bf02b99589..72a27d4358 100644
--- a/paddle/fluid/operators/read_op.cc
+++ b/paddle/fluid/operators/read_op.cc
@@ -79,8 +79,7 @@ class ReadOp : public framework::OperatorBase {
class ReadOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- ReadOpMaker(OpProto* op_proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(op_proto, op_checker) {
+ void Make() override {
AddInput("Reader", "(ReaderHolder) The executed reader.");
AddOutput("Out", "(LoDTensor) The output data.").AsDuplicable();
AddComment(R"DOC(
diff --git a/paddle/fluid/operators/reader/create_batch_reader_op.cc b/paddle/fluid/operators/reader/create_batch_reader_op.cc
index 04c5872bef..4cc7cbc6e8 100644
--- a/paddle/fluid/operators/reader/create_batch_reader_op.cc
+++ b/paddle/fluid/operators/reader/create_batch_reader_op.cc
@@ -52,9 +52,8 @@ class CreateBatchReaderOp : public framework::OperatorBase {
};
class CreateBatchReaderOpMaker : public DecoratedReaderMakerBase {
- public:
- CreateBatchReaderOpMaker(OpProto* op_proto, OpAttrChecker* op_checker)
- : DecoratedReaderMakerBase(op_proto, op_checker) {
+ protected:
+ void Apply() override {
AddAttr<int>("batch_size",
"How many instances the batch reader yields each time.")
.GreaterThan(0);
diff --git a/paddle/fluid/operators/reader/create_double_buffer_reader_op.cc b/paddle/fluid/operators/reader/create_double_buffer_reader_op.cc
index e5efac4615..bc830a2b72 100644
--- a/paddle/fluid/operators/reader/create_double_buffer_reader_op.cc
+++ b/paddle/fluid/operators/reader/create_double_buffer_reader_op.cc
@@ -113,14 +113,13 @@ class CreateDoubleBufferReaderOp : public framework::OperatorBase {
};
class CreateDoubleBufferReaderOpMaker : public DecoratedReaderMakerBase {
- public:
- CreateDoubleBufferReaderOpMaker(OpProto* op_proto, OpAttrChecker* op_checker)
- : DecoratedReaderMakerBase(op_proto, op_checker) {
+ protected:
+ void Apply() override {
AddComment(R"DOC(
CreateDoubleBufferReader Operator
A double buffer reader takes another reader as its 'underlying reader'.
- It launches another thread to execute the 'underlying reader' asynchronously,
+ It launches another thread to execute the 'underlying reader' asynchronously,
which prevents reading process from blocking subsequent training.
)DOC");
std::unordered_set<std::string> enum_range;
diff --git a/paddle/fluid/operators/reader/create_multi_pass_reader_op.cc b/paddle/fluid/operators/reader/create_multi_pass_reader_op.cc
index 0573345ba5..249b0b7c6d 100644
--- a/paddle/fluid/operators/reader/create_multi_pass_reader_op.cc
+++ b/paddle/fluid/operators/reader/create_multi_pass_reader_op.cc
@@ -65,20 +65,19 @@ class CreateMultiPassReaderOp : public framework::OperatorBase {
};
class CreateMultiPassReaderOpMaker : public DecoratedReaderMakerBase {
- public:
- CreateMultiPassReaderOpMaker(OpProto* op_proto, OpAttrChecker* op_checker)
- : DecoratedReaderMakerBase(op_proto, op_checker) {
+ protected:
+ void Apply() override {
AddAttr<int>("pass_num", "The number of pass to run.").GreaterThan(0);
AddComment(R"DOC(
CreateMultiPassReader Operator
- This operator creates a multi-pass reader. A multi-pass reader
- is used to yield data for several pass training continuously.
+ This operator creates a multi-pass reader. A multi-pass reader
+ is used to yield data for several pass training continuously.
It takes the number of passes to run as one of its attributes
- ('pass_num'), and maintains a pass counter to record how many
- passes it has completed. When the underlying reader reaches the
- EOF, the multi-pass reader checks whether it has completed training
- of the given number of pass. If not, the underlying reader will
+ ('pass_num'), and maintains a pass counter to record how many
+ passes it has completed. When the underlying reader reaches the
+ EOF, the multi-pass reader checks whether it has completed training
+ of the given number of pass. If not, the underlying reader will
be re-initialized and starts a new pass automatically.
)DOC");
}
diff --git a/paddle/fluid/operators/reader/create_random_data_generator_op.cc b/paddle/fluid/operators/reader/create_random_data_generator_op.cc
index d1cb8e47da..55bb9739e0 100644
--- a/paddle/fluid/operators/reader/create_random_data_generator_op.cc
+++ b/paddle/fluid/operators/reader/create_random_data_generator_op.cc
@@ -84,9 +84,8 @@ class CreateRandomDataGeneratorOp : public framework::OperatorBase {
};
class CreateRandomDataGeneratorOpMaker : public FileReaderMakerBase {
- public:
- CreateRandomDataGeneratorOpMaker(OpProto* op_proto, OpAttrChecker* op_checker)
- : FileReaderMakerBase(op_proto, op_checker) {
+ protected:
+ void Apply() override {
AddAttr<float>("min", "The lower bound of reader's uniform distribution.");
AddAttr<float>("max", "The upper bound of reader's uniform distribution.");
AddComment(R"DOC(
diff --git a/paddle/fluid/operators/reader/create_recordio_file_reader_op.cc b/paddle/fluid/operators/reader/create_recordio_file_reader_op.cc
index 2ae2972556..282ec3f36b 100644
--- a/paddle/fluid/operators/reader/create_recordio_file_reader_op.cc
+++ b/paddle/fluid/operators/reader/create_recordio_file_reader_op.cc
@@ -76,9 +76,8 @@ class CreateRecordIOReaderOp : public framework::OperatorBase {
};
class CreateRecordIOReaderOpMaker : public FileReaderMakerBase {
- public:
- CreateRecordIOReaderOpMaker(OpProto* op_proto, OpAttrChecker* op_checker)
- : FileReaderMakerBase(op_proto, op_checker) {
+ protected:
+ void Apply() override {
AddAttr<std::string>("filename", "The filename of record io reader");
AddComment(R"DOC(
CreateRecordIOReader Operator
diff --git a/paddle/fluid/operators/reader/create_shuffle_reader_op.cc b/paddle/fluid/operators/reader/create_shuffle_reader_op.cc
index 13825d6591..fd233be945 100644
--- a/paddle/fluid/operators/reader/create_shuffle_reader_op.cc
+++ b/paddle/fluid/operators/reader/create_shuffle_reader_op.cc
@@ -92,9 +92,8 @@ class CreateShuffleReaderOp : public framework::OperatorBase {
};
class CreateShuffleReaderOpMaker : public DecoratedReaderMakerBase {
- public:
- CreateShuffleReaderOpMaker(OpProto* op_proto, OpAttrChecker* op_checker)
- : DecoratedReaderMakerBase(op_proto, op_checker) {
+ protected:
+ void Apply() override {
AddAttr<int>("buffer_size", "The shuffle buffer size.").GreaterThan(0);
AddComment(R"DOC(
CreateShuffleReader Operator
diff --git a/paddle/fluid/operators/reader/create_threaded_reader_op.cc b/paddle/fluid/operators/reader/create_threaded_reader_op.cc
index 1cb9bd3645..1db70f3e96 100644
--- a/paddle/fluid/operators/reader/create_threaded_reader_op.cc
+++ b/paddle/fluid/operators/reader/create_threaded_reader_op.cc
@@ -53,17 +53,16 @@ class CreateThreadedReaderOp : public framework::OperatorBase {
};
class CreateThreadedReaderOpMaker : public DecoratedReaderMakerBase {
- public:
- CreateThreadedReaderOpMaker(OpProto* op_proto, OpAttrChecker* op_checker)
- : DecoratedReaderMakerBase(op_proto, op_checker) {
+ protected:
+ void Apply() override {
AddComment(R"DOC(
CreateThreadedReader Operator
- This operator creates a threaded reader. A threaded reader's
- 'ReadNext()' can be invoked by several threads at the same
- time.
- When the attribute 'safe_mode' is true, the threaded reader's
- 'ReInit()' is disabled to avoid unexpected bugs in multi-thread
+ This operator creates a threaded reader. A threaded reader's
+ 'ReadNext()' can be invoked by several threads at the same
+ time.
+ When the attribute 'safe_mode' is true, the threaded reader's
+ 'ReInit()' is disabled to avoid unexpected bugs in multi-thread
environment.
)DOC");
}
diff --git a/paddle/fluid/operators/reader/open_files_op.cc b/paddle/fluid/operators/reader/open_files_op.cc
index 91ad7d5658..8c0dac65dd 100644
--- a/paddle/fluid/operators/reader/open_files_op.cc
+++ b/paddle/fluid/operators/reader/open_files_op.cc
@@ -185,9 +185,8 @@ class OpenFilesOp : public framework::OperatorBase {
};
class OpenFilesOpMaker : public FileReaderMakerBase {
- public:
- OpenFilesOpMaker(OpProto* op_proto, OpAttrChecker* op_checker)
- : FileReaderMakerBase(op_proto, op_checker) {
+ protected:
+ void Apply() override {
AddAttr<std::vector<std::string>>("file_names", "Files to be read.");
AddAttr<int>("thread_num", "The maximal concurrent prefetch thread number.")
.GreaterThan(0);
@@ -196,7 +195,7 @@ class OpenFilesOpMaker : public FileReaderMakerBase {
AddComment(R"DOC(
OpenFiles Operator
- An OpenFilesOp creates a MultiFileReader, which is able to
+ An OpenFilesOp creates a MultiFileReader, which is able to
read data multi-threaded from multiple files.
)DOC");
}
diff --git a/paddle/fluid/operators/reader/reader_op_registry.cc b/paddle/fluid/operators/reader/reader_op_registry.cc
index 3ff4536819..11f1ddebc4 100644
--- a/paddle/fluid/operators/reader/reader_op_registry.cc
+++ b/paddle/fluid/operators/reader/reader_op_registry.cc
@@ -53,10 +53,7 @@ std::unique_ptr<framework::ReaderBase> CreateReaderByFileName(
return std::unique_ptr<framework::ReaderBase>(reader);
}
-FileReaderMakerBase::FileReaderMakerBase(
- framework::OpProtoAndCheckerMaker::OpProto* op_proto,
- framework::OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(op_proto, op_checker) {
+void FileReaderMakerBase::Make() {
AddOutput("Out", "(ReaderHolder) The created random reader.").AsDuplicable();
AddAttr<std::vector<int>>("shape_concat", "The concat of all data's shapes.");
AddAttr<std::vector<int>>(
@@ -68,6 +65,7 @@ FileReaderMakerBase::FileReaderMakerBase(
"It means the reader will generate two data each time,"
"whose shapes are [2,3,4] and [5,6] respectively.");
AddAttr<std::vector<int>>("lod_levels", "The LoD levels of each data.");
+ Apply();
}
void FileReaderInferShape::operator()(framework::InferShapeContext* ctx) const {
@@ -127,13 +125,11 @@ void DecoratedReaderInferVarType::operator()(
out_reader->SetDataTypes(in_reader->GetDataTypes());
}
-DecoratedReaderMakerBase::DecoratedReaderMakerBase(
- framework::OpProtoAndCheckerMaker::OpProto* op_proto,
- framework::OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(op_proto, op_checker) {
+void DecoratedReaderMakerBase::Make() {
AddInput("UnderlyingReader",
"(ReaderHolder) The underlying reader for creating a batch reader.");
AddOutput("Out", "(ReaderHolder) The created batch reader.");
+ Apply();
}
} // namespace reader
diff --git a/paddle/fluid/operators/reader/reader_op_registry.h b/paddle/fluid/operators/reader/reader_op_registry.h
index ec25f55ef5..244bf15f06 100644
--- a/paddle/fluid/operators/reader/reader_op_registry.h
+++ b/paddle/fluid/operators/reader/reader_op_registry.h
@@ -47,7 +47,10 @@ extern std::vector<framework::DDim> RestoreShapes(
class FileReaderMakerBase : public framework::OpProtoAndCheckerMaker {
public:
- FileReaderMakerBase(OpProto* op_proto, OpAttrChecker* op_checker);
+ void Make() final;
+
+ protected:
+ virtual void Apply() = 0;
};
class FileReaderInferShape : public framework::InferShapeBase {
@@ -76,7 +79,10 @@ class DecoratedReaderInferVarType : public framework::VarTypeInference {
class DecoratedReaderMakerBase : public framework::OpProtoAndCheckerMaker {
public:
- DecoratedReaderMakerBase(OpProto* op_proto, OpAttrChecker* op_checker);
+ void Make() final;
+
+ protected:
+ virtual void Apply() = 0;
};
} // namespace reader
diff --git a/paddle/fluid/operators/recurrent_op.cc b/paddle/fluid/operators/recurrent_op.cc
index 72c2905872..9c1cee7022 100644
--- a/paddle/fluid/operators/recurrent_op.cc
+++ b/paddle/fluid/operators/recurrent_op.cc
@@ -508,8 +508,7 @@ class RecurrentGradOp : public RecurrentBase {
class RecurrentOpProtoMaker : public framework::OpProtoAndCheckerMaker {
public:
- RecurrentOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput(kInputs, "rnn inputs").AsDuplicable();
AddInput(kInitialStates, "rnn initial states").AsDuplicable();
AddInput(kParameters,
diff --git a/paddle/fluid/operators/recv_op.cc b/paddle/fluid/operators/recv_op.cc
index a4dcf704a6..7148bd0e36 100644
--- a/paddle/fluid/operators/recv_op.cc
+++ b/paddle/fluid/operators/recv_op.cc
@@ -53,8 +53,7 @@ class RecvOp : public framework::OperatorBase {
class RecvOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- RecvOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() {
AddOutput("Out", "(Tensor) Variables to get from server.").AsDuplicable();
AddComment(R"DOC(
Recv operator
diff --git a/paddle/fluid/operators/reduce_op.cc b/paddle/fluid/operators/reduce_op.cc
index 093db96647..eb8c21179d 100644
--- a/paddle/fluid/operators/reduce_op.cc
+++ b/paddle/fluid/operators/reduce_op.cc
@@ -90,8 +90,7 @@ class ReduceGradOp : public framework::OperatorWithKernel {
class ReduceOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- ReduceOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() final {
AddInput("X",
"(Tensor) The input tensor. Tensors with rank at most 6 are "
"supported.");
@@ -111,78 +110,20 @@ class ReduceOpMaker : public framework::OpProtoAndCheckerMaker {
"(bool, default false) "
"If true, output a scalar reduced along all dimensions.")
.SetDefault(false);
- comment_ = R"DOC(
-{ReduceOp} Operator.
+ AddComment(string::Sprintf(R"DOC(
+%s Operator.
-This operator computes the {reduce} of input tensor along the given dimension.
+This operator computes the %s of input tensor along the given dimension.
The result tensor has 1 fewer dimension than the input unless keep_dim is true.
If reduce_all is true, just reduce along all dimensions and output a scalar.
-)DOC";
- AddComment(comment_);
+)DOC",
+ GetOpType(), GetName()));
}
protected:
- std::string comment_;
-
- void Replace(std::string *src, std::string from, std::string to) {
- std::size_t len_from = std::strlen(from.c_str());
- std::size_t len_to = std::strlen(to.c_str());
- for (std::size_t pos = src->find(from); pos != std::string::npos;
- pos = src->find(from, pos + len_to)) {
- src->replace(pos, len_from, to);
- }
- }
-
- void SetComment(std::string name, std::string op) {
- Replace(&comment_, "{ReduceOp}", name);
- Replace(&comment_, "{reduce}", op);
- }
-};
-
-class ReduceSumOpMaker : public ReduceOpMaker {
- public:
- ReduceSumOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : ReduceOpMaker(proto, op_checker) {
- SetComment("ReduceSum", "sum");
- AddComment(comment_);
- }
-};
-
-class ReduceMeanOpMaker : public ReduceOpMaker {
- public:
- ReduceMeanOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : ReduceOpMaker(proto, op_checker) {
- SetComment("ReduceMean", "mean");
- AddComment(comment_);
- }
-};
-
-class ReduceMaxOpMaker : public ReduceOpMaker {
- public:
- ReduceMaxOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : ReduceOpMaker(proto, op_checker) {
- SetComment("ReduceMax", "max");
- AddComment(comment_);
- }
-};
-
-class ReduceMinOpMaker : public ReduceOpMaker {
- public:
- ReduceMinOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : ReduceOpMaker(proto, op_checker) {
- SetComment("ReduceMin", "min");
- AddComment(comment_);
- }
-};
-
-class ReduceProdOpMaker : public ReduceOpMaker {
- public:
- ReduceProdOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : ReduceOpMaker(proto, op_checker) {
- SetComment("ReduceProd", "production");
- AddComment(comment_);
- }
+ virtual std::string GetName() const = 0;
+ virtual std::string GetOpType() const = 0;
};
} // namespace operators
@@ -190,25 +131,21 @@ class ReduceProdOpMaker : public ReduceOpMaker {
namespace ops = paddle::operators;
-REGISTER_OPERATOR(reduce_sum, ops::ReduceOp, ops::ReduceSumOpMaker,
- paddle::framework::DefaultGradOpDescMaker<true>);
-REGISTER_OPERATOR(reduce_sum_grad, ops::ReduceGradOp);
-
-REGISTER_OPERATOR(reduce_mean, ops::ReduceOp, ops::ReduceMeanOpMaker,
- paddle::framework::DefaultGradOpDescMaker<true>);
-REGISTER_OPERATOR(reduce_mean_grad, ops::ReduceGradOp);
-
-REGISTER_OPERATOR(reduce_max, ops::ReduceOp, ops::ReduceMaxOpMaker,
- paddle::framework::DefaultGradOpDescMaker<true>);
-REGISTER_OPERATOR(reduce_max_grad, ops::ReduceGradOp);
-
-REGISTER_OPERATOR(reduce_min, ops::ReduceOp, ops::ReduceMinOpMaker,
- paddle::framework::DefaultGradOpDescMaker<true>);
-REGISTER_OPERATOR(reduce_min_grad, ops::ReduceGradOp);
-
-REGISTER_OPERATOR(reduce_prod, ops::ReduceOp, ops::ReduceProdOpMaker,
- paddle::framework::DefaultGradOpDescMaker<true>);
-REGISTER_OPERATOR(reduce_prod_grad, ops::ReduceGradOp);
+#define REGISTER_REDUCE_OP(op_name) \
+ class __##op_name##Maker__ : public ops::ReduceOpMaker { \
+ protected: \
+ virtual std::string GetName() const { return #op_name; } \
+ virtual std::string GetOpType() const { return "Reduce " #op_name; } \
+ }; \
+ REGISTER_OPERATOR(reduce_##op_name, ops::ReduceOp, __##op_name##Maker__, \
+ paddle::framework::DefaultGradOpDescMaker<true>); \
+ REGISTER_OPERATOR(reduce_##op_name##_grad, ops::ReduceGradOp)
+
+REGISTER_REDUCE_OP(sum);
+REGISTER_REDUCE_OP(mean);
+REGISTER_REDUCE_OP(max);
+REGISTER_REDUCE_OP(min);
+REGISTER_REDUCE_OP(prod);
#define REGISTER_REDUCE_CPU_KERNEL(reduce_type, functor, grad_functor) \
REGISTER_OP_CPU_KERNEL(reduce_type, \
diff --git a/paddle/fluid/operators/reorder_lod_tensor_by_rank_op.cc b/paddle/fluid/operators/reorder_lod_tensor_by_rank_op.cc
index 5c3e1f5678..e4f4fe358e 100644
--- a/paddle/fluid/operators/reorder_lod_tensor_by_rank_op.cc
+++ b/paddle/fluid/operators/reorder_lod_tensor_by_rank_op.cc
@@ -23,9 +23,7 @@ namespace operators {
class ReorderLoDTensorByRankTableOpProtoMaker
: public framework::OpProtoAndCheckerMaker {
public:
- ReorderLoDTensorByRankTableOpProtoMaker(OpProto *proto,
- OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X",
"(LoDTensor), the input lod tensor to be reordered according to "
"Input(RankTable).");
diff --git a/paddle/fluid/operators/reshape_op.cc b/paddle/fluid/operators/reshape_op.cc
index 5e5ccc3ded..7f743f577f 100644
--- a/paddle/fluid/operators/reshape_op.cc
+++ b/paddle/fluid/operators/reshape_op.cc
@@ -22,8 +22,7 @@ namespace operators {
class ReshapeOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- ReshapeOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X", "(Tensor). The input tensor of reshape operator.");
AddInput("Shape",
"(Tensor<int32>, optional). If provided, reshape according to "
diff --git a/paddle/fluid/operators/rmsprop_op.cc b/paddle/fluid/operators/rmsprop_op.cc
index a8855b3ccd..919ebe48ca 100644
--- a/paddle/fluid/operators/rmsprop_op.cc
+++ b/paddle/fluid/operators/rmsprop_op.cc
@@ -63,8 +63,7 @@ class RmspropOp : public framework::OperatorWithKernel {
class RmspropOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- RmspropOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("Param",
"(Tensor, default Tensor<float>) "
"Input parameter value that has to be updated.");
diff --git a/paddle/fluid/operators/rnn_memory_helper_op.cc b/paddle/fluid/operators/rnn_memory_helper_op.cc
index 70f205d887..23e5fc1112 100644
--- a/paddle/fluid/operators/rnn_memory_helper_op.cc
+++ b/paddle/fluid/operators/rnn_memory_helper_op.cc
@@ -59,8 +59,7 @@ class RNNMemoryHelperOpShapeInference : public framework::InferShapeBase {
class RNNMemoryHelperOpInfoMaker : public framework::OpProtoAndCheckerMaker {
public:
- RNNMemoryHelperOpInfoMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X", "");
AddOutput("Out", "");
AddAttr<int>("dtype",
@@ -117,8 +116,7 @@ class RNNMemoryHelperGradOp : public framework::OperatorBase {
class RNNMemoryHelperGradOpInfoMaker
: public framework::OpProtoAndCheckerMaker {
public:
- RNNMemoryHelperGradOpInfoMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput(framework::GradVarName("Out"), "");
AddInput("X", "");
AddInput("Out", "");
diff --git a/paddle/fluid/operators/roi_pool_op.cc b/paddle/fluid/operators/roi_pool_op.cc
index 397e49ef20..293abb0ea4 100644
--- a/paddle/fluid/operators/roi_pool_op.cc
+++ b/paddle/fluid/operators/roi_pool_op.cc
@@ -98,8 +98,7 @@ class ROIPoolGradOp : public framework::OperatorWithKernel {
class ROIPoolOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- ROIPoolOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X",
"(Tensor), "
"the input of ROIPoolOp. "
diff --git a/paddle/fluid/operators/row_conv_op.cc b/paddle/fluid/operators/row_conv_op.cc
index 23f720da0b..20f140f962 100644
--- a/paddle/fluid/operators/row_conv_op.cc
+++ b/paddle/fluid/operators/row_conv_op.cc
@@ -76,8 +76,7 @@ class RowConvGradOp : public framework::OperatorWithKernel {
class RowConvOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- RowConvOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : framework::OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X",
"(LoDTensor), the input(X) is a LodTensor, which supports "
"variable time-length input sequences. The underlying tensor "
diff --git a/paddle/fluid/operators/save_combine_op.cc b/paddle/fluid/operators/save_combine_op.cc
index 94703393bf..8c34d95be3 100644
--- a/paddle/fluid/operators/save_combine_op.cc
+++ b/paddle/fluid/operators/save_combine_op.cc
@@ -109,8 +109,7 @@ class SaveCombineOp : public framework::OperatorBase {
class SaveCombineOpProtoMaker : public framework::OpProtoAndCheckerMaker {
public:
- SaveCombineOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput(
"X",
"(vector) Input LoDTensors that need to be saved together in a file.")
diff --git a/paddle/fluid/operators/save_op.cc b/paddle/fluid/operators/save_op.cc
index dcc1b9ec20..e6d27e2ded 100644
--- a/paddle/fluid/operators/save_op.cc
+++ b/paddle/fluid/operators/save_op.cc
@@ -117,8 +117,7 @@ class SaveOp : public framework::OperatorBase {
class SaveOpProtoMaker : public framework::OpProtoAndCheckerMaker {
public:
- SaveOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X", "(Tensor ) Input tensor to be saved");
AddComment(R"DOC(
Save operator
diff --git a/paddle/fluid/operators/scale_op.cc b/paddle/fluid/operators/scale_op.cc
index 7dcf33c989..4687e21e71 100644
--- a/paddle/fluid/operators/scale_op.cc
+++ b/paddle/fluid/operators/scale_op.cc
@@ -37,8 +37,7 @@ class ScaleOp : public framework::OperatorWithKernel {
class ScaleOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- ScaleOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X", "(Tensor) Input tensor of scale operator.");
AddOutput("Out", "(Tensor) Output tensor of scale operator.");
AddComment(R"DOC(
diff --git a/paddle/fluid/operators/scatter_op.cc b/paddle/fluid/operators/scatter_op.cc
index 95b12455ea..bf5e0d8644 100644
--- a/paddle/fluid/operators/scatter_op.cc
+++ b/paddle/fluid/operators/scatter_op.cc
@@ -78,8 +78,7 @@ class ScatterGradOp : public framework::OperatorWithKernel {
class ScatterOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- ScatterOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X", "The source input of scatter op");
AddInput("Ids", "The index input of scatter op where X will be updated");
AddInput("Updates", "The updated value of updates op");
diff --git a/paddle/fluid/operators/select_op.cc b/paddle/fluid/operators/select_op.cc
index 876d8acf0d..e71841d4d1 100644
--- a/paddle/fluid/operators/select_op.cc
+++ b/paddle/fluid/operators/select_op.cc
@@ -380,8 +380,7 @@ class SelectOp : public framework::OperatorBase {
class SelectOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- SelectOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput(kX,
"A set of variables, which are required by operators inside the "
"cases of Select Op")
diff --git a/paddle/fluid/operators/send_barrier_op.cc b/paddle/fluid/operators/send_barrier_op.cc
index 12b844daaa..1ce0907f3a 100644
--- a/paddle/fluid/operators/send_barrier_op.cc
+++ b/paddle/fluid/operators/send_barrier_op.cc
@@ -57,8 +57,7 @@ class SendBarrierOp : public framework::OperatorBase {
class SendBarrierOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- SendBarrierOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() {
AddOutput("RPCClient",
"(RPCClient) The RPC client object which is"
"initialized at most once.");
diff --git a/paddle/fluid/operators/send_op.cc b/paddle/fluid/operators/send_op.cc
index e4386b640a..95bb1f3c69 100644
--- a/paddle/fluid/operators/send_op.cc
+++ b/paddle/fluid/operators/send_op.cc
@@ -92,8 +92,7 @@ class SendOp : public framework::OperatorBase {
class SendOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- SendOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() {
AddInput("X", "(Tensor) Input tensor to be sent").AsDuplicable();
AddOutput("Out", "(Tensor) Output tensor to be received from server")
.AsDuplicable();
diff --git a/paddle/fluid/operators/send_vars_op.cc b/paddle/fluid/operators/send_vars_op.cc
index 56b3713d6a..f11e84c176 100644
--- a/paddle/fluid/operators/send_vars_op.cc
+++ b/paddle/fluid/operators/send_vars_op.cc
@@ -66,8 +66,7 @@ class SendVarsOp : public framework::OperatorBase {
class SendVarsOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- SendVarsOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() {
AddInput("X", "(Tensor, SelectedRows) Input variables to be sent")
.AsDuplicable();
AddOutput("RPCClient",
diff --git a/paddle/fluid/operators/sequence_concat_op.cc b/paddle/fluid/operators/sequence_concat_op.cc
index 3c21903e3a..077b9a5f7d 100644
--- a/paddle/fluid/operators/sequence_concat_op.cc
+++ b/paddle/fluid/operators/sequence_concat_op.cc
@@ -43,8 +43,7 @@ class SequenceConcatOp : public framework::OperatorWithKernel {
class SequenceConcatOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- SequenceConcatOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X",
"(LodTensorArray) Input is a vector of LoDTensor, "
"each of which is a variable-length sequence or nested sequence.")
diff --git a/paddle/fluid/operators/sequence_conv_op.cc b/paddle/fluid/operators/sequence_conv_op.cc
index 94f4b49b00..ec6cb24350 100644
--- a/paddle/fluid/operators/sequence_conv_op.cc
+++ b/paddle/fluid/operators/sequence_conv_op.cc
@@ -102,8 +102,7 @@ class SequenceConvGradOp : public framework::OperatorWithKernel {
class SequenceConvOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- SequenceConvOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput(
"X",
"(LoDTensor) the input(X) is a LodTensor, which supports "
diff --git a/paddle/fluid/operators/sequence_erase_op.cc b/paddle/fluid/operators/sequence_erase_op.cc
index 73c0e89512..1c86486157 100644
--- a/paddle/fluid/operators/sequence_erase_op.cc
+++ b/paddle/fluid/operators/sequence_erase_op.cc
@@ -37,8 +37,7 @@ class SequenceEraseOp : public framework::OperatorWithKernel {
class SequenceEraseOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- SequenceEraseOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X",
"(2-D LoDTensor with the 2nd dim. equal to 1) "
"Input LoDTensor of SequenceEraseOp.");
diff --git a/paddle/fluid/operators/sequence_expand_op.cc b/paddle/fluid/operators/sequence_expand_op.cc
index 84a35d7172..944c7f85e5 100644
--- a/paddle/fluid/operators/sequence_expand_op.cc
+++ b/paddle/fluid/operators/sequence_expand_op.cc
@@ -94,8 +94,7 @@ class SequenceExpandOp : public framework::OperatorWithKernel {
class SequenceExpandOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- SequenceExpandOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X",
"(LoDTensor, default LoDTensor<float>) A 2-D LoDTensor whose lod "
"level is at most 1.");
diff --git a/paddle/fluid/operators/sequence_pool_op.cc b/paddle/fluid/operators/sequence_pool_op.cc
index 933c8c2623..5c6fd13d42 100644
--- a/paddle/fluid/operators/sequence_pool_op.cc
+++ b/paddle/fluid/operators/sequence_pool_op.cc
@@ -38,8 +38,7 @@ class SequencePoolOp : public framework::OperatorWithKernel {
class SequencePoolOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- SequencePoolOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X", "(LoDTensor) The variable-length input of SequencePoolOp");
AddOutput("Out",
"(Tensor) The output of SequencePoolOp does not contain LoD "
diff --git a/paddle/fluid/operators/sequence_reshape_op.cc b/paddle/fluid/operators/sequence_reshape_op.cc
index a2999650b8..ef5e6f3210 100644
--- a/paddle/fluid/operators/sequence_reshape_op.cc
+++ b/paddle/fluid/operators/sequence_reshape_op.cc
@@ -42,8 +42,7 @@ class SequenceReshapeOp : public framework::OperatorWithKernel {
class SequenceReshapeOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- SequenceReshapeOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X",
"(LoDTensor, default LoDTensor<float>) A 2-D LoDTensor with shape "
"being [N, M].");
diff --git a/paddle/fluid/operators/sequence_slice_op.cc b/paddle/fluid/operators/sequence_slice_op.cc
index 7cd620af07..df9243dc04 100644
--- a/paddle/fluid/operators/sequence_slice_op.cc
+++ b/paddle/fluid/operators/sequence_slice_op.cc
@@ -79,8 +79,7 @@ class SequenceSliceGradOp : public framework::OperatorWithKernel {
class SequenceSliceOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- SequenceSliceOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X",
"(LoDTensor), "
"the input of SequenceSliceOp.");
diff --git a/paddle/fluid/operators/sequence_softmax_op.cc b/paddle/fluid/operators/sequence_softmax_op.cc
index a0d47c12ba..c44f8206eb 100644
--- a/paddle/fluid/operators/sequence_softmax_op.cc
+++ b/paddle/fluid/operators/sequence_softmax_op.cc
@@ -57,8 +57,7 @@ class SequenceSoftmaxOp : public framework::OperatorWithKernel {
class SequenceSoftmaxOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- SequenceSoftmaxOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X",
"(LoDTensor) 1-D or 2-D input LoDTensor with the 2-nd dimension "
"of length 1.");
diff --git a/paddle/fluid/operators/sgd_op.cc b/paddle/fluid/operators/sgd_op.cc
index bd04c60ffa..7a2bdeac09 100644
--- a/paddle/fluid/operators/sgd_op.cc
+++ b/paddle/fluid/operators/sgd_op.cc
@@ -68,8 +68,7 @@ class SGDOpInferVarType : public framework::VarTypeInference {
class SGDOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- SGDOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("Param", "(Tensor or SelectedRows) Input parameter");
AddInput("LearningRate", "(Tensor) Learning rate of SGD");
AddInput("Grad", "(Tensor or SelectedRows) Input gradient");
diff --git a/paddle/fluid/operators/shrink_rnn_memory_op.cc b/paddle/fluid/operators/shrink_rnn_memory_op.cc
index a1871a8e7f..8146c5f561 100644
--- a/paddle/fluid/operators/shrink_rnn_memory_op.cc
+++ b/paddle/fluid/operators/shrink_rnn_memory_op.cc
@@ -69,8 +69,7 @@ class ShrinkRNNMemoryOp : public ArrayOp {
class ShrinkRNNMemoryOpProtoMaker : public framework::OpProtoAndCheckerMaker {
public:
- ShrinkRNNMemoryOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X", "(LoDTensor) The RNN step memory to be shrinked.");
AddInput("RankTable", "(LoDRankTable) The lod_rank_table of dynamic RNN.");
AddInput("I",
diff --git a/paddle/fluid/operators/sigmoid_cross_entropy_with_logits_op.cc b/paddle/fluid/operators/sigmoid_cross_entropy_with_logits_op.cc
index 5db77d0493..135e2a6f7f 100644
--- a/paddle/fluid/operators/sigmoid_cross_entropy_with_logits_op.cc
+++ b/paddle/fluid/operators/sigmoid_cross_entropy_with_logits_op.cc
@@ -86,9 +86,7 @@ class SigmoidCrossEntropyWithLogitsGradOp
class SigmoidCrossEntropyWithLogitsOpMaker
: public framework::OpProtoAndCheckerMaker {
public:
- SigmoidCrossEntropyWithLogitsOpMaker(OpProto* proto,
- OpAttrChecker* op_checker)
- : framework::OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X",
"(Tensor, default Tensor<float>), a 2-D tensor with shape N x D, "
"where N is the batch size and D is the number of classes. "
diff --git a/paddle/fluid/operators/sign_op.cc b/paddle/fluid/operators/sign_op.cc
index 8f8b7abd03..f3985dcc02 100644
--- a/paddle/fluid/operators/sign_op.cc
+++ b/paddle/fluid/operators/sign_op.cc
@@ -34,8 +34,7 @@ class SignOp : public framework::OperatorWithKernel {
template <typename AttrType>
class SignOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- SignOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X", "(Tensor) Input tensor of sign operator.");
AddOutput("Out", "(Tensor) Output tensor of sign operator.");
AddComment(R"DOC(
diff --git a/paddle/fluid/operators/smooth_l1_loss_op.cc b/paddle/fluid/operators/smooth_l1_loss_op.cc
index 322581fdef..c44c5f164b 100644
--- a/paddle/fluid/operators/smooth_l1_loss_op.cc
+++ b/paddle/fluid/operators/smooth_l1_loss_op.cc
@@ -46,8 +46,7 @@ class SmoothL1LossOp : public framework::OperatorWithKernel {
class SmoothL1LossOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- SmoothL1LossOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X",
"(Tensor, default Tensor<float>) A tensor with rank at least 2. "
"The input value of smooth l1 loss op with shape "
diff --git a/paddle/fluid/operators/softmax_op.cc b/paddle/fluid/operators/softmax_op.cc
index aa7b192e32..cc256aa627 100644
--- a/paddle/fluid/operators/softmax_op.cc
+++ b/paddle/fluid/operators/softmax_op.cc
@@ -77,8 +77,7 @@ class SoftmaxOp : public framework::OperatorWithKernel {
class SoftmaxOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- SoftmaxOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X",
"The input tensor of softmax. "
"2-D with shape [batch_size, input_feature_dimensions].");
diff --git a/paddle/fluid/operators/softmax_with_cross_entropy_op.cc b/paddle/fluid/operators/softmax_with_cross_entropy_op.cc
index 857e573357..53cb716a97 100644
--- a/paddle/fluid/operators/softmax_with_cross_entropy_op.cc
+++ b/paddle/fluid/operators/softmax_with_cross_entropy_op.cc
@@ -20,8 +20,7 @@ namespace operators {
class SoftmaxWithCrossEntropyOpMaker
: public framework::OpProtoAndCheckerMaker {
public:
- SoftmaxWithCrossEntropyOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("Logits",
"(Tensor, default: Tensor<float>), The unscaled log probabilities "
"which is a 2-D tensor with shape [N x K]. N is the batch_size, "
diff --git a/paddle/fluid/operators/split_byref_op.cc b/paddle/fluid/operators/split_byref_op.cc
index 7413ce3e9c..bc998e1abb 100644
--- a/paddle/fluid/operators/split_byref_op.cc
+++ b/paddle/fluid/operators/split_byref_op.cc
@@ -64,8 +64,7 @@ class SplitByrefOp : public framework::OperatorWithKernel {
class SplitByrefOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- SplitByrefOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X", "(Tensor) Input tensor of the split operator.");
AddOutput("Out", "(Tensor) Output tensors of the split operator.")
.AsDuplicable();
diff --git a/paddle/fluid/operators/split_ids_op.cc b/paddle/fluid/operators/split_ids_op.cc
index a53cbc8ac5..c867c46873 100644
--- a/paddle/fluid/operators/split_ids_op.cc
+++ b/paddle/fluid/operators/split_ids_op.cc
@@ -19,8 +19,7 @@ namespace operators {
class SplitIdsOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- SplitIdsOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("Ids", "(LoDTensor) the input ids with shape{batch_num, 1}");
AddOutput("Out", "(LoDTensor) The outputs of the input Ids.")
.AsDuplicable();
diff --git a/paddle/fluid/operators/split_lod_tensor_op.cc b/paddle/fluid/operators/split_lod_tensor_op.cc
index 3222cce239..767449cde9 100644
--- a/paddle/fluid/operators/split_lod_tensor_op.cc
+++ b/paddle/fluid/operators/split_lod_tensor_op.cc
@@ -125,8 +125,7 @@ class SplitLoDTensorOp : public framework::OperatorBase {
class SplitLoDTensorOpProtoMaker : public framework::OpProtoAndCheckerMaker {
public:
- SplitLoDTensorOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X", "The input LoDTensor");
AddInput("Mask", "A bool column vector which mask the input");
AddOutput("OutTrue", "True branch of input LoDTensor");
diff --git a/paddle/fluid/operators/split_op.cc b/paddle/fluid/operators/split_op.cc
index a4398df36b..5e2b2a9945 100644
--- a/paddle/fluid/operators/split_op.cc
+++ b/paddle/fluid/operators/split_op.cc
@@ -70,8 +70,7 @@ class SplitOp : public framework::OperatorWithKernel {
class SplitOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- SplitOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X", "(Tensor) Input tensor of the split operator.");
AddOutput("Out", "(Tensor) Output tensors of the split operator.")
.AsDuplicable();
diff --git a/paddle/fluid/operators/split_selected_rows_op.cc b/paddle/fluid/operators/split_selected_rows_op.cc
index e1ce3d0c1b..76615a9405 100644
--- a/paddle/fluid/operators/split_selected_rows_op.cc
+++ b/paddle/fluid/operators/split_selected_rows_op.cc
@@ -19,8 +19,7 @@ namespace operators {
class SplitSelectedRowsOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- SplitSelectedRowsOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X", "The input SelectedRows.");
AddOutput("Out", "The outputs of the input SelectedRows.").AsDuplicable();
AddAttr<std::vector<int>>("height_sections",
diff --git a/paddle/fluid/operators/spp_op.cc b/paddle/fluid/operators/spp_op.cc
index 1cada95501..a2a96b72f0 100644
--- a/paddle/fluid/operators/spp_op.cc
+++ b/paddle/fluid/operators/spp_op.cc
@@ -20,8 +20,7 @@ namespace operators {
class SppOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- SppOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput(
"X",
"(Tensor) The input tensor of spp operator. "
diff --git a/paddle/fluid/operators/squared_l2_distance_op.cc b/paddle/fluid/operators/squared_l2_distance_op.cc
index c32f575b54..42532a294b 100644
--- a/paddle/fluid/operators/squared_l2_distance_op.cc
+++ b/paddle/fluid/operators/squared_l2_distance_op.cc
@@ -56,8 +56,7 @@ class SquaredL2DistanceOp : public framework::OperatorWithKernel {
class SquaredL2DistanceOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- SquaredL2DistanceOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X", "(Tensor) Input of SquaredL2DistanceOp.");
AddInput("Y", "(Tensor) Target of SquaredL2DistanceOp.");
AddOutput("sub_result",
diff --git a/paddle/fluid/operators/squared_l2_norm_op.cc b/paddle/fluid/operators/squared_l2_norm_op.cc
index 4ce51259da..7bd82e0ce4 100644
--- a/paddle/fluid/operators/squared_l2_norm_op.cc
+++ b/paddle/fluid/operators/squared_l2_norm_op.cc
@@ -48,8 +48,7 @@ class SquaredL2NormGradOp : public framework::OperatorWithKernel {
class SquaredL2NormOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- SquaredL2NormOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : framework::OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X", "(Tensor) The input of squared_l2_norm op.");
AddOutput("Out", "(Scalar) The output of squared_l2_norm op.");
AddComment(R"DOC(
diff --git a/paddle/fluid/operators/sum_op.cc b/paddle/fluid/operators/sum_op.cc
index 108f26fafe..bcc5e22d4a 100644
--- a/paddle/fluid/operators/sum_op.cc
+++ b/paddle/fluid/operators/sum_op.cc
@@ -112,8 +112,7 @@ class SumOp : public framework::OperatorWithKernel {
class SumOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- SumOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X", "(vector<Tensor>) The input tensors of sum operator.")
.AsDuplicable();
AddOutput("Out", "(Tensor) The output tensor of sum operator.");
diff --git a/paddle/fluid/operators/target_assign_op.cc b/paddle/fluid/operators/target_assign_op.cc
index 33ff967e5e..9fce216e88 100644
--- a/paddle/fluid/operators/target_assign_op.cc
+++ b/paddle/fluid/operators/target_assign_op.cc
@@ -65,8 +65,7 @@ class TargetAssignOp : public framework::OperatorWithKernel {
class TargetAssignOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- TargetAssignOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X",
"(LoDTensor), This input is a 3D LoDTensor with shape [M, P, K]. "
"Some elements in X will be assigned to Out based on the "
diff --git a/paddle/fluid/operators/tensor_array_read_write_op.cc b/paddle/fluid/operators/tensor_array_read_write_op.cc
index 2636812c42..c703d11eec 100644
--- a/paddle/fluid/operators/tensor_array_read_write_op.cc
+++ b/paddle/fluid/operators/tensor_array_read_write_op.cc
@@ -57,8 +57,7 @@ class WriteToArrayOp : public ArrayOp {
class WriteToArrayOpProtoMaker : public framework::OpProtoAndCheckerMaker {
public:
- WriteToArrayOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X", "(LoDTensor) the tensor will be written to tensor array");
AddInput(
"I",
@@ -148,8 +147,7 @@ class ReadFromArrayOp : public ArrayOp {
class ReadFromArrayProtoMaker : public framework::OpProtoAndCheckerMaker {
public:
- ReadFromArrayProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X", "(TensorArray) the array will be read from.");
AddInput("I",
"(Tensor) the subscript index in tensor array. The number of "
diff --git a/paddle/fluid/operators/top_k_op.cc b/paddle/fluid/operators/top_k_op.cc
index 942a5de3f9..c17d1afc30 100644
--- a/paddle/fluid/operators/top_k_op.cc
+++ b/paddle/fluid/operators/top_k_op.cc
@@ -48,8 +48,7 @@ class TopkOp : public framework::OperatorWithKernel {
class TopkOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- TopkOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("X", "(Tensor) The input of Topk op");
AddOutput("Out", "(Tensor) The output tensor of Topk op");
AddOutput("Indices", "(Tensor) The indices of Topk elements of input");
diff --git a/paddle/fluid/operators/transpose_op.cc b/paddle/fluid/operators/transpose_op.cc
index 3555cb68ca..60556a564c 100644
--- a/paddle/fluid/operators/transpose_op.cc
+++ b/paddle/fluid/operators/transpose_op.cc
@@ -56,8 +56,7 @@ class TransposeOp : public framework::OperatorWithKernel {
class TransposeOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- TransposeOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput(
"X",
"(Tensor) The input tensor, tensors with rank up to 6 are supported.");
diff --git a/paddle/fluid/operators/uniform_random_batch_size_like_op.cc b/paddle/fluid/operators/uniform_random_batch_size_like_op.cc
index 00f00bb403..aa9f794786 100644
--- a/paddle/fluid/operators/uniform_random_batch_size_like_op.cc
+++ b/paddle/fluid/operators/uniform_random_batch_size_like_op.cc
@@ -33,8 +33,7 @@ class UniformRandomBatchSizeLikeOp : public BatchSizeLikeOp {
class UniformRandomBatchSizeLikeOpMaker : public BatchSizeLikeOpMaker {
public:
- UniformRandomBatchSizeLikeOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : BatchSizeLikeOpMaker(proto, op_checker) {
+ void Make() override {
AddComment(R"DOC(
Uniform random operator
diff --git a/paddle/fluid/operators/uniform_random_op.cc b/paddle/fluid/operators/uniform_random_op.cc
index 3b5cf68dd4..137ea91cae 100644
--- a/paddle/fluid/operators/uniform_random_op.cc
+++ b/paddle/fluid/operators/uniform_random_op.cc
@@ -85,8 +85,7 @@ class UniformRandomOp : public framework::OperatorWithKernel {
class UniformRandomOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- UniformRandomOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : framework::OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddOutput("Out", "(Tensor) The output tensor of uniform random op");
AddComment(R"DOC(
Uniform random operator.
diff --git a/paddle/fluid/operators/unpool_op.cc b/paddle/fluid/operators/unpool_op.cc
index b3cd87efa2..1d441b43b1 100644
--- a/paddle/fluid/operators/unpool_op.cc
+++ b/paddle/fluid/operators/unpool_op.cc
@@ -20,8 +20,7 @@ namespace operators {
class Unpool2dOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- Unpool2dOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput(
"X",
"(Tensor) The input tensor of unpool operator. "
diff --git a/paddle/fluid/operators/warpctc_op.cc b/paddle/fluid/operators/warpctc_op.cc
index 6835a5dd62..e06c8c962f 100644
--- a/paddle/fluid/operators/warpctc_op.cc
+++ b/paddle/fluid/operators/warpctc_op.cc
@@ -53,8 +53,7 @@ class WarpCTCOp : public framework::OperatorWithKernel {
class WarpCTCOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- WarpCTCOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput("Logits",
"(LodTensor, default: LoDTensor<float>), the unscaled "
"probabilities of variable-length sequences, which is a 2-D "
diff --git a/paddle/fluid/operators/while_op.cc b/paddle/fluid/operators/while_op.cc
index 710cc9fc2e..175c3ac5d7 100644
--- a/paddle/fluid/operators/while_op.cc
+++ b/paddle/fluid/operators/while_op.cc
@@ -68,8 +68,7 @@ class WhileOp : public framework::OperatorBase {
class WhileOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- WhileOpMaker(OpProto *proto, OpAttrChecker *op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddInput(kX,
"A set of variables, which are required by operators inside the "
"block of While Op.")
From f4851f14b8398515ab393cde509f48989586b40f Mon Sep 17 00:00:00 2001
From: chengduoZH <zhaochengduo@163.com>
Date: Mon, 7 May 2018 14:07:46 +0800
Subject: [PATCH 022/195] clean code
---
.../details/threaded_ssa_graph_executor.cc | 108 ++++++++++--------
.../details/threaded_ssa_graph_executor.h | 16 +++
.../tests/unittests/test_parallel_executor.py | 4 +
3 files changed, 80 insertions(+), 48 deletions(-)
diff --git a/paddle/fluid/framework/details/threaded_ssa_graph_executor.cc b/paddle/fluid/framework/details/threaded_ssa_graph_executor.cc
index 5e6ed5cb7c..e90523ebe8 100644
--- a/paddle/fluid/framework/details/threaded_ssa_graph_executor.cc
+++ b/paddle/fluid/framework/details/threaded_ssa_graph_executor.cc
@@ -14,8 +14,6 @@
#include "paddle/fluid/framework/details/threaded_ssa_graph_executor.h"
-#include "paddle/fluid/framework/details/fetch_op_handle.h"
-
namespace paddle {
namespace framework {
namespace details {
@@ -45,73 +43,33 @@ FeedFetchList ThreadedSSAGraphExecutor::Run(
// Should revisit it if overlapping is available.
std::unordered_set<OpHandleBase *> delayed_ops;
- auto InsertPendingVar = [&pending_vars, &ready_vars](VarHandleBase &var) {
- pending_vars.insert(&var);
- if (var.generated_op_ == nullptr) {
- ready_vars.Push(&var);
- }
- };
-
- auto InsertPendingOp = [&pending_ops](OpHandleBase &op_instance) {
- pending_ops.insert({&op_instance, op_instance.Inputs().size()});
- };
-
// Transform SSAGraph to pending_ops & pending_vars
for (auto &var_map : graph_->vars_) {
for (auto &name_pair : var_map) {
for (auto &version_pair : name_pair.second) {
- InsertPendingVar(*version_pair);
+ InsertPendingVar(&pending_vars, &ready_vars, version_pair.get());
}
}
}
for (auto &var : graph_->dep_vars_) {
- InsertPendingVar(*var);
+ InsertPendingVar(&pending_vars, &ready_vars, var.get());
}
for (auto &op : graph_->ops_) {
if (op->Inputs().empty()) { // Special case, Op has no input.
ready_ops.insert(op.get());
} else {
- InsertPendingOp(*op);
+ InsertPendingOp(&pending_ops, op.get());
}
}
// Step 2. Insert FetchOps
std::vector<std::unique_ptr<FetchOpHandle>> fetch_ops;
- FeedFetchList fetch_data(fetch_tensors.size());
-
- std::unordered_map<std::string, std::vector<VarHandleBase *>> fetched_vars;
-
- for (auto &fetch_var_name : fetch_tensors) {
- for (auto &var_map : graph_->vars_) {
- auto it = var_map.find(fetch_var_name);
- if (it != var_map.end()) {
- fetched_vars[fetch_var_name].push_back(it->second.rbegin()->get());
- }
- }
- }
-
std::unordered_set<std::unique_ptr<VarHandleBase>> fetch_dependencies;
- for (size_t i = 0; i < fetch_tensors.size(); ++i) {
- auto &var_name = fetch_tensors[i];
- auto &vars = fetched_vars.at(var_name);
- auto *op = new FetchOpHandle(&fetch_data, i, &local_scopes_);
- fetch_ops.emplace_back(op);
-
- for (auto &p : places_) {
- op->SetDeviceContext(p, fetch_ctxs_.Get(p));
- }
-
- for (auto *var : vars) {
- op->AddInput(var);
- }
+ FeedFetchList fetch_data(fetch_tensors.size());
- auto *fetch_dummy = new DummyVarHandle();
- op->AddOutput(fetch_dummy);
- fetch_dependencies.emplace(fetch_dummy);
- InsertPendingVar(*fetch_dummy);
- InsertPendingOp(*op);
- }
+ InsertFetchOps(fetch_tensors, &fetch_ops, &fetch_dependencies, &pending_ops,
+ &pending_vars, &ready_vars, &fetch_data);
auto run_all_ops = [&](std::unordered_set<OpHandleBase *> &set) {
for (auto *op : set) {
@@ -174,6 +132,60 @@ FeedFetchList ThreadedSSAGraphExecutor::Run(
return fetch_data;
}
+void ThreadedSSAGraphExecutor::InsertFetchOps(
+ const std::vector<std::string> &fetch_tensors,
+ std::vector<std::unique_ptr<FetchOpHandle>> *fetch_ops,
+ std::unordered_set<std::unique_ptr<VarHandleBase>> *fetch_dependencies,
+ std::unordered_map<OpHandleBase *, size_t> *pending_ops,
+ std::unordered_set<VarHandleBase *> *pending_vars,
+ BlockingQueue<VarHandleBase *> *ready_vars, FeedFetchList *fetch_data) {
+ std::unordered_map<std::string, std::vector<VarHandleBase *>> fetched_vars;
+
+ for (auto &fetch_var_name : fetch_tensors) {
+ for (auto &var_map : graph_->vars_) {
+ auto it = var_map.find(fetch_var_name);
+ if (it != var_map.end()) {
+ fetched_vars[fetch_var_name].push_back(it->second.rbegin()->get());
+ }
+ }
+ }
+
+ for (size_t i = 0; i < fetch_tensors.size(); ++i) {
+ auto &var_name = fetch_tensors[i];
+ auto &vars = fetched_vars.at(var_name);
+ auto *op = new FetchOpHandle(fetch_data, i, &local_scopes_);
+ fetch_ops->emplace_back(op);
+
+ for (auto &p : places_) {
+ op->SetDeviceContext(p, fetch_ctxs_.Get(p));
+ }
+
+ for (auto *var : vars) {
+ op->AddInput(var);
+ }
+
+ auto *fetch_dummy = new DummyVarHandle();
+ op->AddOutput(fetch_dummy);
+ fetch_dependencies->emplace(fetch_dummy);
+ this->InsertPendingVar(pending_vars, ready_vars, fetch_dummy);
+ this->InsertPendingOp(pending_ops, op);
+ }
+}
+
+void ThreadedSSAGraphExecutor::InsertPendingOp(
+ std::unordered_map<OpHandleBase *, size_t> *pending_ops,
+ OpHandleBase *op_instance) const {
+ pending_ops->insert({op_instance, op_instance->Inputs().size()});
+}
+
+void ThreadedSSAGraphExecutor::InsertPendingVar(
+ std::unordered_set<VarHandleBase *> *pending_vars,
+ BlockingQueue<VarHandleBase *> *ready_vars, VarHandleBase *var) const {
+ pending_vars->insert(var);
+ if (var->generated_op_ == nullptr) {
+ ready_vars->Push(var);
+ }
+}
void ThreadedSSAGraphExecutor::RunOp(
BlockingQueue<VarHandleBase *> *ready_var_q, details::OpHandleBase *op) {
auto op_run = [ready_var_q, op, this] {
diff --git a/paddle/fluid/framework/details/threaded_ssa_graph_executor.h b/paddle/fluid/framework/details/threaded_ssa_graph_executor.h
index d089b79d91..f18a88526b 100644
--- a/paddle/fluid/framework/details/threaded_ssa_graph_executor.h
+++ b/paddle/fluid/framework/details/threaded_ssa_graph_executor.h
@@ -23,6 +23,7 @@
#include <functional>
#include "ThreadPool.h" // ThreadPool in thrird party
#include "paddle/fluid/framework/blocking_queue.h"
+#include "paddle/fluid/framework/details/fetch_op_handle.h"
#include "paddle/fluid/framework/details/ssa_graph_executor.h"
namespace paddle {
@@ -58,6 +59,21 @@ class ThreadedSSAGraphExecutor : public SSAGraphExecutor {
std::unique_ptr<platform::EnforceNotMet> exception_;
std::atomic<int> running_ops_;
bool allow_op_delay_;
+
+ void InsertPendingOp(std::unordered_map<OpHandleBase *, size_t> *pending_ops,
+ OpHandleBase *op_instance) const;
+
+ void InsertPendingVar(std::unordered_set<VarHandleBase *> *pending_vars,
+ BlockingQueue<VarHandleBase *> *ready_vars,
+ VarHandleBase *var) const;
+
+ void InsertFetchOps(
+ const std::vector<std::string> &fetch_tensors,
+ std::vector<std::unique_ptr<FetchOpHandle>> *fetch_ops,
+ std::unordered_set<std::unique_ptr<VarHandleBase>> *fetch_dependencies,
+ std::unordered_map<OpHandleBase *, size_t> *pending_ops,
+ std::unordered_set<VarHandleBase *> *pending_vars,
+ BlockingQueue<VarHandleBase *> *ready_vars, FeedFetchList *fetch_data);
};
} // namespace details
diff --git a/python/paddle/fluid/tests/unittests/test_parallel_executor.py b/python/paddle/fluid/tests/unittests/test_parallel_executor.py
index 9056f5e66f..34fdd46057 100644
--- a/python/paddle/fluid/tests/unittests/test_parallel_executor.py
+++ b/python/paddle/fluid/tests/unittests/test_parallel_executor.py
@@ -721,3 +721,7 @@ class TestCRFModel(unittest.TestCase):
def test_update_dense_parameter(self):
self.check_network_convergence(is_sparse=False)
+
+
+if __name__ == '__main__':
+ unittest.main()
From 59509785733609fc204760e3f93ff3225ffd67f4 Mon Sep 17 00:00:00 2001
From: Yang Yang <yangyang62@baidu.com>
Date: Tue, 8 May 2018 21:38:09 +0000
Subject: [PATCH 023/195] decrease the pass number of test_label_semantic_roles
---
python/paddle/fluid/tests/book/test_label_semantic_roles.py | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/python/paddle/fluid/tests/book/test_label_semantic_roles.py b/python/paddle/fluid/tests/book/test_label_semantic_roles.py
index 50ef29c457..0faba33032 100644
--- a/python/paddle/fluid/tests/book/test_label_semantic_roles.py
+++ b/python/paddle/fluid/tests/book/test_label_semantic_roles.py
@@ -36,7 +36,7 @@ depth = 8
mix_hidden_lr = 1e-3
IS_SPARSE = True
-PASS_NUM = 100
+PASS_NUM = 10
BATCH_SIZE = 10
embedding_name = 'emb'
From 9eec2c75098708e95f2207f89c5e8002c09c557a Mon Sep 17 00:00:00 2001
From: chengduoZH <zhaochengduo@163.com>
Date: Wed, 9 May 2018 11:13:10 +0800
Subject: [PATCH 024/195] refine pe
---
.../framework/details/broadcast_op_handle.cc | 12 +-------
.../framework/details/broadcast_op_handle.h | 1 -
.../details/computation_op_handle.cc | 16 +++++------
.../framework/details/computation_op_handle.h | 2 ++
.../framework/details/fetch_op_handle.cc | 19 ++++++++-----
.../fluid/framework/details/fetch_op_handle.h | 4 ++-
.../framework/details/gather_op_handle.cc | 13 +--------
.../framework/details/gather_op_handle.h | 1 -
.../details/nccl_all_reduce_op_handle.cc | 5 +---
.../fluid/framework/details/op_handle_base.cc | 28 +++++++++++++++++--
.../fluid/framework/details/op_handle_base.h | 10 ++++++-
.../framework/details/reduce_op_handle.cc | 13 +--------
.../framework/details/reduce_op_handle.h | 2 --
.../details/scale_loss_grad_op_handle.cc | 1 +
.../fluid/framework/details/send_op_handle.cc | 8 +-----
15 files changed, 65 insertions(+), 70 deletions(-)
diff --git a/paddle/fluid/framework/details/broadcast_op_handle.cc b/paddle/fluid/framework/details/broadcast_op_handle.cc
index 2afa47c81b..f176e4e159 100644
--- a/paddle/fluid/framework/details/broadcast_op_handle.cc
+++ b/paddle/fluid/framework/details/broadcast_op_handle.cc
@@ -38,9 +38,7 @@ void BroadcastOpHandle::RunImpl() {
out_var_handles.size(), places_.size(),
"The number of output should equal to the number of places.");
- // Wait input done, this Wait is asynchronous operation platform::Place
- // &in_place;
- WaitInputVarGenerated(*in_var_handle);
+ WaitInputVarGenerated();
std::vector<const Scope *> var_scopes;
for (auto *s : local_scopes_) {
@@ -147,14 +145,6 @@ void BroadcastOpHandle::RunImpl() {
}
}
-void BroadcastOpHandle::WaitInputVarGenerated(const VarHandle &in_var) {
- if (in_var.generated_op_) {
- for (auto &pair : dev_ctxes_) {
- in_var.generated_op_->Wait(pair.second);
- }
- }
-}
-
std::string BroadcastOpHandle::Name() const { return "broadcast"; }
} // namespace details
} // namespace framework
diff --git a/paddle/fluid/framework/details/broadcast_op_handle.h b/paddle/fluid/framework/details/broadcast_op_handle.h
index 984a95008c..48e356af4b 100644
--- a/paddle/fluid/framework/details/broadcast_op_handle.h
+++ b/paddle/fluid/framework/details/broadcast_op_handle.h
@@ -57,7 +57,6 @@ struct BroadcastOpHandle : public OpHandleBase {
protected:
void RunImpl() override;
- void WaitInputVarGenerated(const VarHandle &in_var);
private:
const std::vector<Scope *> &local_scopes_;
diff --git a/paddle/fluid/framework/details/computation_op_handle.cc b/paddle/fluid/framework/details/computation_op_handle.cc
index 7ff0efe093..ffbe2094a4 100644
--- a/paddle/fluid/framework/details/computation_op_handle.cc
+++ b/paddle/fluid/framework/details/computation_op_handle.cc
@@ -26,20 +26,20 @@ ComputationOpHandle::ComputationOpHandle(const OpDesc &op_desc, Scope *scope,
place_(place) {}
void ComputationOpHandle::RunImpl() {
- auto *cur_ctx = dev_ctxes_[place_];
- for (auto *in : inputs_) {
- bool need_wait = in->generated_op_ &&
- in->generated_op_->DeviceContext(place_) != cur_ctx;
- if (need_wait) {
- in->generated_op_->Wait(cur_ctx);
- }
- }
+ WaitInputVarGenerated(place_);
this->RunAndRecordEvent([this] {
op_->Run(*scope_->FindVar(kLocalExecScopeName)->Get<Scope *>(), place_);
});
}
+bool ComputationOpHandle::NeedWait(VarHandleBase *in_var) {
+ bool need_wait =
+ dynamic_cast<VarHandle *>(in_var) && in_var->generated_op_ &&
+ in_var->generated_op_->DeviceContext(place_) != dev_ctxes_[place_];
+ return need_wait;
+}
+
std::string ComputationOpHandle::Name() const { return op_->Type(); }
} // namespace details
} // namespace framework
diff --git a/paddle/fluid/framework/details/computation_op_handle.h b/paddle/fluid/framework/details/computation_op_handle.h
index c363b973d9..36e6f1bf59 100644
--- a/paddle/fluid/framework/details/computation_op_handle.h
+++ b/paddle/fluid/framework/details/computation_op_handle.h
@@ -36,6 +36,8 @@ struct ComputationOpHandle : public OpHandleBase {
protected:
void RunImpl() override;
+ virtual bool NeedWait(VarHandleBase *in_var);
+
private:
std::unique_ptr<OperatorBase> op_;
Scope *scope_;
diff --git a/paddle/fluid/framework/details/fetch_op_handle.cc b/paddle/fluid/framework/details/fetch_op_handle.cc
index 1e8ca20b51..b1c9dd0d15 100644
--- a/paddle/fluid/framework/details/fetch_op_handle.cc
+++ b/paddle/fluid/framework/details/fetch_op_handle.cc
@@ -31,7 +31,7 @@ FetchOpHandle::~FetchOpHandle() {
}
}
-void FetchOpHandle::Wait(platform::DeviceContext *waited_dev) {
+void FetchOpHandle::RecordWaitEventOnCtx(platform::DeviceContext *waited_ctx) {
PADDLE_THROW("Nobody should wait FetchOp. Unexpceted Error");
}
@@ -45,12 +45,8 @@ void FetchOpHandle::WaitAndMergeCPUTensors() const {
}
void FetchOpHandle::RunImpl() {
- auto cpu_ctx =
- platform::DeviceContextPool::Instance().Get(platform::CPUPlace());
- for (auto *input : inputs_) {
- auto *var = static_cast<VarHandle *>(input);
- var->generated_op_->Wait(cpu_ctx);
- }
+ WaitInputVarGenerated(platform::CPUPlace());
+
tensors_.resize(inputs_.size());
auto *var_handle = static_cast<VarHandle *>(inputs_[0]);
auto &var_name = var_handle->name_;
@@ -77,6 +73,15 @@ void FetchOpHandle::RunImpl() {
this->WaitAndMergeCPUTensors();
}
+void FetchOpHandle::WaitInputVarGenerated(const platform::Place &place) {
+ auto cpu_ctx = platform::DeviceContextPool::Instance().Get(place);
+ for (auto *input : inputs_) {
+ if (input->generated_op_) {
+ input->generated_op_->RecordWaitEventOnCtx(cpu_ctx);
+ }
+ }
+}
+
std::string FetchOpHandle::Name() const { return "Fetch"; }
} // namespace details
diff --git a/paddle/fluid/framework/details/fetch_op_handle.h b/paddle/fluid/framework/details/fetch_op_handle.h
index b49f3df338..e696a7a9ce 100644
--- a/paddle/fluid/framework/details/fetch_op_handle.h
+++ b/paddle/fluid/framework/details/fetch_op_handle.h
@@ -33,7 +33,7 @@ struct FetchOpHandle : public OpHandleBase {
~FetchOpHandle();
- void Wait(platform::DeviceContext *waited_dev) override;
+ void RecordWaitEventOnCtx(platform::DeviceContext *waited_ctx) override;
void WaitAndMergeCPUTensors() const;
@@ -42,6 +42,8 @@ struct FetchOpHandle : public OpHandleBase {
protected:
void RunImpl() override;
+ virtual void WaitInputVarGenerated(const platform::Place &place);
+
private:
FeedFetchList *data_;
size_t offset_;
diff --git a/paddle/fluid/framework/details/gather_op_handle.cc b/paddle/fluid/framework/details/gather_op_handle.cc
index 3dfc972a44..2be0230456 100644
--- a/paddle/fluid/framework/details/gather_op_handle.cc
+++ b/paddle/fluid/framework/details/gather_op_handle.cc
@@ -55,7 +55,7 @@ void GatherOpHandle::RunImpl() {
"Currently, gather_op only can gather SelectedRows.");
// Wait input done, this Wait is asynchronous operation
- WaitInputVarGenerated(in_var_handles);
+ WaitInputVarGenerated();
auto &pre_in_value = pre_in_var->Get<framework::SelectedRows>();
std::vector<int64_t> out_rows;
@@ -111,17 +111,6 @@ void GatherOpHandle::RunImpl() {
});
}
-void GatherOpHandle::WaitInputVarGenerated(
- const std::vector<VarHandle *> &in_var_handles) {
- for (auto *in : in_var_handles) {
- if (in->generated_op_) {
- for (auto pair : dev_ctxes_) {
- in->generated_op_->Wait(pair.second);
- }
- }
- }
-}
-
std::string GatherOpHandle::Name() const { return "gather"; }
} // namespace details
} // namespace framework
diff --git a/paddle/fluid/framework/details/gather_op_handle.h b/paddle/fluid/framework/details/gather_op_handle.h
index c394dd7a14..d11ef8556a 100644
--- a/paddle/fluid/framework/details/gather_op_handle.h
+++ b/paddle/fluid/framework/details/gather_op_handle.h
@@ -39,7 +39,6 @@ struct GatherOpHandle : public OpHandleBase {
protected:
void RunImpl() override;
- void WaitInputVarGenerated(const std::vector<VarHandle *> &in_var_handles);
private:
const std::vector<Scope *> &local_scopes_;
diff --git a/paddle/fluid/framework/details/nccl_all_reduce_op_handle.cc b/paddle/fluid/framework/details/nccl_all_reduce_op_handle.cc
index b055bb48f6..95aa599cd3 100644
--- a/paddle/fluid/framework/details/nccl_all_reduce_op_handle.cc
+++ b/paddle/fluid/framework/details/nccl_all_reduce_op_handle.cc
@@ -34,10 +34,7 @@ void NCCLAllReduceOpHandle::RunImpl() {
return; // No need to all reduce when GPU count = 1;
} else {
// Wait input done
- for (auto *in : inputs_) {
- auto &p = static_cast<VarHandle *>(in)->place_;
- in->generated_op_->Wait(dev_ctxes_[p]);
- }
+ WaitInputVarGenerated();
auto &var_name = static_cast<VarHandle *>(this->inputs_[0])->name_;
int dtype = -1;
diff --git a/paddle/fluid/framework/details/op_handle_base.cc b/paddle/fluid/framework/details/op_handle_base.cc
index 534d77860f..b05b9d95e7 100644
--- a/paddle/fluid/framework/details/op_handle_base.cc
+++ b/paddle/fluid/framework/details/op_handle_base.cc
@@ -56,15 +56,15 @@ void OpHandleBase::Run(bool use_event) {
RunImpl();
}
-void OpHandleBase::Wait(platform::DeviceContext *waited_dev) {
+void OpHandleBase::RecordWaitEventOnCtx(platform::DeviceContext *waited_ctx) {
#ifdef PADDLE_WITH_CUDA
- if (platform::is_cpu_place(waited_dev->GetPlace()) || events_.empty()) {
+ if (platform::is_cpu_place(waited_ctx->GetPlace()) || events_.empty()) {
for (auto &dev_ctx : dev_ctxes_) {
dev_ctx.second->Wait();
}
} else {
auto stream =
- static_cast<platform::CUDADeviceContext *>(waited_dev)->stream();
+ static_cast<platform::CUDADeviceContext *>(waited_ctx)->stream();
for (auto &ev : events_) {
PADDLE_ENFORCE(cudaStreamWaitEvent(stream, ev.second, 0));
}
@@ -86,6 +86,28 @@ void OpHandleBase::AddOutput(VarHandleBase *out) {
out->generated_op_ = this;
}
+void OpHandleBase::WaitInputVarGenerated() {
+ for (auto in_var : inputs_) {
+ if (NeedWait(in_var)) {
+ for (auto &pair : dev_ctxes_) {
+ in_var->generated_op_->RecordWaitEventOnCtx(pair.second);
+ }
+ }
+ }
+}
+
+void OpHandleBase::WaitInputVarGenerated(const platform::Place &place) {
+ for (auto *in : inputs_) {
+ if (NeedWait(in)) {
+ in->generated_op_->RecordWaitEventOnCtx(dev_ctxes_[place]);
+ }
+ }
+}
+
+bool OpHandleBase::NeedWait(VarHandleBase *in_var) {
+ return dynamic_cast<VarHandle *>(in_var) && in_var->generated_op_;
+}
+
void OpHandleBase::RunAndRecordEvent(const std::function<void()> &callback) {
#ifdef PADDLE_WITH_CUDA
if (!events_.empty()) { // Use event
diff --git a/paddle/fluid/framework/details/op_handle_base.h b/paddle/fluid/framework/details/op_handle_base.h
index 00f213f3ed..3d4a093125 100644
--- a/paddle/fluid/framework/details/op_handle_base.h
+++ b/paddle/fluid/framework/details/op_handle_base.h
@@ -38,12 +38,20 @@ class OpHandleBase {
void Run(bool use_event);
- virtual void Wait(platform::DeviceContext *waited_dev);
+ virtual void RecordWaitEventOnCtx(platform::DeviceContext *waited_ctx);
void AddInput(VarHandleBase *in);
void AddOutput(VarHandleBase *out);
+ // Wait inputs are generated, this Wait is asynchronous operation.
+ virtual void WaitInputVarGenerated();
+
+ // Wait inputs are generated, this Wait is asynchronous operation.
+ virtual void WaitInputVarGenerated(const platform::Place &place);
+
+ virtual bool NeedWait(VarHandleBase *in_var);
+
// If the Op involves data transfer of multiple devices that
// will likely block other computations.
virtual bool IsMultiDeviceTransfer() { return false; }
diff --git a/paddle/fluid/framework/details/reduce_op_handle.cc b/paddle/fluid/framework/details/reduce_op_handle.cc
index 1bb04c1dfc..f653064ade 100644
--- a/paddle/fluid/framework/details/reduce_op_handle.cc
+++ b/paddle/fluid/framework/details/reduce_op_handle.cc
@@ -51,7 +51,7 @@ void ReduceOpHandle::RunImpl() {
PADDLE_ENFORCE_NOT_NULL(pre_in_var);
// Wait input done, this Wait is asynchronous operation
- WaitInputVarGenerated(in_var_handles);
+ WaitInputVarGenerated();
// NOTE: The Places of all input tensor must be all on CPU or all on GPU.
std::vector<platform::Place> in_places; // used to get dev_ctx
@@ -157,17 +157,6 @@ std::vector<const T *> ReduceOpHandle::GetInputValues(
return in_selected_rows;
}
-void ReduceOpHandle::WaitInputVarGenerated(
- const std::vector<VarHandle *> &in_var_handles) {
- for (auto *in : in_var_handles) {
- if (in->generated_op_) {
- for (auto pair : dev_ctxes_) {
- in->generated_op_->Wait(pair.second);
- }
- }
- }
-}
-
std::string ReduceOpHandle::Name() const { return "reduce"; }
} // namespace details
} // namespace framework
diff --git a/paddle/fluid/framework/details/reduce_op_handle.h b/paddle/fluid/framework/details/reduce_op_handle.h
index 59731d348d..c652a2f4eb 100644
--- a/paddle/fluid/framework/details/reduce_op_handle.h
+++ b/paddle/fluid/framework/details/reduce_op_handle.h
@@ -60,8 +60,6 @@ struct ReduceOpHandle : public OpHandleBase {
protected:
void RunImpl() override;
- void WaitInputVarGenerated(const std::vector<VarHandle *> &in_var_handles);
-
template <typename T>
std::vector<const T *> GetInputValues(
const std::vector<VarHandle *> &in_var_handles,
diff --git a/paddle/fluid/framework/details/scale_loss_grad_op_handle.cc b/paddle/fluid/framework/details/scale_loss_grad_op_handle.cc
index 1cd3113030..d9c387e79d 100644
--- a/paddle/fluid/framework/details/scale_loss_grad_op_handle.cc
+++ b/paddle/fluid/framework/details/scale_loss_grad_op_handle.cc
@@ -29,6 +29,7 @@ ScaleLossGradOpHandle::ScaleLossGradOpHandle(size_t num_dev, Scope *scope,
ScaleLossGradOpHandle::~ScaleLossGradOpHandle() {}
void ScaleLossGradOpHandle::RunImpl() {
+ // Doesn't wait any event
std::string var_name = static_cast<VarHandle *>(this->outputs_[0])->name_;
auto &local_scope = *scope_->FindVar(kLocalExecScopeName)->Get<Scope *>();
diff --git a/paddle/fluid/framework/details/send_op_handle.cc b/paddle/fluid/framework/details/send_op_handle.cc
index 0763f92171..ee4beb5f9b 100644
--- a/paddle/fluid/framework/details/send_op_handle.cc
+++ b/paddle/fluid/framework/details/send_op_handle.cc
@@ -27,13 +27,7 @@ SendOpHandle::SendOpHandle(const framework::OpDesc &op_desc,
void SendOpHandle::RunImpl() {
// Wait input done
- for (auto *in : inputs_) {
- auto &p = static_cast<VarHandle *>(in)->place_;
- if (in->DebugString() == "dummy") { // HACK
- continue;
- }
- in->generated_op_->Wait(dev_ctxes_[p]);
- }
+ WaitInputVarGenerated();
auto &tmp_scope = local_scope_->FindVar(kLocalExecScopeName)->Get<Scope *>();
// FIXME(wuyi): can not use RunAndRecordEvent here, for it will cause dead
// lock.
From 3de43a87ef1a94c0fc7161a922bcbeb078705e48 Mon Sep 17 00:00:00 2001
From: Xin Pan <panxin.grad@gmail.com>
Date: Sun, 6 May 2018 22:02:28 +0800
Subject: [PATCH 025/195] Add a multi-dim add layer test.
We need to figure out if tensorrt
use row-major or col-major for tensor
layerout inorder to do conversion.
---
.../fluid/inference/tensorrt/test_engine.cc | 33 +++++++++++++++++++
1 file changed, 33 insertions(+)
diff --git a/paddle/fluid/inference/tensorrt/test_engine.cc b/paddle/fluid/inference/tensorrt/test_engine.cc
index a08b78f930..e27d73314f 100644
--- a/paddle/fluid/inference/tensorrt/test_engine.cc
+++ b/paddle/fluid/inference/tensorrt/test_engine.cc
@@ -77,6 +77,39 @@ TEST_F(TensorRTEngineTest, add_layer) {
ASSERT_EQ(y_cpu, x_v * 2 + 3);
}
+TEST_F(TensorRTEngineTest, add_layer_multi_dim) {
+ // Weight in CPU memory.
+ // It seems tensorrt FC use col-major: [[1.0, 3.3], [1.1, 4.4]]
+ // instead of row-major, which is [[1.0, 1.1], [3.3, 4.4]]
+ float raw_weight[4] = {1.0, 1.1, 3.3, 4.4};
+ // [1, 2]
+ float raw_bias[2] = {1.3, 2.4};
+
+ TensorRTEngine::Weight weight(nvinfer1::DataType::kFLOAT, raw_weight, 4);
+ TensorRTEngine::Weight bias(nvinfer1::DataType::kFLOAT, raw_bias, 2);
+ auto* x = engine_->DeclareInput("x", nvinfer1::DataType::kFLOAT,
+ nvinfer1::DimsCHW{1, 2, 1});
+ auto* fc_layer = TRT_ENGINE_ADD_LAYER(engine_, FullyConnected, *x, 2,
+ weight.get(), bias.get());
+ PADDLE_ENFORCE(fc_layer != nullptr);
+
+ engine_->DeclareOutput(fc_layer, 0, "y");
+ engine_->FreezeNetwork();
+ ASSERT_EQ(engine_->engine()->getNbBindings(), 2);
+
+ // fill in real data [1.0, 2.0]
+ float x_v[2] = {1.0, 2.0};
+ engine_->SetInputFromCPU("x", reinterpret_cast<void*>(&x_v),
+ 2 * sizeof(float));
+ engine_->Execute(1);
+
+ LOG(INFO) << "to get output";
+ float y_cpu[2] = {-1., -1.};
+ engine_->GetOutputInCPU("y", &y_cpu[0], sizeof(float) * 2);
+ ASSERT_EQ(y_cpu[0], 4.5);
+ ASSERT_EQ(y_cpu[1], 14.5);
+}
+
} // namespace tensorrt
} // namespace inference
} // namespace paddle
From 6728d96d891b027bf233e21d55d76a545ac5df4f Mon Sep 17 00:00:00 2001
From: Xin Pan <panxin.grad@gmail.com>
Date: Tue, 8 May 2018 08:12:03 +0800
Subject: [PATCH 026/195] follow comments
---
paddle/fluid/inference/tensorrt/test_engine.cc | 2 --
1 file changed, 2 deletions(-)
diff --git a/paddle/fluid/inference/tensorrt/test_engine.cc b/paddle/fluid/inference/tensorrt/test_engine.cc
index e27d73314f..69dbb9a3f2 100644
--- a/paddle/fluid/inference/tensorrt/test_engine.cc
+++ b/paddle/fluid/inference/tensorrt/test_engine.cc
@@ -82,7 +82,6 @@ TEST_F(TensorRTEngineTest, add_layer_multi_dim) {
// It seems tensorrt FC use col-major: [[1.0, 3.3], [1.1, 4.4]]
// instead of row-major, which is [[1.0, 1.1], [3.3, 4.4]]
float raw_weight[4] = {1.0, 1.1, 3.3, 4.4};
- // [1, 2]
float raw_bias[2] = {1.3, 2.4};
TensorRTEngine::Weight weight(nvinfer1::DataType::kFLOAT, raw_weight, 4);
@@ -97,7 +96,6 @@ TEST_F(TensorRTEngineTest, add_layer_multi_dim) {
engine_->FreezeNetwork();
ASSERT_EQ(engine_->engine()->getNbBindings(), 2);
- // fill in real data [1.0, 2.0]
float x_v[2] = {1.0, 2.0};
engine_->SetInputFromCPU("x", reinterpret_cast<void*>(&x_v),
2 * sizeof(float));
From 6eeb81953810a8c2f3c8b3c2725db9c94d0ec6b6 Mon Sep 17 00:00:00 2001
From: Yan Chunwei <yanchunwei@outlook.com>
Date: Wed, 9 May 2018 14:59:44 +0800
Subject: [PATCH 027/195] feature/inference analysis dot (#10494)
---
paddle/fluid/inference/CMakeLists.txt | 2 +
.../fluid/inference/analysis/CMakeLists.txt | 1 +
paddle/fluid/inference/analysis/dot.cc | 23 +++
paddle/fluid/inference/analysis/dot.h | 154 ++++++++++++++++++
4 files changed, 180 insertions(+)
create mode 100644 paddle/fluid/inference/analysis/CMakeLists.txt
create mode 100644 paddle/fluid/inference/analysis/dot.cc
create mode 100644 paddle/fluid/inference/analysis/dot.h
diff --git a/paddle/fluid/inference/CMakeLists.txt b/paddle/fluid/inference/CMakeLists.txt
index 50f635a41a..db953e5cf3 100644
--- a/paddle/fluid/inference/CMakeLists.txt
+++ b/paddle/fluid/inference/CMakeLists.txt
@@ -21,6 +21,8 @@ endif()
if(WITH_TESTING)
add_subdirectory(tests/book)
+ # analysis test depends the models that generate by python/paddle/fluid/tests/book
+ add_subdirectory(analysis)
endif()
if (TENSORRT_FOUND)
diff --git a/paddle/fluid/inference/analysis/CMakeLists.txt b/paddle/fluid/inference/analysis/CMakeLists.txt
new file mode 100644
index 0000000000..de7becae4d
--- /dev/null
+++ b/paddle/fluid/inference/analysis/CMakeLists.txt
@@ -0,0 +1 @@
+cc_library(dot SRCS dot.cc)
diff --git a/paddle/fluid/inference/analysis/dot.cc b/paddle/fluid/inference/analysis/dot.cc
new file mode 100644
index 0000000000..d5471ffcb5
--- /dev/null
+++ b/paddle/fluid/inference/analysis/dot.cc
@@ -0,0 +1,23 @@
+// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+// http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include "paddle/fluid/inference/analysis/dot.h"
+
+namespace paddle {
+namespace inference {
+namespace analysis {
+size_t Dot::counter = 0;
+} // namespace analysis
+} // namespace inference
+} // namespace paddle
diff --git a/paddle/fluid/inference/analysis/dot.h b/paddle/fluid/inference/analysis/dot.h
new file mode 100644
index 0000000000..3359987874
--- /dev/null
+++ b/paddle/fluid/inference/analysis/dot.h
@@ -0,0 +1,154 @@
+// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+// http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+/*
+ * This file implements some helper classes and methods for DOT programming
+ * support. It will give a visualization of the graph and that helps to debug
+ * the logics of each Pass.
+ */
+#pragma once
+
+#include <glog/logging.h>
+#include <sstream>
+#include <unordered_map>
+#include <vector>
+
+namespace paddle {
+namespace inference {
+namespace analysis {
+
+/*
+ * A Dot template that helps to build a DOT graph definition.
+ */
+class Dot {
+ public:
+ static size_t counter;
+
+ struct Attr {
+ std::string key;
+ std::string value;
+
+ Attr(const std::string& key, const std::string& value)
+ : key(key), value(value) {}
+
+ std::string repr() const {
+ std::stringstream ss;
+ ss << key << "=" << '"' << value << '"';
+ return ss.str();
+ }
+ };
+
+ struct Node {
+ std::string name;
+ std::vector<Attr> attrs;
+
+ Node(const std::string& name, const std::vector<Attr>& attrs)
+ : name(name),
+ attrs(attrs),
+ id_("node_" + std::to_string(Dot::counter++)) {}
+
+ std::string id() const { return id_; }
+
+ std::string repr() const {
+ std::stringstream ss;
+ CHECK(!name.empty());
+ ss << id_;
+ for (size_t i = 0; i < attrs.size(); i++) {
+ if (i == 0) {
+ ss << "[label=" << '"' << name << '"' << " ";
+ }
+ ss << attrs[i].repr();
+ ss << ((i < attrs.size() - 1) ? " " : "]");
+ }
+ return ss.str();
+ }
+
+ private:
+ std::string id_;
+ };
+
+ struct Edge {
+ std::string source;
+ std::string target;
+ std::vector<Attr> attrs;
+
+ Edge(const std::string& source, const std::string& target,
+ const std::vector<Attr>& attrs)
+ : source(source), target(target), attrs(attrs) {}
+
+ std::string repr() const {
+ std::stringstream ss;
+ CHECK(!source.empty());
+ CHECK(!target.empty());
+ ss << source << "->" << target;
+ for (size_t i = 0; i < attrs.size(); i++) {
+ if (i == 0) {
+ ss << "[";
+ }
+ ss << attrs[i].repr();
+ ss << ((i < attrs.size() - 1) ? " " : "]");
+ }
+ return ss.str();
+ }
+ };
+
+ Dot() = default;
+
+ explicit Dot(const std::vector<Attr>& attrs) : attrs_(attrs) {}
+
+ void AddNode(const std::string& name, const std::vector<Attr>& attrs) {
+ CHECK(!nodes_.count(name)) << "duplicate Node '" << name << "'";
+ nodes_.emplace(name, Node{name, attrs});
+ }
+
+ void AddEdge(const std::string& source, const std::string& target,
+ const std::vector<Attr>& attrs) {
+ CHECK(!source.empty());
+ CHECK(!target.empty());
+ auto sid = nodes_.at(source).id();
+ auto tid = nodes_.at(target).id();
+ edges_.emplace_back(sid, tid, attrs);
+ }
+
+ // Compile to DOT language codes.
+ std::string Build() const {
+ std::stringstream ss;
+ const std::string indent = " ";
+ ss << "digraph G {" << '\n';
+
+ // Add graph attrs
+ for (const auto& attr : attrs_) {
+ ss << indent << attr.repr() << '\n';
+ }
+ // add nodes
+ for (auto& item : nodes_) {
+ ss << indent << item.second.repr() << '\n';
+ }
+ // add edges
+ for (auto& edge : edges_) {
+ ss << indent << edge.repr() << '\n';
+ }
+ ss << "} // end G";
+ return ss.str();
+ }
+
+ private:
+ std::unordered_map<std::string, Node> nodes_;
+ std::vector<Edge> edges_;
+ std::vector<Attr> attrs_;
+};
+
+} // namespace analysis
+} // namespace inference
+} // namespace paddle
From d0e8bd2905e5c9472fd8718ff09e1349e8552355 Mon Sep 17 00:00:00 2001
From: Wojciech Uss <wojciech.uss@intel.com>
Date: Tue, 8 May 2018 11:58:15 +0200
Subject: [PATCH 028/195] bump mkldnn version
---
cmake/external/mkldnn.cmake | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/cmake/external/mkldnn.cmake b/cmake/external/mkldnn.cmake
index 5759e5c489..83c1cf1457 100644
--- a/cmake/external/mkldnn.cmake
+++ b/cmake/external/mkldnn.cmake
@@ -53,7 +53,7 @@ ExternalProject_Add(
${EXTERNAL_PROJECT_LOG_ARGS}
DEPENDS ${MKLDNN_DEPENDS}
GIT_REPOSITORY "https://github.com/01org/mkl-dnn.git"
- GIT_TAG "v0.11"
+ GIT_TAG "v0.14"
PREFIX ${MKLDNN_SOURCES_DIR}
UPDATE_COMMAND ""
CMAKE_ARGS -DCMAKE_INSTALL_PREFIX=${MKLDNN_INSTALL_DIR}
From f096a2fc3b4e0c54649faf2dad6767fdd9c55f65 Mon Sep 17 00:00:00 2001
From: weixing02 <wx_crome@163.com>
Date: Wed, 9 May 2018 15:59:14 +0800
Subject: [PATCH 029/195] Move all images to doc/v2/images/
---
doc/v2/images/FullyConnected.jpg | Bin 0 -> 50847 bytes
doc/v2/images/add_security_group.png | Bin 0 -> 118948 bytes
doc/v2/images/bi_lstm.jpg | Bin 0 -> 35593 bytes
doc/v2/images/checkpointing.png | Bin 0 -> 183359 bytes
doc/v2/images/create_efs.png | Bin 0 -> 241814 bytes
doc/v2/images/csr.png | Bin 0 -> 370051 bytes
doc/v2/images/data_dispatch.png | Bin 0 -> 33872 bytes
doc/v2/images/dataset.graffle | Bin 0 -> 2770 bytes
doc/v2/images/dataset.png | Bin 0 -> 10845 bytes
doc/v2/images/doc_en.png | Bin 0 -> 162824 bytes
doc/v2/images/efs_mount.png | Bin 0 -> 230609 bytes
.../encoder-decoder-attention-model.png | Bin 0 -> 68089 bytes
doc/v2/images/engine.png | Bin 0 -> 13586 bytes
doc/v2/images/file_storage.graffle | Bin 0 -> 3059 bytes
doc/v2/images/file_storage.png | Bin 0 -> 43413 bytes
doc/v2/images/glossary_rnn.dot | 42 +++++++++++++++
doc/v2/images/glossary_rnn_with_memory.dot | 48 ++++++++++++++++++
doc/v2/images/gradients.png | Bin 0 -> 22890 bytes
doc/v2/images/init_lock.graffle | Bin 0 -> 3090 bytes
doc/v2/images/init_lock.png | Bin 0 -> 26774 bytes
doc/v2/images/k8s-paddle-arch.png | Bin 0 -> 430953 bytes
doc/v2/images/layers.png | Bin 0 -> 11646 bytes
doc/v2/images/managed_policy.png | Bin 0 -> 247321 bytes
doc/v2/images/matrix.png | Bin 0 -> 18407 bytes
doc/v2/images/nvvp1.png | Bin 0 -> 426047 bytes
doc/v2/images/nvvp2.png | Bin 0 -> 495117 bytes
doc/v2/images/nvvp3.png | Bin 0 -> 253700 bytes
doc/v2/images/nvvp4.png | Bin 0 -> 283198 bytes
doc/v2/images/overview.png | Bin 0 -> 10766 bytes
doc/v2/images/paddle-cloud-in-data-center.png | Bin 0 -> 78576 bytes
doc/v2/images/paddle-etcd.graffle | Bin 0 -> 5578 bytes
doc/v2/images/paddle-etcd.png | Bin 0 -> 50377 bytes
doc/v2/images/paddle-model-sharding.graffle | Bin 0 -> 2989 bytes
doc/v2/images/paddle-model-sharding.png | Bin 0 -> 38398 bytes
doc/v2/images/paddle-ps-0.png | Bin 0 -> 21368 bytes
doc/v2/images/paddle-ps-1.png | Bin 0 -> 28337 bytes
doc/v2/images/paddle-ps.graffle | Bin 0 -> 2890 bytes
doc/v2/images/paddle-task-queues.graffle | Bin 0 -> 2740 bytes
doc/v2/images/paddle-task-queues.png | Bin 0 -> 34753 bytes
doc/v2/images/paddle-task-states.graffle | Bin 0 -> 2305 bytes
doc/v2/images/paddle-task-states.png | Bin 0 -> 18224 bytes
doc/v2/images/ps_cn.png | Bin 0 -> 33865 bytes
doc/v2/images/ps_en.png | Bin 0 -> 145107 bytes
doc/v2/images/pserver_and_trainer.png | Bin 0 -> 71688 bytes
doc/v2/images/pserver_init.graffle | Bin 0 -> 2436 bytes
doc/v2/images/pserver_init.png | Bin 0 -> 28616 bytes
doc/v2/images/route53_create_recordset.png | Bin 0 -> 35749 bytes
doc/v2/images/route53_create_zone.png | Bin 0 -> 52035 bytes
doc/v2/images/sequence_data.png | Bin 0 -> 481460 bytes
.../simple_full_hierarchical_recurrent.dot | 30 +++++++++++
doc/v2/images/simple_full_recurrent.dot | 19 +++++++
doc/v2/images/submit-job.graffle | Bin 0 -> 3931 bytes
doc/v2/images/submit-job.png | Bin 0 -> 52772 bytes
doc/v2/images/trainer.graffle | Bin 0 -> 6144 bytes
doc/v2/images/trainer.png | Bin 0 -> 145107 bytes
doc/v2/images/trainer_cn.png | Bin 0 -> 33865 bytes
doc/v2/images/worker_security_group.png | Bin 0 -> 89208 bytes
doc/v2/images/workflow_of_CAPI.png | Bin 0 -> 458577 bytes
58 files changed, 139 insertions(+)
create mode 100644 doc/v2/images/FullyConnected.jpg
create mode 100644 doc/v2/images/add_security_group.png
create mode 100644 doc/v2/images/bi_lstm.jpg
create mode 100644 doc/v2/images/checkpointing.png
create mode 100644 doc/v2/images/create_efs.png
create mode 100644 doc/v2/images/csr.png
create mode 100644 doc/v2/images/data_dispatch.png
create mode 100644 doc/v2/images/dataset.graffle
create mode 100644 doc/v2/images/dataset.png
create mode 100644 doc/v2/images/doc_en.png
create mode 100644 doc/v2/images/efs_mount.png
create mode 100644 doc/v2/images/encoder-decoder-attention-model.png
create mode 100644 doc/v2/images/engine.png
create mode 100644 doc/v2/images/file_storage.graffle
create mode 100644 doc/v2/images/file_storage.png
create mode 100644 doc/v2/images/glossary_rnn.dot
create mode 100644 doc/v2/images/glossary_rnn_with_memory.dot
create mode 100644 doc/v2/images/gradients.png
create mode 100644 doc/v2/images/init_lock.graffle
create mode 100644 doc/v2/images/init_lock.png
create mode 100644 doc/v2/images/k8s-paddle-arch.png
create mode 100644 doc/v2/images/layers.png
create mode 100644 doc/v2/images/managed_policy.png
create mode 100644 doc/v2/images/matrix.png
create mode 100644 doc/v2/images/nvvp1.png
create mode 100644 doc/v2/images/nvvp2.png
create mode 100644 doc/v2/images/nvvp3.png
create mode 100644 doc/v2/images/nvvp4.png
create mode 100644 doc/v2/images/overview.png
create mode 100644 doc/v2/images/paddle-cloud-in-data-center.png
create mode 100644 doc/v2/images/paddle-etcd.graffle
create mode 100644 doc/v2/images/paddle-etcd.png
create mode 100644 doc/v2/images/paddle-model-sharding.graffle
create mode 100644 doc/v2/images/paddle-model-sharding.png
create mode 100644 doc/v2/images/paddle-ps-0.png
create mode 100644 doc/v2/images/paddle-ps-1.png
create mode 100644 doc/v2/images/paddle-ps.graffle
create mode 100644 doc/v2/images/paddle-task-queues.graffle
create mode 100644 doc/v2/images/paddle-task-queues.png
create mode 100644 doc/v2/images/paddle-task-states.graffle
create mode 100644 doc/v2/images/paddle-task-states.png
create mode 100644 doc/v2/images/ps_cn.png
create mode 100644 doc/v2/images/ps_en.png
create mode 100644 doc/v2/images/pserver_and_trainer.png
create mode 100644 doc/v2/images/pserver_init.graffle
create mode 100644 doc/v2/images/pserver_init.png
create mode 100644 doc/v2/images/route53_create_recordset.png
create mode 100644 doc/v2/images/route53_create_zone.png
create mode 100644 doc/v2/images/sequence_data.png
create mode 100644 doc/v2/images/simple_full_hierarchical_recurrent.dot
create mode 100644 doc/v2/images/simple_full_recurrent.dot
create mode 100644 doc/v2/images/submit-job.graffle
create mode 100644 doc/v2/images/submit-job.png
create mode 100644 doc/v2/images/trainer.graffle
create mode 100644 doc/v2/images/trainer.png
create mode 100644 doc/v2/images/trainer_cn.png
create mode 100644 doc/v2/images/worker_security_group.png
create mode 100644 doc/v2/images/workflow_of_CAPI.png
diff --git a/doc/v2/images/FullyConnected.jpg b/doc/v2/images/FullyConnected.jpg
new file mode 100644
index 0000000000000000000000000000000000000000..b2241f401434e527f95ee4e0e541a3f2ff78fd1e
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diff --git a/doc/v2/images/add_security_group.png b/doc/v2/images/add_security_group.png
new file mode 100644
index 0000000000000000000000000000000000000000..bd34f46c9b0ada7027fd53e553e7d033255d25fc
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diff --git a/doc/v2/images/glossary_rnn.dot b/doc/v2/images/glossary_rnn.dot
new file mode 100644
index 0000000000..2cd0fb1820
--- /dev/null
+++ b/doc/v2/images/glossary_rnn.dot
@@ -0,0 +1,42 @@
+digraph G{
+ subgraph cluster_timestep0 {
+ label="recurrent timestep i-1"
+ bgcolor=lightgray
+ node [style=filled,color=white]
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+ fc0_1 [label="fc 1"]
+ fc0_2 [label="fc 2"]
+
+ fc0_0 -> fc0_1
+ fc0_1 -> fc0_2
+ }
+
+ subgraph cluster_timestep1 {
+ label="recurrent timestep i"
+ node [style=filled];
+ fc1_0 [label="fc 0"]
+ fc1_1 [label="fc 1"]
+ fc1_2 [label="fc 2"]
+ color=blue
+
+ fc1_0 -> fc1_1
+ fc1_1 -> fc1_2
+ }
+
+ subgraph cluster_timestep2 {
+ label="recurrent timestep i+1"
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+ fc2_1 [label="fc 1"]
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\ No newline at end of file
diff --git a/doc/v2/images/glossary_rnn_with_memory.dot b/doc/v2/images/glossary_rnn_with_memory.dot
new file mode 100644
index 0000000000..0f101ec2d8
--- /dev/null
+++ b/doc/v2/images/glossary_rnn_with_memory.dot
@@ -0,0 +1,48 @@
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+ }
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+ subgraph cluster_timestep1 {
+ label="recurrent timestep i"
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+ }
+
+
+ m0 -> m1 [style="dotted" constraint=false]
+ m1 -> m2 [style="dotted" constraint=false]
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\ No newline at end of file
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literal 0
HcmV?d00001
diff --git a/doc/v2/images/simple_full_hierarchical_recurrent.dot b/doc/v2/images/simple_full_hierarchical_recurrent.dot
new file mode 100644
index 0000000000..ff278a0323
--- /dev/null
+++ b/doc/v2/images/simple_full_hierarchical_recurrent.dot
@@ -0,0 +1,30 @@
+digraph G {
+ rankdir=LR;
+
+ subgraph cluster_t0 {
+ a [label="4"]
+ b [label="5"]
+ c [label="2"]
+ }
+
+ subgraph cluster_t1 {
+ d [label="0"]
+ e [label="9"]
+ }
+
+ subgraph cluster_t2 {
+ f [label="8"]
+ g [label="1"]
+ h [label="4"]
+ }
+
+ a -> b;
+ b -> c;
+ c -> d [constraint=false];
+
+ d -> e;
+ e -> f [constraint=false];
+
+ f -> g;
+ g -> h;
+}
\ No newline at end of file
diff --git a/doc/v2/images/simple_full_recurrent.dot b/doc/v2/images/simple_full_recurrent.dot
new file mode 100644
index 0000000000..cee281fbac
--- /dev/null
+++ b/doc/v2/images/simple_full_recurrent.dot
@@ -0,0 +1,19 @@
+digraph G {
+ rankdir=LR;
+ a [label="4"]
+ b [label="5"]
+ c [label="2"]
+ d [label="0"]
+ e [label="9"]
+ f [label="8"]
+ g [label="1"]
+ h [label="4"]
+
+ a -> b;
+ b -> c;
+ c -> d;
+ d -> e;
+ e -> f;
+ f -> g;
+ g -> h;
+}
\ No newline at end of file
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diff --git a/doc/v2/images/submit-job.png b/doc/v2/images/submit-job.png
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HcmV?d00001
From 333e26d3e16d96298f4f3b7d5c1d376cf99b7163 Mon Sep 17 00:00:00 2001
From: weixing02 <wx_crome@163.com>
Date: Wed, 9 May 2018 15:59:37 +0800
Subject: [PATCH 030/195] Fix image and table display error
---
doc/v2/design/mkl/mkldnn.md | 48 +++++++++++++++++++++++++++++--------
1 file changed, 38 insertions(+), 10 deletions(-)
diff --git a/doc/v2/design/mkl/mkldnn.md b/doc/v2/design/mkl/mkldnn.md
index 1bd2e7bc34..5a6011ea5c 100644
--- a/doc/v2/design/mkl/mkldnn.md
+++ b/doc/v2/design/mkl/mkldnn.md
@@ -5,7 +5,7 @@
充分展现英特尔平台的优势，有效提升PaddlePaddle在英特尔架构上的性能。
<div align="center">
-<img src="image/overview.png"><br/>
+<img src="https://raw.githubusercontent.com/PaddlePaddle/Paddle/develop/doc/v2/images/overview.png"><br/>
Figure 1. PaddlePaddle on IA
</div>
@@ -42,16 +42,44 @@ Figure 1. PaddlePaddle on IA
MKL，MKLML以及MKL-DNN三者关系如下表：
-| Name | Open Source | License | Descriptions |
-| :---------- | :--------------- | :---------- | :------------ |
-| MKL | No | Proprietary | Accelerate math processing routines |
-| MKLML | No | Proprietary | Small package of MKL, especially for Machine Learning |
-| MKL-DNN | Yes | Apache 2.0 | Accelerate primitives processing routines especially for Deep Neural Networks |
+<table>
+<thead>
+<tr>
+<th>Name</th>
+<th>Open Source</th>
+<th>License</th>
+<th>Descriptions</th>
+</tr>
+</thead>
+<tbody>
+<tr>
+<td>MKL</td>
+<td>No</td>
+<td>Proprietary</td>
+<td>Accelerate math processing routines</td>
+</tr>
+
+<tr>
+<td>MKLML</td>
+<td>No</td>
+<td>Proprietary</td>
+<td>Small package of MKL, especially for Machine Learning</td>
+</tr>
+
+<tr>
+<td>MKL-DNN</td>
+<td>Yes</td>
+<td>Apache 2.0</td>
+<td>Accelerate primitives processing routines especially for Deep Neural Networks</td>
+</tr>
+
+</tbody>
+</table>
MKLML可以与MKL-DNN共同使用，以此达到最好的性能。
<div align="center">
-<img src="image/engine.png"><br/>
+<img src="https://raw.githubusercontent.com/PaddlePaddle/Paddle/develop/doc/v2/images/engine.png"><br/>
Figure 2. PaddlePaddle with MKL Engines
</div>
@@ -103,7 +131,7 @@ MKL-DNN的库目前只有动态库`libmkldnn.so`。
所以我们定义了一个`MKLDNNMatrix`用于管理MKL-DNN数据的不同格式以及相互之间的转换。
<div align="center">
-<img src="image/matrix.png"><br/>
+<img src="https://raw.githubusercontent.com/PaddlePaddle/Paddle/develop/doc/v2/images/matrix.png"><br/>
Figure 3. MKLDNNMatrix
</div>
@@ -113,7 +141,7 @@ Figure 3. MKLDNNMatrix
子类只需要使用定义好的接口，实现具体的函数功能即可。
<div align="center">
-<img src="image/layers.png"><br/>
+<img src="https://raw.githubusercontent.com/PaddlePaddle/Paddle/develop/doc/v2/images/layers.png"><br/>
Figure 4. MKLDNNLayer
</div>
@@ -150,7 +178,7 @@ Figure 4. MKLDNNLayer
所以整体上，在实现每个子类的时候就不需要关心分支的事情了。
<div align="center">
-<img src="image/gradients.png"><br/>
+<img src="https://raw.githubusercontent.com/PaddlePaddle/Paddle/develop/doc/v2/images/gradients.png"><br/>
Figure 5. Merge Gradients
</div>
From db7b70d505903bb1cd31afe490bc610a4fda970f Mon Sep 17 00:00:00 2001
From: weixing02 <wx_crome@163.com>
Date: Wed, 9 May 2018 16:46:20 +0800
Subject: [PATCH 031/195] Adjust
---
doc/v2/design/mkl/mkldnn.md | 1 -
1 file changed, 1 deletion(-)
diff --git a/doc/v2/design/mkl/mkldnn.md b/doc/v2/design/mkl/mkldnn.md
index 5a6011ea5c..bd5bcf6f67 100644
--- a/doc/v2/design/mkl/mkldnn.md
+++ b/doc/v2/design/mkl/mkldnn.md
@@ -58,7 +58,6 @@ MKL，MKLML以及MKL-DNN三者关系如下表：
<td>Proprietary</td>
<td>Accelerate math processing routines</td>
</tr>
-
<tr>
<td>MKLML</td>
<td>No</td>
From 819038113e454dbf6f4fc7617e394002af4bdd45 Mon Sep 17 00:00:00 2001
From: Yan Chunwei <yanchunwei@outlook.com>
Date: Wed, 9 May 2018 17:04:45 +0800
Subject: [PATCH 032/195] Feature/engine refactor (#10497)
* init refactor
* init
* update some comment
* fix build
* fix errorrr
* fix bug
* fix comment
* update
---
paddle/fluid/inference/engine.h | 15 +++++++
.../fluid/inference/tensorrt/CMakeLists.txt | 5 ++-
.../inference/tensorrt/convert/CMakeLists.txt | 4 +-
paddle/fluid/inference/tensorrt/engine.cc | 44 +++++++++++++------
paddle/fluid/inference/tensorrt/engine.h | 6 ++-
5 files changed, 54 insertions(+), 20 deletions(-)
diff --git a/paddle/fluid/inference/engine.h b/paddle/fluid/inference/engine.h
index 6b0ac92fa9..de0375551e 100644
--- a/paddle/fluid/inference/engine.h
+++ b/paddle/fluid/inference/engine.h
@@ -19,6 +19,9 @@ limitations under the License. */
namespace paddle {
namespace inference {
+struct Buffer;
+enum class DeviceType { UNK = -1, CPU, GPU };
+
/*
* EngineBase is the base class of all inference engines. An inference engine
* takes a paddle program as input, and outputs the result in fluid Tensor
@@ -45,8 +48,20 @@ class EngineBase {
// Execute the engine, that will run the inference network.
virtual void Execute(int batch_size) = 0;
+ // Return the IO buffer that allocated in engine. One can read/write directly
+ // on the buffer. If the buffer's buffer is nullptr, one can also allocate
+ // memory and maintain it outside the engine.
+ virtual Buffer& buffer(const std::string& name) = 0;
+
virtual ~EngineBase() {}
}; // class EngineBase
+struct Buffer {
+ void* buffer{nullptr}; // buffer should be allocated only once.
+ int max_size; // buffer allocated space.
+ int size; // data size.
+ DeviceType device{DeviceType::UNK}; // tells which device this buffer is on.
+};
+
} // namespace inference
} // namespace paddle
diff --git a/paddle/fluid/inference/tensorrt/CMakeLists.txt b/paddle/fluid/inference/tensorrt/CMakeLists.txt
index 288789d6e4..41632dabcb 100644
--- a/paddle/fluid/inference/tensorrt/CMakeLists.txt
+++ b/paddle/fluid/inference/tensorrt/CMakeLists.txt
@@ -1,4 +1,5 @@
+nv_library(tensorrt_engine SRCS engine.cc)
nv_test(test_tensorrt SRCS test_tensorrt.cc DEPS dynload_cuda device_context dynamic_loader)
-nv_test(test_tensorrt_engine SRCS test_engine.cc engine.cc DEPS dynload_cuda)
-set(ENGINE_FILE ${CMAKE_CURRENT_SOURCE_DIR}/engine.cc)
+nv_test(test_tensorrt_engine SRCS test_engine.cc DEPS dynload_cuda tensorrt_engine)
+
add_subdirectory(convert)
diff --git a/paddle/fluid/inference/tensorrt/convert/CMakeLists.txt b/paddle/fluid/inference/tensorrt/convert/CMakeLists.txt
index 3c5909c0be..5178c54c08 100644
--- a/paddle/fluid/inference/tensorrt/convert/CMakeLists.txt
+++ b/paddle/fluid/inference/tensorrt/convert/CMakeLists.txt
@@ -1,4 +1,4 @@
nv_test(test_op_converter SRCS test_op_converter.cc mul_op.cc conv2d_op.cc DEPS ${FLUID_CORE_MODULES})
-nv_test(test_trt_activation_op SRCS test_activation_op.cc ${ENGINE_FILE} activation_op.cc
- DEPS ${FLUID_CORE_MODULES} activation_op)
+nv_test(test_trt_activation_op SRCS test_activation_op.cc activation_op.cc
+ DEPS ${FLUID_CORE_MODULES} activation_op tensorrt_engine)
nv_test(test_io_converter SRCS test_io_converter.cc io_converter.cc DEPS dynload_cuda dynamic_loader lod_tensor)
diff --git a/paddle/fluid/inference/tensorrt/engine.cc b/paddle/fluid/inference/tensorrt/engine.cc
index df123a5907..1c296e33a6 100644
--- a/paddle/fluid/inference/tensorrt/engine.cc
+++ b/paddle/fluid/inference/tensorrt/engine.cc
@@ -30,16 +30,24 @@ void TensorRTEngine::Build(const DescType& paddle_model) {
}
void TensorRTEngine::Execute(int batch_size) {
- infer_context_->enqueue(batch_size, buffers_.data(), *stream_, nullptr);
+ std::vector<void*> buffers;
+ for (auto& buf : buffers_) {
+ PADDLE_ENFORCE_NOT_NULL(buf.buffer, "buffer should be allocated");
+ PADDLE_ENFORCE_GT(buf.max_size, 0);
+ PADDLE_ENFORCE(buf.device == DeviceType::GPU);
+ buffers.push_back(buf.buffer);
+ }
+ infer_context_->enqueue(batch_size, buffers.data(), *stream_, nullptr);
cudaStreamSynchronize(*stream_);
}
TensorRTEngine::~TensorRTEngine() {
// clean buffer
- for (auto& buffer : buffers_) {
- if (buffer != nullptr) {
- PADDLE_ENFORCE_EQ(0, cudaFree(buffer));
- buffer = nullptr;
+ for (auto& buf : buffers_) {
+ if (buf.buffer != nullptr) {
+ PADDLE_ENFORCE_EQ(0, cudaFree(buf.buffer));
+ buf.buffer = nullptr;
+ buf.max_size = 0;
}
}
}
@@ -59,7 +67,7 @@ void TensorRTEngine::FreezeNetwork() {
infer_context_.reset(infer_engine_->createExecutionContext());
// allocate GPU buffers.
- buffers_.resize(buffer_sizes_.size(), nullptr);
+ buffers_.resize(buffer_sizes_.size());
for (auto& item : buffer_sizes_) {
if (item.second == 0) {
auto slot_offset = infer_engine_->getBindingIndex(item.first.c_str());
@@ -67,7 +75,11 @@ void TensorRTEngine::FreezeNetwork() {
infer_engine_->getBindingDataType(slot_offset))] *
AccumDims(infer_engine_->getBindingDimensions(slot_offset));
}
- PADDLE_ENFORCE_EQ(0, cudaMalloc(&buffer(item.first), item.second));
+ auto& buf = buffer(item.first);
+ CHECK(buf.buffer == nullptr); // buffer should be allocated only once.
+ PADDLE_ENFORCE_EQ(0, cudaMalloc(&buf.buffer, item.second));
+ buf.size = buf.max_size = item.second;
+ buf.device = DeviceType::GPU;
}
}
@@ -113,7 +125,7 @@ void TensorRTEngine::DeclareOutput(const std::string& name) {
}
void* TensorRTEngine::GetOutputInGPU(const std::string& name) {
- return buffer(name);
+ return buffer(name).buffer;
}
void TensorRTEngine::GetOutputInCPU(const std::string& name, void* dst,
@@ -123,11 +135,13 @@ void TensorRTEngine::GetOutputInCPU(const std::string& name, void* dst,
PADDLE_ENFORCE(it != buffer_sizes_.end());
PADDLE_ENFORCE_GT(it->second, 0);
PADDLE_ENFORCE_GE(max_size, it->second);
- PADDLE_ENFORCE_EQ(0, cudaMemcpyAsync(dst, buffer(name), it->second,
+ auto& buf = buffer(name);
+ PADDLE_ENFORCE_NOT_NULL(buf.buffer, "buffer should be allocated before");
+ PADDLE_ENFORCE_EQ(0, cudaMemcpyAsync(dst, buf.buffer, it->second,
cudaMemcpyDeviceToHost, *stream_));
}
-void*& TensorRTEngine::buffer(const std::string& name) {
+Buffer& TensorRTEngine::buffer(const std::string& name) {
PADDLE_ENFORCE(infer_engine_ != nullptr, "call FreezeNetwork first.");
auto it = buffer_sizes_.find(name);
PADDLE_ENFORCE(it != buffer_sizes_.end());
@@ -137,10 +151,12 @@ void*& TensorRTEngine::buffer(const std::string& name) {
void TensorRTEngine::SetInputFromCPU(const std::string& name, void* data,
size_t size) {
- void* buf = buffer(name);
- cudaMemcpyAsync(buf, data, size, cudaMemcpyHostToDevice, *stream_);
- PADDLE_ENFORCE_EQ(
- 0, cudaMemcpyAsync(buf, data, size, cudaMemcpyHostToDevice, *stream_));
+ auto& buf = buffer(name);
+ PADDLE_ENFORCE_NOT_NULL(buf.buffer);
+ PADDLE_ENFORCE_LE(size, buf.max_size, "buffer is too small");
+ PADDLE_ENFORCE(buf.device == DeviceType::GPU);
+ PADDLE_ENFORCE_EQ(0, cudaMemcpyAsync(buf.buffer, data, size,
+ cudaMemcpyHostToDevice, *stream_));
}
void TensorRTEngine::SetITensor(const std::string& name,
diff --git a/paddle/fluid/inference/tensorrt/engine.h b/paddle/fluid/inference/tensorrt/engine.h
index ec919b943d..b8298c6059 100644
--- a/paddle/fluid/inference/tensorrt/engine.h
+++ b/paddle/fluid/inference/tensorrt/engine.h
@@ -87,7 +87,9 @@ class TensorRTEngine : public EngineBase {
// these memory directly for acceleration, for example, output the converted
// data directly to the buffer to save data copy overhead.
// NOTE this should be used after calling `FreezeNetwork`.
- void*& buffer(const std::string& name);
+ Buffer& buffer(const std::string& name) override;
+
+ cudaStream_t* stream() { return stream_; }
// Fill an input from CPU memory with name and size.
void SetInputFromCPU(const std::string& name, void* data, size_t size);
@@ -116,7 +118,7 @@ class TensorRTEngine : public EngineBase {
cudaStream_t* stream_;
nvinfer1::ILogger& logger_;
- std::vector<void*> buffers_;
+ std::vector<Buffer> buffers_;
// max data size for the buffers.
std::unordered_map<std::string /*name*/, size_t /*max size*/> buffer_sizes_;
std::unordered_map<std::string /*name*/, nvinfer1::ITensor* /*ITensor*/>
From f093a7b332ceb43ca111c9db1a87baf83d6eb7fe Mon Sep 17 00:00:00 2001
From: Xin Pan <panxin.grad@gmail.com>
Date: Wed, 9 May 2018 18:16:36 +0800
Subject: [PATCH 033/195] allow inference test to generate timeline
generate timeline file
PYTHONPATH=/paddle/dev/my/build2/python/ python /paddle/dev/my/Paddle2/tools/timeline.py --profile_path=train=run_inference_profiler --timeline_path=/tmp/timeline_infer
visualize it
open url chrome://tracing
---
paddle/fluid/inference/tests/test_helper.h | 6 +++---
1 file changed, 3 insertions(+), 3 deletions(-)
diff --git a/paddle/fluid/inference/tests/test_helper.h b/paddle/fluid/inference/tests/test_helper.h
index af2a7a5620..2f391dc1e2 100644
--- a/paddle/fluid/inference/tests/test_helper.h
+++ b/paddle/fluid/inference/tests/test_helper.h
@@ -105,7 +105,7 @@ void TestInference(const std::string& dirname,
state = paddle::platform::ProfilerState::kCPU;
} else {
#ifdef PADDLE_WITH_CUDA
- state = paddle::platform::ProfilerState::kCUDA;
+ state = paddle::platform::ProfilerState::kAll;
// The default device_id of paddle::platform::CUDAPlace is 0.
// Users can get the device_id using:
// int device_id = place.GetDeviceId();
@@ -143,7 +143,7 @@ void TestInference(const std::string& dirname,
}
// Disable the profiler and print the timing information
paddle::platform::DisableProfiler(paddle::platform::EventSortingKey::kDefault,
- "load_program_profiler.txt");
+ "load_program_profiler");
paddle::platform::ResetProfiler();
// 3. Get the feed_target_names and fetch_target_names
@@ -208,7 +208,7 @@ void TestInference(const std::string& dirname,
// Disable the profiler and print the timing information
paddle::platform::DisableProfiler(
paddle::platform::EventSortingKey::kDefault,
- "run_inference_profiler.txt");
+ "run_inference_profiler");
paddle::platform::ResetProfiler();
}
From a2de156dfae0ee542fbb77a0a7c368030ca9c7c6 Mon Sep 17 00:00:00 2001
From: typhoonzero <typhoonzero1986@gmail.com>
Date: Wed, 9 May 2018 20:47:44 +0800
Subject: [PATCH 034/195] refine serde code
---
.../operators/detail/sendrecvop_utils.cc | 239 +++++++++---------
paddle/fluid/operators/detail/serde_test.cc | 6 +-
.../operators/detail/variable_response.cc | 40 +--
.../fluid/transpiler/distribute_transpiler.py | 86 ++++---
4 files changed, 193 insertions(+), 178 deletions(-)
diff --git a/paddle/fluid/operators/detail/sendrecvop_utils.cc b/paddle/fluid/operators/detail/sendrecvop_utils.cc
index d68cf467f7..e77c38f59a 100644
--- a/paddle/fluid/operators/detail/sendrecvop_utils.cc
+++ b/paddle/fluid/operators/detail/sendrecvop_utils.cc
@@ -29,129 +29,148 @@ namespace paddle {
namespace operators {
namespace detail {
+using VarMsg = sendrecv::VariableMessage;
+
+VarMsg::Type DataTypeToEnum(std::type_index type) {
+ if (typeid(platform::float16).hash_code() == type.hash_code()) {
+ return VarMsg::FP16;
+ } else if (typeid(const float).hash_code() == type.hash_code()) {
+ // CPPLint complains Using C-style cast. Use static_cast<float>() instead
+ // One fix to this is to replace float with const float because
+ // typeid(T) == typeid(const T)
+ // http://en.cppreference.com/w/cpp/language/typeid
+ return VarMsg::FP32;
+ } else if (typeid(const double).hash_code() == type.hash_code()) {
+ return VarMsg::FP64;
+ } else if (typeid(const int).hash_code() == type.hash_code()) {
+ return VarMsg::INT32;
+ } else if (typeid(const int64_t).hash_code() == type.hash_code()) {
+ return VarMsg::INT64;
+ } else if (typeid(const bool).hash_code() == type.hash_code()) {
+ return VarMsg::BOOL;
+ } else {
+ PADDLE_THROW("Not supported");
+ }
+}
+
+void GetTensorPayload(framework::Variable* var,
+ const platform::DeviceContext& ctx, VarMsg* request,
+ void** payload, size_t* payload_size) {
+ auto tensor = var->Get<framework::LoDTensor>();
+ // FIXME(wuyi): data types in send_recv.proto is not synced with
+ // framework.proto
+ request->set_data_type(DataTypeToEnum(tensor.type()));
+ for (auto& dim : framework::vectorize(tensor.dims())) {
+ request->add_dims(dim);
+ }
+ const framework::LoD lod = tensor.lod();
+ if (lod.size() > 0) {
+ request->set_lod_level(lod.size());
+ for (auto& each : lod) {
+ VarMsg::LodData* lod_inner = request->add_lod();
+ for (auto& d : each) {
+ lod_inner->add_lod_data(d);
+ }
+ }
+ }
+ if (platform::is_gpu_place(ctx.GetPlace())) {
+#ifdef PADDLE_WITH_CUDA
+ PADDLE_ENFORCE(platform::is_gpu_place(tensor.place()));
+ platform::CPUPlace cpu;
+ auto& gpu_dev_ctx = static_cast<const platform::CUDADeviceContext&>(ctx);
+ auto copy_size = tensor.numel() * framework::SizeOfType(tensor.type());
+ *payload = memory::Alloc(cpu, copy_size);
+
+ memory::Copy(cpu, *payload, boost::get<platform::CUDAPlace>(tensor.place()),
+ reinterpret_cast<const void*>(tensor.data<void>()), copy_size,
+ gpu_dev_ctx.stream());
+ ctx.Wait();
+#endif
+ } else {
+ *payload = tensor.data<void>();
+ }
+ *payload_size = tensor.numel() * framework::SizeOfType(tensor.type());
+}
+
+void GetSelectedRowsPayload(framework::Variable* var,
+ const platform::DeviceContext& ctx, VarMsg* request,
+ void** payload, size_t* payload_size) {
+ auto* slr = var->GetMutable<framework::SelectedRows>();
+ request->set_data_type(DataTypeToEnum(slr->value().type()));
+ request->set_lod_level(0);
+ request->set_slr_height(slr->height());
+
+ for (auto& dim : framework::vectorize(slr->value().dims())) {
+ request->add_dims(dim);
+ }
+
+ auto* tensor = slr->mutable_value();
+ if (platform::is_gpu_place(ctx.GetPlace())) {
+#ifdef PADDLE_WITH_CUDA
+ platform::CPUPlace cpu;
+ auto& gpu_dev_ctx = static_cast<const platform::CUDADeviceContext&>(ctx);
+ auto copy_size = tensor->numel() * framework::SizeOfType(tensor->type());
+ *payload = memory::Alloc(cpu, copy_size);
+ memory::Copy(cpu, *payload,
+ boost::get<platform::CUDAPlace>(tensor->place()),
+ reinterpret_cast<const void*>(tensor->data<void>()), copy_size,
+ gpu_dev_ctx.stream());
+ ctx.Wait();
+#endif
+ } else {
+ *payload = slr->mutable_value()->data<void>();
+ }
+ *payload_size = tensor->numel() * framework::SizeOfType(tensor->type());
+}
+
void SerializeToByteBuffer(const std::string& name, framework::Variable* var,
const platform::DeviceContext& ctx,
::grpc::ByteBuffer* msg,
const std::string& out_name) {
- using VarMsg = sendrecv::VariableMessage;
- // When using GPU, need to free the copied CPU buffer
- // when the ByteBuffer destroies
- // TODO(typhoonzero): add unref here, if we have dependent
- // parallelism execution, need to know when to free the tensor.
+ // Default DestroyCallback does nothing, When using GPU
+ // the CPU buffer need to be freed.
DestroyCallback destroy_callback = [](void* backing) {};
-
- auto buffer = std::unique_ptr<char[]>(new char[1024]);
- void* buf = buffer.get();
-
+ VarMsg request;
void* payload = nullptr;
size_t payload_size;
- ProtoEncodeHelper e(static_cast<char*>(buf), 1024);
+
+ request.set_varname(name);
// Note: normally the profiler is enabled in 1 trainer, hence only
// 1 trainer returns true for ShouldSendProfileState(). It tells PS
// servers the trainer's profiling state so that PS can follow the
// trainer.
- if (platform::ShouldSendProfileState()) {
- e.WriteBool(VarMsg::kProfileFieldNumber, platform::IsProfileEnabled());
+ request.set_profile(platform::IsProfileEnabled());
+ if (!out_name.empty()) {
+ request.set_out_varname(out_name);
}
- e.WriteString(VarMsg::kVarnameFieldNumber, name);
if (var->IsType<framework::LoDTensor>()) {
- e.WriteUint64(VarMsg::kTypeFieldNumber, 0);
+ request.set_type(::sendrecv::LOD_TENSOR);
+ GetTensorPayload(var, ctx, &request, &payload, &payload_size);
} else if (var->IsType<framework::SelectedRows>()) {
- e.WriteUint64(VarMsg::kTypeFieldNumber, 1);
+ request.set_type(::sendrecv::SELECTED_ROWS);
+ GetSelectedRowsPayload(var, ctx, &request, &payload, &payload_size);
+ } else {
+ PADDLE_THROW("Serialize does not support type: %s",
+ typeid(var->Type()).name());
}
- if (!out_name.empty()) {
- e.WriteString(VarMsg::kOutVarnameFieldNumber, out_name);
+ if (platform::is_gpu_place(ctx.GetPlace())) {
+ // GPU data is copied to CPU buffer when sending,
+ // free the buffer when possible.
+ destroy_callback = [](void* backing) {
+ platform::CPUPlace cpu;
+ memory::Free(cpu, backing);
+ };
}
- switch (framework::ToVarType(var->Type())) {
- case framework::proto::VarType_Type_LOD_TENSOR: {
- auto tensor = var->Get<framework::LoDTensor>();
- e.WriteUint64(VarMsg::kDataTypeFieldNumber,
- framework::ToDataType(tensor.type()));
- for (auto& dim : framework::vectorize(tensor.dims())) {
- e.WriteUint64(VarMsg::kDimsFieldNumber, dim);
- }
- auto lod = tensor.lod(); // std::vector<Vector<size_t>>
- if (lod.size() > 0) {
- e.WriteUint64(VarMsg::kLodLevelFieldNumber, lod.size());
-
- for (auto& each : lod) {
- e.WriteVarlengthBeginning(VarMsg::kLodFieldNumber,
- 2 + // tag + varintlength of submessage
- 1 + // kLodDataFieldNumber
- each.size());
- // auto copied from GPU
- for (auto& d : each) {
- e.WriteUint64(VarMsg::LodData::kLodDataFieldNumber, d);
- }
- }
- }
- if (platform::is_gpu_place(ctx.GetPlace())) {
-#ifdef PADDLE_WITH_CUDA
- PADDLE_ENFORCE(platform::is_gpu_place(tensor.place()));
- platform::CPUPlace cpu;
- auto& gpu_dev_ctx =
- static_cast<const platform::CUDADeviceContext&>(ctx);
- auto copy_size = tensor.numel() * framework::SizeOfType(tensor.type());
- payload = memory::Alloc(cpu, copy_size);
-
- memory::Copy(cpu, payload,
- boost::get<platform::CUDAPlace>(tensor.place()),
- reinterpret_cast<const void*>(tensor.data<void>()),
- copy_size, gpu_dev_ctx.stream());
- ctx.Wait();
- destroy_callback = [](void* backing) {
- platform::CPUPlace cpu;
- memory::Free(cpu, backing);
- };
-#endif
- } else {
- payload = tensor.data<void>();
- }
- payload_size = tensor.numel() * framework::SizeOfType(tensor.type());
- e.WriteVarlengthBeginning(VarMsg::kSerializedFieldNumber, payload_size);
- } break;
- case framework::proto::VarType_Type_SELECTED_ROWS: {
- // TODO(typhoonzero): selectedrows implement should not use unique_ptr
- auto* slr = var->GetMutable<framework::SelectedRows>();
- e.WriteUint64(VarMsg::kDataTypeFieldNumber,
- framework::ToDataType(slr->value().type()));
- for (auto& dim : framework::vectorize(slr->value().dims())) {
- e.WriteUint64(VarMsg::kDimsFieldNumber, dim);
- }
- e.WriteUint64(VarMsg::kLodLevelFieldNumber, 0);
- e.WriteUint64(VarMsg::kSlrHeightFieldNumber, slr->height());
- auto* tensor = slr->mutable_value();
- if (platform::is_gpu_place(ctx.GetPlace())) {
-#ifdef PADDLE_WITH_CUDA
- platform::CPUPlace cpu;
- auto& gpu_dev_ctx =
- static_cast<const platform::CUDADeviceContext&>(ctx);
- auto copy_size =
- tensor->numel() * framework::SizeOfType(tensor->type());
- payload = memory::Alloc(cpu, copy_size);
- memory::Copy(cpu, payload,
- boost::get<platform::CUDAPlace>(tensor->place()),
- reinterpret_cast<const void*>(tensor->data<void>()),
- copy_size, gpu_dev_ctx.stream());
- ctx.Wait();
- destroy_callback = [](void* backing) {
- platform::CPUPlace cpu;
- memory::Free(cpu, backing);
- };
-#endif
- } else {
- payload = slr->mutable_value()->data<void>();
- }
- payload_size = tensor->numel() * framework::SizeOfType(tensor->type());
- e.WriteVarlengthBeginning(VarMsg::kSerializedFieldNumber, payload_size);
- } break;
- default:
- PADDLE_THROW("Serialize does not support type: %s",
- typeid(var->Type()).name());
- break;
- }
+ std::string header;
+ request.AppendToString(&header);
+ auto buffer = std::unique_ptr<char[]>(new char[1024]);
+ void* buf = buffer.get();
+ ProtoEncodeHelper e(static_cast<char*>(buf), 1024);
+ e.WriteRawBytes(std::string(header.data(), header.size()));
+ e.WriteVarlengthBeginning(VarMsg::kSerializedFieldNumber, payload_size);
+
// steal reference of tensor data
::grpc::Slice slices[4]; // metadata, tensor, rows meta, rows
int num_slices = 2; // only SelectedRows have rows buffer
@@ -162,12 +181,9 @@ void SerializeToByteBuffer(const std::string& name, framework::Variable* var,
static_cast<char*>(payload)),
::grpc::Slice::STEAL_REF);
- if (framework::ToVarType(var->Type()) ==
- framework::proto::VarType_Type_SELECTED_ROWS) {
+ if (var->IsType<framework::SelectedRows>()) {
auto* slr = var->GetMutable<framework::SelectedRows>();
-
ProtoEncodeHelper e2(static_cast<char*>(buf), 128);
- // NOTE: rows is of type int64_t
size_t rows_memory_size =
slr->rows().size() * framework::SizeOfType(typeid(int64_t));
e2.WriteVarlengthBeginning(VarMsg::kRowsFieldNumber, rows_memory_size);
@@ -178,10 +194,7 @@ void SerializeToByteBuffer(const std::string& name, framework::Variable* var,
grpc_slice_new_with_user_data(
const_cast<void*>(
reinterpret_cast<const void*>(slr->rows().data())),
- rows_memory_size,
- [](void* backing) {
- // TODO(typhoonzero): add unref here, same as above.
- },
+ rows_memory_size, [](void* backing) {},
const_cast<char*>(
reinterpret_cast<const char*>(slr->rows().data()))),
::grpc::Slice::STEAL_REF);
diff --git a/paddle/fluid/operators/detail/serde_test.cc b/paddle/fluid/operators/detail/serde_test.cc
index e9eaaf1cbc..15892295e6 100644
--- a/paddle/fluid/operators/detail/serde_test.cc
+++ b/paddle/fluid/operators/detail/serde_test.cc
@@ -117,11 +117,11 @@ void RunTestLodTensor(platform::Place place, int from_type = 0) {
// serialize var to ByteBuffer
framework::Variable var;
auto* tensor = var.GetMutable<framework::LoDTensor>();
- tensor->Resize(framework::make_ddim({4, 8, 4, 2}));
+ tensor->Resize(framework::make_ddim({512, 8, 4, 2}));
framework::LoD lod;
lod.push_back(framework::Vector<size_t>({1, 3, 8}));
tensor->set_lod(lod);
- int tensor_numel = 4 * 8 * 4 * 2;
+ int tensor_numel = 512 * 8 * 4 * 2;
platform::DeviceContextPool& pool = platform::DeviceContextPool::Instance();
auto& ctx = *pool.Get(place);
tensor->mutable_data<float>(place);
@@ -142,7 +142,7 @@ void RunTestLodTensor(platform::Place place, int from_type = 0) {
EXPECT_TRUE(varmsg.ParseFromString(tmp));
EXPECT_EQ(varmsg.varname(), "myvar");
EXPECT_EQ(varmsg.type(), 0);
- EXPECT_EQ(varmsg.dims()[0], 4);
+ EXPECT_EQ(varmsg.dims()[0], 512);
EXPECT_EQ(varmsg.dims()[1], 8);
EXPECT_EQ(varmsg.dims()[2], 4);
EXPECT_EQ(varmsg.dims()[3], 2);
diff --git a/paddle/fluid/operators/detail/variable_response.cc b/paddle/fluid/operators/detail/variable_response.cc
index f4a374d56d..99602a05d0 100644
--- a/paddle/fluid/operators/detail/variable_response.cc
+++ b/paddle/fluid/operators/detail/variable_response.cc
@@ -210,15 +210,15 @@ bool ParseLodData(::google::protobuf::io::CodedInputStream* input,
}
if (wt == WIRETYPE_LENGTH_DELIMITED) {
- int length = 0;
- if (!input->ReadVarintSizeAsInt(&length)) {
+ int num_bytes = 0;
+ if (!input->ReadVarintSizeAsInt(&num_bytes)) {
return tag;
}
-
- for (int i = 0; i < length; i++) {
+ int start_pos = input->CurrentPosition();
+ while (input->CurrentPosition() - start_pos < num_bytes) {
uint64_t v;
if (!input->ReadVarint64(&v)) {
- return false;
+ return tag;
}
lod->push_back(v);
}
@@ -275,8 +275,8 @@ int VariableResponse::Parse(Source* source) {
break;
}
case sendrecv::VariableMessage::kTypeFieldNumber: {
- uint64_t v;
- if ((wt != WIRETYPE_VARINT) || !input.ReadVarint64(&v)) {
+ uint32_t v;
+ if ((wt != WIRETYPE_VARINT) || !input.ReadVarint32(&v)) {
return tag;
}
@@ -284,8 +284,8 @@ int VariableResponse::Parse(Source* source) {
break;
}
case sendrecv::VariableMessage::kDataTypeFieldNumber: {
- uint64_t v = 0;
- if ((wt != WIRETYPE_VARINT) || !input.ReadVarint64(&v)) {
+ uint32_t v = 0;
+ if ((wt != WIRETYPE_VARINT) || !input.ReadVarint32(&v)) {
return tag;
}
@@ -305,11 +305,12 @@ int VariableResponse::Parse(Source* source) {
// packed
if (wt == WIRETYPE_LENGTH_DELIMITED) {
- int length = 0;
- if (!input.ReadVarintSizeAsInt(&length)) {
+ int num_bytes = 0;
+ if (!input.ReadVarintSizeAsInt(&num_bytes)) {
return tag;
}
- for (int i = 0; i < length; i++) {
+ int start_pos = input.CurrentPosition();
+ while (input.CurrentPosition() - start_pos < num_bytes) {
uint64_t v;
if (!input.ReadVarint64(&v)) {
return tag;
@@ -318,7 +319,6 @@ int VariableResponse::Parse(Source* source) {
}
break;
}
-
return tag;
}
case sendrecv::VariableMessage::kLodLevelFieldNumber: {
@@ -372,9 +372,9 @@ int VariableResponse::Parse(Source* source) {
meta_.varname() != "",
"meta info should be got first!");
- int length = 0;
+ int num_bytes = 0;
if (wt != WIRETYPE_LENGTH_DELIMITED ||
- !ReadVarintSizeAsInt(&input, &length)) {
+ !ReadVarintSizeAsInt(&input, &num_bytes)) {
return tag;
}
@@ -382,14 +382,14 @@ int VariableResponse::Parse(Source* source) {
if (meta_.type() == sendrecv::LOD_TENSOR) {
PADDLE_ENFORCE(meta_.lod_size() >= 0,
"lod info should be got first!");
- if (!CopyLodTensorData(&input, *dev_ctx_, dims, length)) {
+ if (!CopyLodTensorData(&input, *dev_ctx_, dims, num_bytes)) {
return tag;
}
break;
}
if (meta_.type() == sendrecv::SELECTED_ROWS) {
- if (!CopySelectRowsTensorData(&input, *dev_ctx_, dims, length)) {
+ if (!CopySelectRowsTensorData(&input, *dev_ctx_, dims, num_bytes)) {
return tag;
}
break;
@@ -403,13 +403,13 @@ int VariableResponse::Parse(Source* source) {
meta_.varname() != "",
"meta info should be got first!");
- int length = 0;
+ int num_bytes = 0;
if (wt != WIRETYPE_LENGTH_DELIMITED ||
- !ReadVarintSizeAsInt(&input, &length)) {
+ !ReadVarintSizeAsInt(&input, &num_bytes)) {
return tag;
}
- if (!CopySelectRowsData(&input, *dev_ctx_, length)) {
+ if (!CopySelectRowsData(&input, *dev_ctx_, num_bytes)) {
return tag;
}
break;
diff --git a/python/paddle/fluid/transpiler/distribute_transpiler.py b/python/paddle/fluid/transpiler/distribute_transpiler.py
index 640ac9f085..b45cb987d8 100644
--- a/python/paddle/fluid/transpiler/distribute_transpiler.py
+++ b/python/paddle/fluid/transpiler/distribute_transpiler.py
@@ -18,7 +18,9 @@ import math
import distributed_splitter as splitter
from .. import core
-from ..framework import Program, default_main_program, Variable, Parameter
+from ..framework import Program, default_main_program, \
+ default_startup_program, \
+ Variable, Parameter, grad_var_name
LOOKUP_TABLE_TYPE = "lookup_table"
LOOKUP_TABLE_GRAD_TYPE = "lookup_table_grad"
@@ -153,43 +155,43 @@ class DistributeTranspiler:
split_method=splitter.round_robin,
sync_mode=True):
"""
- Transpile the program to distributed data-parallelism programs.
- The main_program will be transformed to use a remote parameter server
- to do parameter optimization. And the optimization graph will be put
- into a parameter server program.
-
- Use different methods to split trainable variables to different
- parameter servers.
-
- Steps to transpile trainer:
- 1. split variable to multiple blocks, aligned by product(dim[1:]) (width).
- 2. rename splited grad variables to add trainer_id suffix ".trainer_%d".
- 3. modify trainer program add split_op to each grad variable.
- 4. append send_op to send splited variables to server and fetch
- params(splited blocks or origin param) from server.
- 5. append concat_op to merge splited blocks to update local weights.
-
- Steps to transpile pserver:
- 1. create new program for parameter server.
- 2. create params and grad variables that assigned to current server instance.
- 3. create a sub-block in the server side program
- 4. append ops that should run on current server instance.
- 5. add listen_and_serv op
-
- :param trainer_id: one unique id for each trainer in a job.
- :type trainer_id: int
- :param program: program to transpile, default is default_main_program
- :type program: Program
- :param pservers: parameter server endpoints like "m1:6174,m2:6174"
- :type pservers: string
- :param trainers: total number of workers/trainers in the job
- :type trainers: int
- :param split_method: A function to determin how to split variables
- to different servers equally.
- :type split_method: function
- :type sync_mode: boolean default True
- :param sync_mode: if sync_mode is set True, it means that dist transpiler
- will transpile the program into sync_mode pserver and trainer program.
+ Transpile the program to distributed data-parallelism programs.
+ The main_program will be transformed to use a remote parameter server
+ to do parameter optimization. And the optimization graph will be put
+ into a parameter server program.
+
+ Use different methods to split trainable variables to different
+ parameter servers.
+
+ Steps to transpile trainer:
+ 1. split variable to multiple blocks, aligned by product(dim[1:]) (width).
+ 2. rename splited grad variables to add trainer_id suffix ".trainer_%d".
+ 3. modify trainer program add split_op to each grad variable.
+ 4. append send_op to send splited variables to server and fetch
+ params(splited blocks or origin param) from server.
+ 5. append concat_op to merge splited blocks to update local weights.
+
+ Steps to transpile pserver:
+ 1. create new program for parameter server.
+ 2. create params and grad variables that assigned to current server instance.
+ 3. create a sub-block in the server side program
+ 4. append ops that should run on current server instance.
+ 5. add listen_and_serv op
+
+ :param trainer_id: one unique id for each trainer in a job.
+ :type trainer_id: int
+ :param program: program to transpile, default is default_main_program
+ :type program: Program
+ :param pservers: parameter server endpoints like "m1:6174,m2:6174"
+ :type pservers: string
+ :param trainers: total number of workers/trainers in the job
+ :type trainers: int
+ :param split_method: A function to determin how to split variables
+ to different servers equally.
+ :type split_method: function
+ :type sync_mode: boolean default True
+ :param sync_mode: if sync_mode is set True, it means that dist transpiler
+ will transpile the program into sync_mode pserver and trainer program.
"""
assert (callable(split_method))
if program is None:
@@ -244,7 +246,7 @@ class DistributeTranspiler:
]
grad_list = [
grad for grad in grad_list
- if grad.name != framework.grad_var_name(self.table_name)
+ if grad.name != grad_var_name(self.table_name)
]
self.table_param_grad = [
param_grad for param_grad in params_grads
@@ -494,7 +496,7 @@ class DistributeTranspiler:
were split to several blocks.
"""
s_prog = Program()
- orig_s_prog = framework.default_startup_program()
+ orig_s_prog = default_startup_program()
params = self.param_grad_ep_mapping[endpoint]["params"]
def _get_splited_name_and_shape(varname):
@@ -619,7 +621,7 @@ class DistributeTranspiler:
# 2. add split_ids_op and send_vars_op to send gradient to pservers
# there should only be one table_name
all_ops = program.global_block().ops
- table_grad_name = framework.grad_var_name(self.table_name)
+ table_grad_name = grad_var_name(self.table_name)
for op in all_ops:
if table_grad_name in op.output_arg_names:
op_index = list(all_ops).index(op)
@@ -692,7 +694,7 @@ class DistributeTranspiler:
persistable=True)
grad_var = _clone_var(
pserver_program.global_block(),
- self.origin_program.global_block().vars[framework.grad_var_name(
+ self.origin_program.global_block().vars[grad_var_name(
self.table_name)],
persistable=False)
From 830532213a120ce9a5645cb3bba4797b4447b50f Mon Sep 17 00:00:00 2001
From: chengduoZH <zhaochengduo@163.com>
Date: Wed, 9 May 2018 14:44:02 +0800
Subject: [PATCH 035/195] extract method from broadcast::RunImpl
---
.../framework/details/broadcast_op_handle.cc | 56 ++++++++++++-------
.../framework/details/broadcast_op_handle.h | 3 +
.../fluid/framework/details/op_handle_base.h | 8 ++-
.../framework/details/reduce_op_handle.cc | 20 ++++---
.../fluid/framework/details/send_op_handle.cc | 2 +-
5 files changed, 56 insertions(+), 33 deletions(-)
diff --git a/paddle/fluid/framework/details/broadcast_op_handle.cc b/paddle/fluid/framework/details/broadcast_op_handle.cc
index f176e4e159..d5ca061944 100644
--- a/paddle/fluid/framework/details/broadcast_op_handle.cc
+++ b/paddle/fluid/framework/details/broadcast_op_handle.cc
@@ -48,29 +48,9 @@ void BroadcastOpHandle::RunImpl() {
auto *in_var =
var_scopes.at(in_var_handle->scope_idx_)->FindVar(in_var_handle->name_);
PADDLE_ENFORCE_NOT_NULL(in_var);
-
Tensor &in_tensor = VariableVisitor::GetMutableTensor(in_var);
- // NOTE: The tensors' Place of input and output must be all on GPU or all on
- // CPU.
- for (auto *out_var_handle : out_var_handles) {
- if (out_var_handle->IsTheSameVar(*in_var_handle)) {
- continue;
- }
- auto t_out_p = out_var_handle->place_;
- auto *out_var = var_scopes.at(out_var_handle->scope_idx_)
- ->FindVar(out_var_handle->name_);
- PADDLE_ENFORCE_NOT_NULL(out_var);
- if (platform::is_gpu_place(in_tensor.place())) {
- PADDLE_ENFORCE(platform::is_gpu_place(t_out_p),
- "Places of input and output must be all on GPU.");
- } else {
- t_out_p = platform::CPUPlace();
- }
- VariableVisitor::ShareDimsAndLoD(*in_var, out_var);
- VariableVisitor::GetMutableTensor(out_var).mutable_data(t_out_p,
- in_tensor.type());
- }
+ InitOutputValue(*in_var_handle, out_var_handles);
if (platform::is_cpu_place(in_tensor.place())) {
for (auto *out_var_handle : out_var_handles) {
@@ -145,6 +125,40 @@ void BroadcastOpHandle::RunImpl() {
}
}
+void BroadcastOpHandle::InitOutputValue(
+ const VarHandle &in_var_handle,
+ const std::vector<VarHandle *> &out_var_handles) const {
+ std::vector<const Scope *> var_scopes;
+ for (auto *s : local_scopes_) {
+ var_scopes.emplace_back(s->FindVar(kLocalExecScopeName)->Get<Scope *>());
+ }
+ auto *in_var =
+ var_scopes.at(in_var_handle.scope_idx_)->FindVar(in_var_handle.name_);
+
+ Tensor &in_tensor = VariableVisitor::GetMutableTensor(in_var);
+
+ // NOTE: The tensors' Place of input and output must be all on GPU or all on
+ // CPU.
+ for (auto *out_var_handle : out_var_handles) {
+ if (out_var_handle->IsTheSameVar(in_var_handle)) {
+ continue;
+ }
+ auto t_out_p = out_var_handle->place_;
+ auto *out_var = var_scopes.at(out_var_handle->scope_idx_)
+ ->FindVar(out_var_handle->name_);
+ PADDLE_ENFORCE_NOT_NULL(out_var);
+ if (is_gpu_place(in_tensor.place())) {
+ PADDLE_ENFORCE(platform::is_gpu_place(t_out_p),
+ "Places of input and output must be all on GPU.");
+ } else {
+ t_out_p = platform::CPUPlace();
+ }
+ VariableVisitor::ShareDimsAndLoD(*in_var, out_var);
+ VariableVisitor::GetMutableTensor(out_var).mutable_data(t_out_p,
+ in_tensor.type());
+ }
+}
+
std::string BroadcastOpHandle::Name() const { return "broadcast"; }
} // namespace details
} // namespace framework
diff --git a/paddle/fluid/framework/details/broadcast_op_handle.h b/paddle/fluid/framework/details/broadcast_op_handle.h
index 48e356af4b..629aa00cb8 100644
--- a/paddle/fluid/framework/details/broadcast_op_handle.h
+++ b/paddle/fluid/framework/details/broadcast_op_handle.h
@@ -64,6 +64,9 @@ struct BroadcastOpHandle : public OpHandleBase {
#ifdef PADDLE_WITH_CUDA
const platform::NCCLContextMap *nccl_ctxs_;
#endif
+
+ void InitOutputValue(const VarHandle &in_var_handle,
+ const std::vector<VarHandle *> &out_var_handles) const;
};
} // namespace details
} // namespace framework
diff --git a/paddle/fluid/framework/details/op_handle_base.h b/paddle/fluid/framework/details/op_handle_base.h
index 3d4a093125..fe1735d05d 100644
--- a/paddle/fluid/framework/details/op_handle_base.h
+++ b/paddle/fluid/framework/details/op_handle_base.h
@@ -44,10 +44,14 @@ class OpHandleBase {
void AddOutput(VarHandleBase *out);
- // Wait inputs are generated, this Wait is asynchronous operation.
+ // This method adds the wait events of all the input on all the device
+ // context.
+ // NODE: This Wait is asynchronous operation.
virtual void WaitInputVarGenerated();
- // Wait inputs are generated, this Wait is asynchronous operation.
+ // This method adds the wait events of all the input on the specified device
+ // context.
+ // NODE: This Wait is asynchronous operation.
virtual void WaitInputVarGenerated(const platform::Place &place);
virtual bool NeedWait(VarHandleBase *in_var);
diff --git a/paddle/fluid/framework/details/reduce_op_handle.cc b/paddle/fluid/framework/details/reduce_op_handle.cc
index f653064ade..7160e346da 100644
--- a/paddle/fluid/framework/details/reduce_op_handle.cc
+++ b/paddle/fluid/framework/details/reduce_op_handle.cc
@@ -80,19 +80,21 @@ void ReduceOpHandle::RunImpl() {
}
if (pre_in_var->IsType<framework::SelectedRows>()) {
- std::vector<const SelectedRows *> in_selected_rows =
- GetInputValues<SelectedRows>(in_var_handles, var_scopes);
-
- GatherSelectedRows(in_selected_rows, in_places, dev_ctxes_, t_out_p,
- out_var->GetMutable<framework::SelectedRows>());
+ this->RunAndRecordEvent([&] {
+ std::vector<const SelectedRows *> in_selected_rows =
+ GetInputValues<SelectedRows>(in_var_handles, var_scopes);
+ GatherSelectedRows(in_selected_rows, in_places, dev_ctxes_, t_out_p,
+ out_var->GetMutable<framework::SelectedRows>());
+ });
} else {
std::vector<const LoDTensor *> lod_tensors =
GetInputValues<LoDTensor>(in_var_handles, var_scopes);
-
if (paddle::platform::is_cpu_place(lod_tensors[0]->place())) {
- ReduceLoDTensor func(lod_tensors,
- out_var->GetMutable<framework::LoDTensor>());
- VisitDataType(ToDataType(lod_tensors[0]->type()), func);
+ this->RunAndRecordEvent([&] {
+ ReduceLoDTensor func(lod_tensors,
+ out_var->GetMutable<framework::LoDTensor>());
+ VisitDataType(ToDataType(lod_tensors[0]->type()), func);
+ });
} else if (paddle::platform::is_gpu_place(lod_tensors[0]->place())) {
#ifdef PADDLE_WITH_CUDA
auto pre_in = pre_in_var->Get<framework::LoDTensor>();
diff --git a/paddle/fluid/framework/details/send_op_handle.cc b/paddle/fluid/framework/details/send_op_handle.cc
index ee4beb5f9b..01f3a9df76 100644
--- a/paddle/fluid/framework/details/send_op_handle.cc
+++ b/paddle/fluid/framework/details/send_op_handle.cc
@@ -27,7 +27,7 @@ SendOpHandle::SendOpHandle(const framework::OpDesc &op_desc,
void SendOpHandle::RunImpl() {
// Wait input done
- WaitInputVarGenerated();
+ WaitInputVarGenerated(place_);
auto &tmp_scope = local_scope_->FindVar(kLocalExecScopeName)->Get<Scope *>();
// FIXME(wuyi): can not use RunAndRecordEvent here, for it will cause dead
// lock.
From 0fed3db3eb7111599fbb0acb9a2831f8a91ea55c Mon Sep 17 00:00:00 2001
From: Jeff Wang <wangjeff@baidu.com>
Date: Wed, 9 May 2018 14:05:45 -0700
Subject: [PATCH 036/195] Put all new tests under high-level-api (#10534)
* Put all new tests under high-level-api
* be consistent with the naming
---
.../image_classification/notest_image_classification_resnet.py | 0
.../image_classification/notest_image_classification_vgg.py | 0
.../label_semantic_roles/no_test_label_semantic_roles.py | 0
.../recognize_digits}/notest_recognize_digits_conv.py | 0
.../recognize_digits}/notest_recognize_digits_mlp.py | 0
.../notest_understand_sentiment_stacked_lstm.py | 0
.../{ => high-level-api}/word2vec/no_test_word2vec_new_api.py | 0
7 files changed, 0 insertions(+), 0 deletions(-)
rename python/paddle/fluid/tests/book/{ => high-level-api}/image_classification/notest_image_classification_resnet.py (100%)
rename python/paddle/fluid/tests/book/{ => high-level-api}/image_classification/notest_image_classification_vgg.py (100%)
rename python/paddle/fluid/tests/book/{ => high-level-api}/label_semantic_roles/no_test_label_semantic_roles.py (100%)
rename python/paddle/fluid/tests/book/{notest_recognize_digits => high-level-api/recognize_digits}/notest_recognize_digits_conv.py (100%)
rename python/paddle/fluid/tests/book/{notest_recognize_digits => high-level-api/recognize_digits}/notest_recognize_digits_mlp.py (100%)
rename python/paddle/fluid/tests/book/{ => high-level-api}/understand_sentiment/notest_understand_sentiment_stacked_lstm.py (100%)
rename python/paddle/fluid/tests/book/{ => high-level-api}/word2vec/no_test_word2vec_new_api.py (100%)
diff --git a/python/paddle/fluid/tests/book/image_classification/notest_image_classification_resnet.py b/python/paddle/fluid/tests/book/high-level-api/image_classification/notest_image_classification_resnet.py
similarity index 100%
rename from python/paddle/fluid/tests/book/image_classification/notest_image_classification_resnet.py
rename to python/paddle/fluid/tests/book/high-level-api/image_classification/notest_image_classification_resnet.py
diff --git a/python/paddle/fluid/tests/book/image_classification/notest_image_classification_vgg.py b/python/paddle/fluid/tests/book/high-level-api/image_classification/notest_image_classification_vgg.py
similarity index 100%
rename from python/paddle/fluid/tests/book/image_classification/notest_image_classification_vgg.py
rename to python/paddle/fluid/tests/book/high-level-api/image_classification/notest_image_classification_vgg.py
diff --git a/python/paddle/fluid/tests/book/label_semantic_roles/no_test_label_semantic_roles.py b/python/paddle/fluid/tests/book/high-level-api/label_semantic_roles/no_test_label_semantic_roles.py
similarity index 100%
rename from python/paddle/fluid/tests/book/label_semantic_roles/no_test_label_semantic_roles.py
rename to python/paddle/fluid/tests/book/high-level-api/label_semantic_roles/no_test_label_semantic_roles.py
diff --git a/python/paddle/fluid/tests/book/notest_recognize_digits/notest_recognize_digits_conv.py b/python/paddle/fluid/tests/book/high-level-api/recognize_digits/notest_recognize_digits_conv.py
similarity index 100%
rename from python/paddle/fluid/tests/book/notest_recognize_digits/notest_recognize_digits_conv.py
rename to python/paddle/fluid/tests/book/high-level-api/recognize_digits/notest_recognize_digits_conv.py
diff --git a/python/paddle/fluid/tests/book/notest_recognize_digits/notest_recognize_digits_mlp.py b/python/paddle/fluid/tests/book/high-level-api/recognize_digits/notest_recognize_digits_mlp.py
similarity index 100%
rename from python/paddle/fluid/tests/book/notest_recognize_digits/notest_recognize_digits_mlp.py
rename to python/paddle/fluid/tests/book/high-level-api/recognize_digits/notest_recognize_digits_mlp.py
diff --git a/python/paddle/fluid/tests/book/understand_sentiment/notest_understand_sentiment_stacked_lstm.py b/python/paddle/fluid/tests/book/high-level-api/understand_sentiment/notest_understand_sentiment_stacked_lstm.py
similarity index 100%
rename from python/paddle/fluid/tests/book/understand_sentiment/notest_understand_sentiment_stacked_lstm.py
rename to python/paddle/fluid/tests/book/high-level-api/understand_sentiment/notest_understand_sentiment_stacked_lstm.py
diff --git a/python/paddle/fluid/tests/book/word2vec/no_test_word2vec_new_api.py b/python/paddle/fluid/tests/book/high-level-api/word2vec/no_test_word2vec_new_api.py
similarity index 100%
rename from python/paddle/fluid/tests/book/word2vec/no_test_word2vec_new_api.py
rename to python/paddle/fluid/tests/book/high-level-api/word2vec/no_test_word2vec_new_api.py
From 0446220e0143afd9a6fafe600c645d9fd010333f Mon Sep 17 00:00:00 2001
From: Lei Wang <bestwanglei@gmail.com>
Date: Wed, 9 May 2018 16:54:37 -0700
Subject: [PATCH 037/195] CI: rerun failed tests. (#10536)
* CI: rerun failed tests.
* fix check style error.
---
paddle/fluid/inference/tensorrt/test_engine.cc | 2 +-
paddle/scripts/docker/build.sh | 7 +++++++
paddle/scripts/paddle_build.sh | 8 ++++++++
paddle/scripts/paddle_docker_build.sh | 2 +-
4 files changed, 17 insertions(+), 2 deletions(-)
diff --git a/paddle/fluid/inference/tensorrt/test_engine.cc b/paddle/fluid/inference/tensorrt/test_engine.cc
index 69dbb9a3f2..e635f0f87d 100644
--- a/paddle/fluid/inference/tensorrt/test_engine.cc
+++ b/paddle/fluid/inference/tensorrt/test_engine.cc
@@ -98,7 +98,7 @@ TEST_F(TensorRTEngineTest, add_layer_multi_dim) {
float x_v[2] = {1.0, 2.0};
engine_->SetInputFromCPU("x", reinterpret_cast<void*>(&x_v),
- 2 * sizeof(float));
+ 2 * sizeof(float));
engine_->Execute(1);
LOG(INFO) << "to get output";
diff --git a/paddle/scripts/docker/build.sh b/paddle/scripts/docker/build.sh
index 7e00bd3848..c63b57ce40 100755
--- a/paddle/scripts/docker/build.sh
+++ b/paddle/scripts/docker/build.sh
@@ -100,7 +100,14 @@ function run_test() {
Running unit tests ...
========================================
EOF
+ set +e
ctest --output-on-failure
+ if [ $? != 0 ]; then
+ set -e
+ ctest --output-on-failure --rerun-failed
+ set +e
+ fi
+ set -e
# make install should also be test when unittest
make install -j `nproc`
pip install /usr/local/opt/paddle/share/wheels/*.whl
diff --git a/paddle/scripts/paddle_build.sh b/paddle/scripts/paddle_build.sh
index 1595cc9e8a..245b580bdf 100755
--- a/paddle/scripts/paddle_build.sh
+++ b/paddle/scripts/paddle_build.sh
@@ -299,7 +299,14 @@ function run_test() {
Running unit tests ...
========================================
EOF
+ set +e
ctest --output-on-failure
+ if [ $? != 0 ]; then
+ set -e
+ ctest --output-on-failure --rerun-failed
+ set +e
+ fi
+ set -e
# make install should also be test when unittest
make install -j `nproc`
pip install /usr/local/opt/paddle/share/wheels/*.whl
@@ -467,6 +474,7 @@ EOF
}
function main() {
+ set -e
local CMD=$1
init
case $CMD in
diff --git a/paddle/scripts/paddle_docker_build.sh b/paddle/scripts/paddle_docker_build.sh
index ddae9f19a2..7f5f7902bb 100755
--- a/paddle/scripts/paddle_docker_build.sh
+++ b/paddle/scripts/paddle_docker_build.sh
@@ -59,7 +59,7 @@ EOL
if [ ! -d "${HOME}/.ccache" ]; then
mkdir ${HOME}/.ccache
fi
- set -x
+ set -ex
${DOCKER_CMD} run -it \
--name $CONTAINER_ID \
${DOCKER_ENV} \
From 61eb3aa6b36a4e25b8b9a1edc2a76618204be4fd Mon Sep 17 00:00:00 2001
From: Lei Wang <bestwanglei@gmail.com>
Date: Tue, 8 May 2018 20:32:44 -0700
Subject: [PATCH 038/195] Dockerfile: fix production dockefile when
WITH_GOLONG=OFF.
---
paddle/scripts/paddle_build.sh | 14 ++++++++++----
1 file changed, 10 insertions(+), 4 deletions(-)
diff --git a/paddle/scripts/paddle_build.sh b/paddle/scripts/paddle_build.sh
index 245b580bdf..5363cf6865 100755
--- a/paddle/scripts/paddle_build.sh
+++ b/paddle/scripts/paddle_build.sh
@@ -405,7 +405,7 @@ function gen_dockerfile() {
cat <<EOF
========================================
- Generate /paddle/build/Dockerfile ...
+ Generate ${PADDLE_ROOT}/build/Dockerfile ...
========================================
EOF
@@ -429,7 +429,7 @@ EOF
CMD='"true"'
fi
- cat >> /paddle/build/Dockerfile <<EOF
+ cat >> ${PADDLE_ROOT}/build/Dockerfile <<EOF
ADD python/dist/*.whl /
# run paddle version to install python packages first
RUN apt-get update &&\
@@ -443,8 +443,14 @@ EOF
${DOCKERFILE_CUDNN_DSO}
${DOCKERFILE_GPU_ENV}
ENV NCCL_LAUNCH_MODE PARALLEL
- ADD go/cmd/pserver/pserver /usr/bin/
- ADD go/cmd/master/master /usr/bin/
+EOF
+ if [[ ${WITH_GOLANG:-OFF} == "ON" ]]; then
+ cat >> ${PADDLE_ROOT}/build/Dockerfile <<EOF
+ ADD go/cmd/pserver/pserver /usr/bin/
+ ADD go/cmd/master/master /usr/bin/
+EOF
+ fi
+ cat >> ${PADDLE_ROOT}/build/Dockerfile <<EOF
# default command shows the paddle version and exit
CMD [${CMD}]
EOF
From 55831575afd0ac42cad33b320b913d4888e3cc29 Mon Sep 17 00:00:00 2001
From: Xi Chen <putcncx@gmail.com>
Date: Wed, 9 May 2018 17:18:16 -0700
Subject: [PATCH 039/195] save metrics data to csv file
---
.../aws_benchmarking/server/cluster_master.py | 42 +++++++++++++++++++
1 file changed, 42 insertions(+)
diff --git a/tools/aws_benchmarking/server/cluster_master.py b/tools/aws_benchmarking/server/cluster_master.py
index 1333a942bf..a9b2484654 100644
--- a/tools/aws_benchmarking/server/cluster_master.py
+++ b/tools/aws_benchmarking/server/cluster_master.py
@@ -20,6 +20,7 @@ import time
import threading
import logging
import copy
+import csv
import netaddr
import boto3
@@ -136,6 +137,12 @@ parser.add_argument(
parser.add_argument(
'--master_server_ip', type=str, default="", help="master server private ip")
+parser.add_argument(
+ '--metric_data_identifier',
+ type=str,
+ default="**metrics_data: ",
+ help="key string to identify metrics data")
+
parser.add_argument(
'--no_clean_up',
type=str2bool,
@@ -155,6 +162,11 @@ logging.basicConfig(
log_files = ["master.log"]
+metrics = {}
+
+metrics_csv_file_name = "metrics.csv"
+is_metrics_file_created = False
+
def create_subnet():
# if no vpc id provided, list vpcs
@@ -329,12 +341,42 @@ def create_pservers():
cleanup(args.task_name)
+def save_metrics_data(str_msg):
+ #parse msg
+ logging.info("found metrics data, saving it to csv file")
+ global is_metrics_file_created
+ metrics_raw = str_msg.split(",")
+ with open(args.log_path + metrics_csv_file_name, 'a') as csvfile:
+ csv_fieldnames = []
+ csv_write_data = {}
+ for metric in metrics_raw:
+ metric_data = metric.split("=")
+ metric_key = metric_data[0].strip()
+ metric_val = float(metric_data[1].strip())
+ if not metric_key in metrics:
+ metrics[metric_key] = []
+ metric_repo = metrics[metric_key]
+ metric_repo.append(metric_val)
+ csv_fieldnames.append(metric_key)
+ csv_write_data[metric_key] = metric_val
+ writer = csv.DictWriter(csvfile, fieldnames=csv_fieldnames)
+ if not is_metrics_file_created:
+ writer.writeheader()
+ is_metrics_file_created = True
+ writer.writerow(csv_write_data)
+ logging.info("csv file appended")
+
+
def log_to_file(source, filename):
if not filename in log_files:
log_files.append(filename)
with open(args.log_path + filename, "a") as log_file:
for line in iter(source.readline, ""):
log_file.write(line)
+ if (line.startswith(args.metric_data_identifier)):
+ #found key data, trying to add to csv
+ line = line.replace(args.metric_data_identifier, "")
+ save_metrics_data(line)
def parse_command(command_raw, defaults={}):
From dcb77813aa2e9fa949971c1c53ff38d5149a8974 Mon Sep 17 00:00:00 2001
From: Xin Pan <panxin.grad@gmail.com>
Date: Thu, 10 May 2018 09:34:10 +0800
Subject: [PATCH 040/195] Revert "CI: rerun failed tests. (#10536)"
This reverts commit 0446220e0143afd9a6fafe600c645d9fd010333f.
Reason:
Rerun failed test hides flaky test.
Flaky test can be bugs, for example, race condition.
Test shouldn't be flaky, if a test is flaky, it should be fixed.
---
paddle/fluid/inference/tensorrt/test_engine.cc | 2 +-
paddle/scripts/docker/build.sh | 7 -------
paddle/scripts/paddle_build.sh | 8 --------
paddle/scripts/paddle_docker_build.sh | 2 +-
4 files changed, 2 insertions(+), 17 deletions(-)
diff --git a/paddle/fluid/inference/tensorrt/test_engine.cc b/paddle/fluid/inference/tensorrt/test_engine.cc
index e635f0f87d..69dbb9a3f2 100644
--- a/paddle/fluid/inference/tensorrt/test_engine.cc
+++ b/paddle/fluid/inference/tensorrt/test_engine.cc
@@ -98,7 +98,7 @@ TEST_F(TensorRTEngineTest, add_layer_multi_dim) {
float x_v[2] = {1.0, 2.0};
engine_->SetInputFromCPU("x", reinterpret_cast<void*>(&x_v),
- 2 * sizeof(float));
+ 2 * sizeof(float));
engine_->Execute(1);
LOG(INFO) << "to get output";
diff --git a/paddle/scripts/docker/build.sh b/paddle/scripts/docker/build.sh
index c63b57ce40..7e00bd3848 100755
--- a/paddle/scripts/docker/build.sh
+++ b/paddle/scripts/docker/build.sh
@@ -100,14 +100,7 @@ function run_test() {
Running unit tests ...
========================================
EOF
- set +e
ctest --output-on-failure
- if [ $? != 0 ]; then
- set -e
- ctest --output-on-failure --rerun-failed
- set +e
- fi
- set -e
# make install should also be test when unittest
make install -j `nproc`
pip install /usr/local/opt/paddle/share/wheels/*.whl
diff --git a/paddle/scripts/paddle_build.sh b/paddle/scripts/paddle_build.sh
index 245b580bdf..1595cc9e8a 100755
--- a/paddle/scripts/paddle_build.sh
+++ b/paddle/scripts/paddle_build.sh
@@ -299,14 +299,7 @@ function run_test() {
Running unit tests ...
========================================
EOF
- set +e
ctest --output-on-failure
- if [ $? != 0 ]; then
- set -e
- ctest --output-on-failure --rerun-failed
- set +e
- fi
- set -e
# make install should also be test when unittest
make install -j `nproc`
pip install /usr/local/opt/paddle/share/wheels/*.whl
@@ -474,7 +467,6 @@ EOF
}
function main() {
- set -e
local CMD=$1
init
case $CMD in
diff --git a/paddle/scripts/paddle_docker_build.sh b/paddle/scripts/paddle_docker_build.sh
index 7f5f7902bb..ddae9f19a2 100755
--- a/paddle/scripts/paddle_docker_build.sh
+++ b/paddle/scripts/paddle_docker_build.sh
@@ -59,7 +59,7 @@ EOL
if [ ! -d "${HOME}/.ccache" ]; then
mkdir ${HOME}/.ccache
fi
- set -ex
+ set -x
${DOCKER_CMD} run -it \
--name $CONTAINER_ID \
${DOCKER_ENV} \
From eb95417e0528cb625341d081aef4a20d5fcb2b32 Mon Sep 17 00:00:00 2001
From: Kexin Zhao <zhaokexin01@baidu.com>
Date: Thu, 3 May 2018 15:45:00 -0700
Subject: [PATCH 041/195] initial commit
---
paddle/fluid/operators/load_op.cc | 20 ++++++++++++++++++++
1 file changed, 20 insertions(+)
diff --git a/paddle/fluid/operators/load_op.cc b/paddle/fluid/operators/load_op.cc
index c6bd2bf3df..5a6145d517 100644
--- a/paddle/fluid/operators/load_op.cc
+++ b/paddle/fluid/operators/load_op.cc
@@ -46,6 +46,19 @@ class LoadOp : public framework::OperatorBase {
auto *tensor = out_var->GetMutable<framework::LoDTensor>();
DeserializeFromStream(fin, tensor, *dev_ctx);
+
+ auto load_as_fp16 = Attr<bool>("load_as_fp16");
+ auto in_dtype = framework::ToDataType(tensor->type());
+ auto out_dtype = load_as_fp16 ? framework::proto::VarType::FP16 : in_dtype;
+
+ if (in_dtype != out_dtype) {
+ // convert to float16 tensor
+ auto in_kernel_type = framework::OpKernelType(in_dtype, place);
+ auto out_kernel_type = framework::OpKernelType(out_dtype, place);
+ framework::LoDTensor fp16_tensor;
+ framework::TransDataType(in_kernel_type, out_kernel_type, *tensor,
+ &fp16_tensor);
+ }
}
};
@@ -54,6 +67,13 @@ class LoadOpProtoMaker : public framework::OpProtoAndCheckerMaker {
LoadOpProtoMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
AddOutput("Out", "(Tensor) The tensor need to be loaded");
+ AddAttr<bool>(
+ "load_as_fp16",
+ "(boolean, default false)"
+ "If true, the tensor will be first loaded and then "
+ "converted to float16 data type. Otherwise, the tensor will be "
+ "directly loaded without data type conversion.")
+ .SetDefault(false);
AddAttr<std::string>("file_path",
"(string) "
"Variable will be loaded from \"file_path\".")
From 270a87fb6686760fe5b0b0f155e3a7306a42afdf Mon Sep 17 00:00:00 2001
From: Kexin Zhao <zhaokexin01@baidu.com>
Date: Wed, 9 May 2018 12:06:08 -0700
Subject: [PATCH 042/195] add load op fp16 mode test
---
paddle/fluid/operators/load_op.cc | 18 +++++++
paddle/fluid/operators/save_load_op_test.cc | 55 ++++++++++++++++++++-
2 files changed, 72 insertions(+), 1 deletion(-)
diff --git a/paddle/fluid/operators/load_op.cc b/paddle/fluid/operators/load_op.cc
index 5a6145d517..662a616543 100644
--- a/paddle/fluid/operators/load_op.cc
+++ b/paddle/fluid/operators/load_op.cc
@@ -12,7 +12,9 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
#include <fstream>
+#include <iostream>
+#include "paddle/fluid/framework/data_type_transform.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/platform/device_context.h"
#include "paddle/fluid/platform/profiler.h"
@@ -51,14 +53,30 @@ class LoadOp : public framework::OperatorBase {
auto in_dtype = framework::ToDataType(tensor->type());
auto out_dtype = load_as_fp16 ? framework::proto::VarType::FP16 : in_dtype;
+ std::cout << "In load op: " << std::endl;
+ std::cout << "before conversion block" << std::endl;
+
if (in_dtype != out_dtype) {
// convert to float16 tensor
auto in_kernel_type = framework::OpKernelType(in_dtype, place);
auto out_kernel_type = framework::OpKernelType(out_dtype, place);
framework::LoDTensor fp16_tensor;
+ // copy LoD info to the new tensor
+ fp16_tensor.set_lod(tensor->lod());
+ std::cout << "before TransDataType" << std::endl;
framework::TransDataType(in_kernel_type, out_kernel_type, *tensor,
&fp16_tensor);
+ std::cout << "after TransDataType" << std::endl;
+ // reset output tensor
+ out_var->Clear();
+ tensor = out_var->GetMutable<framework::LoDTensor>();
+ tensor->set_lod(fp16_tensor.lod());
+ std::cout << "before TransDataType" << std::endl;
+ tensor->ShareDataWith(fp16_tensor);
+ std::cout << "after TransDataType" << std::endl;
}
+
+ std::cout << "Out of load op: " << std::endl;
}
};
diff --git a/paddle/fluid/operators/save_load_op_test.cc b/paddle/fluid/operators/save_load_op_test.cc
index 74385ee475..6a5ae01347 100644
--- a/paddle/fluid/operators/save_load_op_test.cc
+++ b/paddle/fluid/operators/save_load_op_test.cc
@@ -63,7 +63,7 @@ TEST(SaveLoadOp, CPU) {
}
}
-TEST(SaveLoadFP16Op, CPU) {
+TEST(SaveFP16Op, CPU) {
paddle::framework::Scope scope;
paddle::platform::CPUPlace place;
@@ -94,3 +94,56 @@ TEST(SaveLoadFP16Op, CPU) {
EXPECT_EQ(expect[i], static_cast<float>(actual[i]));
}
}
+
+TEST(LoadFP16Op, CPU) {
+ paddle::framework::Scope scope;
+ paddle::platform::CPUPlace place;
+
+ auto var = scope.Var("test_var");
+ auto tensor = var->GetMutable<paddle::framework::LoDTensor>();
+ tensor->Resize({3, 10});
+
+ paddle::framework::LoD expect_lod;
+ expect_lod.resize(1);
+ expect_lod[0].push_back(0);
+ expect_lod[0].push_back(1);
+ expect_lod[0].push_back(2);
+ expect_lod[0].push_back(3);
+
+ tensor->set_lod(expect_lod);
+ float* expect = tensor->mutable_data<float>(place);
+ for (int64_t i = 0; i < tensor->numel(); ++i) {
+ expect[i] = static_cast<float>(paddle::platform::float16(i));
+ }
+
+ paddle::framework::AttributeMap attrs;
+ attrs.insert({"file_path", std::string("tensor.save")});
+ attrs.insert({"load_as_fp16", true});
+
+ auto save_op = paddle::framework::OpRegistry::CreateOp(
+ "save", {{"X", {"test_var"}}}, {}, attrs);
+ save_op->Run(scope, place);
+
+ auto load_var = scope.Var("out_var");
+ auto target = load_var->GetMutable<paddle::framework::LoDTensor>();
+ auto load_op = paddle::framework::OpRegistry::CreateOp(
+ "load", {}, {{"Out", {"out_var"}}}, attrs);
+ LOG(INFO) << "before load op run";
+ load_op->Run(scope, place);
+ LOG(INFO) << "after load op run";
+
+ paddle::platform::float16* actual = target->data<paddle::platform::float16>();
+ LOG(INFO) << "after target->data";
+ for (int64_t i = 0; i < tensor->numel(); ++i) {
+ EXPECT_EQ(expect[i], static_cast<float>(actual[i]));
+ }
+ LOG(INFO) << "after expect equal";
+
+ auto& actual_lod = target->lod();
+ EXPECT_EQ(expect_lod.size(), actual_lod.size());
+ for (size_t i = 0; i < expect_lod.size(); ++i) {
+ for (size_t j = 0; j < expect_lod[i].size(); ++j) {
+ EXPECT_EQ(expect_lod[i][j], actual_lod[i][j]);
+ }
+ }
+}
From cbf502e5d4ab2ac8742fc461cafdd4e5c983716e Mon Sep 17 00:00:00 2001
From: Kexin Zhao <zhaokexin01@baidu.com>
Date: Wed, 9 May 2018 14:24:00 -0700
Subject: [PATCH 043/195] fix error
---
paddle/fluid/operators/save_load_op_test.cc | 6 +++---
1 file changed, 3 insertions(+), 3 deletions(-)
diff --git a/paddle/fluid/operators/save_load_op_test.cc b/paddle/fluid/operators/save_load_op_test.cc
index 6a5ae01347..9c15461305 100644
--- a/paddle/fluid/operators/save_load_op_test.cc
+++ b/paddle/fluid/operators/save_load_op_test.cc
@@ -125,21 +125,21 @@ TEST(LoadFP16Op, CPU) {
save_op->Run(scope, place);
auto load_var = scope.Var("out_var");
- auto target = load_var->GetMutable<paddle::framework::LoDTensor>();
auto load_op = paddle::framework::OpRegistry::CreateOp(
"load", {}, {{"Out", {"out_var"}}}, attrs);
LOG(INFO) << "before load op run";
load_op->Run(scope, place);
LOG(INFO) << "after load op run";
- paddle::platform::float16* actual = target->data<paddle::platform::float16>();
+ auto target = load_var->Get<paddle::framework::LoDTensor>();
+ paddle::platform::float16* actual = target.data<paddle::platform::float16>();
LOG(INFO) << "after target->data";
for (int64_t i = 0; i < tensor->numel(); ++i) {
EXPECT_EQ(expect[i], static_cast<float>(actual[i]));
}
LOG(INFO) << "after expect equal";
- auto& actual_lod = target->lod();
+ auto& actual_lod = target.lod();
EXPECT_EQ(expect_lod.size(), actual_lod.size());
for (size_t i = 0; i < expect_lod.size(); ++i) {
for (size_t j = 0; j < expect_lod[i].size(); ++j) {
From aa2635fe65a7360e075a985f34213ffbc8d9e1fd Mon Sep 17 00:00:00 2001
From: Kexin Zhao <zhaokexin01@baidu.com>
Date: Wed, 9 May 2018 14:37:13 -0700
Subject: [PATCH 044/195] clean code
---
paddle/fluid/operators/load_op.cc | 11 +----------
paddle/fluid/operators/save_load_op_test.cc | 4 ----
2 files changed, 1 insertion(+), 14 deletions(-)
diff --git a/paddle/fluid/operators/load_op.cc b/paddle/fluid/operators/load_op.cc
index 662a616543..abf7becb2e 100644
--- a/paddle/fluid/operators/load_op.cc
+++ b/paddle/fluid/operators/load_op.cc
@@ -12,7 +12,6 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
#include <fstream>
-#include <iostream>
#include "paddle/fluid/framework/data_type_transform.h"
#include "paddle/fluid/framework/op_registry.h"
@@ -53,9 +52,6 @@ class LoadOp : public framework::OperatorBase {
auto in_dtype = framework::ToDataType(tensor->type());
auto out_dtype = load_as_fp16 ? framework::proto::VarType::FP16 : in_dtype;
- std::cout << "In load op: " << std::endl;
- std::cout << "before conversion block" << std::endl;
-
if (in_dtype != out_dtype) {
// convert to float16 tensor
auto in_kernel_type = framework::OpKernelType(in_dtype, place);
@@ -63,20 +59,15 @@ class LoadOp : public framework::OperatorBase {
framework::LoDTensor fp16_tensor;
// copy LoD info to the new tensor
fp16_tensor.set_lod(tensor->lod());
- std::cout << "before TransDataType" << std::endl;
framework::TransDataType(in_kernel_type, out_kernel_type, *tensor,
&fp16_tensor);
- std::cout << "after TransDataType" << std::endl;
+
// reset output tensor
out_var->Clear();
tensor = out_var->GetMutable<framework::LoDTensor>();
tensor->set_lod(fp16_tensor.lod());
- std::cout << "before TransDataType" << std::endl;
tensor->ShareDataWith(fp16_tensor);
- std::cout << "after TransDataType" << std::endl;
}
-
- std::cout << "Out of load op: " << std::endl;
}
};
diff --git a/paddle/fluid/operators/save_load_op_test.cc b/paddle/fluid/operators/save_load_op_test.cc
index 9c15461305..8d5c17490c 100644
--- a/paddle/fluid/operators/save_load_op_test.cc
+++ b/paddle/fluid/operators/save_load_op_test.cc
@@ -127,17 +127,13 @@ TEST(LoadFP16Op, CPU) {
auto load_var = scope.Var("out_var");
auto load_op = paddle::framework::OpRegistry::CreateOp(
"load", {}, {{"Out", {"out_var"}}}, attrs);
- LOG(INFO) << "before load op run";
load_op->Run(scope, place);
- LOG(INFO) << "after load op run";
auto target = load_var->Get<paddle::framework::LoDTensor>();
paddle::platform::float16* actual = target.data<paddle::platform::float16>();
- LOG(INFO) << "after target->data";
for (int64_t i = 0; i < tensor->numel(); ++i) {
EXPECT_EQ(expect[i], static_cast<float>(actual[i]));
}
- LOG(INFO) << "after expect equal";
auto& actual_lod = target.lod();
EXPECT_EQ(expect_lod.size(), actual_lod.size());
From e3aff13451f3c63f65784df0b2e4d7b59567a6b1 Mon Sep 17 00:00:00 2001
From: Xin Pan <panxin.grad@gmail.com>
Date: Thu, 10 May 2018 10:30:42 +0800
Subject: [PATCH 045/195] Our tests interfere with each other and cause random
failure.
We should improve our test isolation before raising the
level of parallelism.
---
paddle/scripts/paddle_docker_build.sh | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/paddle/scripts/paddle_docker_build.sh b/paddle/scripts/paddle_docker_build.sh
index 7f5f7902bb..ac32bf0292 100755
--- a/paddle/scripts/paddle_docker_build.sh
+++ b/paddle/scripts/paddle_docker_build.sh
@@ -32,7 +32,7 @@ function start_build_docker() {
DOCKER_ENV=$(cat <<EOL
-e FLAGS_fraction_of_gpu_memory_to_use=0.15 \
-e CTEST_OUTPUT_ON_FAILURE=1 \
- -e CTEST_PARALLEL_LEVEL=5 \
+ -e CTEST_PARALLEL_LEVEL=1 \
-e APT_MIRROR=${apt_mirror} \
-e WITH_GPU=ON \
-e CUDA_ARCH_NAME=Auto \
From 4a5ebb6806b3f27c983918e86c1419a25464c45b Mon Sep 17 00:00:00 2001
From: Luo Tao <luotao02@baidu.com>
Date: Thu, 10 May 2018 10:10:23 +0800
Subject: [PATCH 046/195] fix tensorrt_engine compiler error
---
paddle/fluid/inference/CMakeLists.txt | 2 +-
paddle/fluid/inference/tensorrt/CMakeLists.txt | 2 +-
2 files changed, 2 insertions(+), 2 deletions(-)
diff --git a/paddle/fluid/inference/CMakeLists.txt b/paddle/fluid/inference/CMakeLists.txt
index db953e5cf3..b98aeed8a0 100644
--- a/paddle/fluid/inference/CMakeLists.txt
+++ b/paddle/fluid/inference/CMakeLists.txt
@@ -20,8 +20,8 @@ if(NOT APPLE)
endif()
if(WITH_TESTING)
+ # both tests/book and analysis depends the models that generated by python/paddle/fluid/tests/book
add_subdirectory(tests/book)
- # analysis test depends the models that generate by python/paddle/fluid/tests/book
add_subdirectory(analysis)
endif()
diff --git a/paddle/fluid/inference/tensorrt/CMakeLists.txt b/paddle/fluid/inference/tensorrt/CMakeLists.txt
index 41632dabcb..677b3e04af 100644
--- a/paddle/fluid/inference/tensorrt/CMakeLists.txt
+++ b/paddle/fluid/inference/tensorrt/CMakeLists.txt
@@ -1,4 +1,4 @@
-nv_library(tensorrt_engine SRCS engine.cc)
+nv_library(tensorrt_engine SRCS engine.cc DEPS framework_proto)
nv_test(test_tensorrt SRCS test_tensorrt.cc DEPS dynload_cuda device_context dynamic_loader)
nv_test(test_tensorrt_engine SRCS test_engine.cc DEPS dynload_cuda tensorrt_engine)
From 602aa433222d2958b00851e15d2c52ec23a09bb2 Mon Sep 17 00:00:00 2001
From: typhoonzero <typhoonzero1986@gmail.com>
Date: Thu, 10 May 2018 11:14:28 +0800
Subject: [PATCH 047/195] cast data type
---
.../operators/detail/sendrecvop_utils.cc | 31 +++----------------
1 file changed, 5 insertions(+), 26 deletions(-)
diff --git a/paddle/fluid/operators/detail/sendrecvop_utils.cc b/paddle/fluid/operators/detail/sendrecvop_utils.cc
index e77c38f59a..1a8a1af20f 100644
--- a/paddle/fluid/operators/detail/sendrecvop_utils.cc
+++ b/paddle/fluid/operators/detail/sendrecvop_utils.cc
@@ -31,35 +31,14 @@ namespace detail {
using VarMsg = sendrecv::VariableMessage;
-VarMsg::Type DataTypeToEnum(std::type_index type) {
- if (typeid(platform::float16).hash_code() == type.hash_code()) {
- return VarMsg::FP16;
- } else if (typeid(const float).hash_code() == type.hash_code()) {
- // CPPLint complains Using C-style cast. Use static_cast<float>() instead
- // One fix to this is to replace float with const float because
- // typeid(T) == typeid(const T)
- // http://en.cppreference.com/w/cpp/language/typeid
- return VarMsg::FP32;
- } else if (typeid(const double).hash_code() == type.hash_code()) {
- return VarMsg::FP64;
- } else if (typeid(const int).hash_code() == type.hash_code()) {
- return VarMsg::INT32;
- } else if (typeid(const int64_t).hash_code() == type.hash_code()) {
- return VarMsg::INT64;
- } else if (typeid(const bool).hash_code() == type.hash_code()) {
- return VarMsg::BOOL;
- } else {
- PADDLE_THROW("Not supported");
- }
-}
-
void GetTensorPayload(framework::Variable* var,
const platform::DeviceContext& ctx, VarMsg* request,
void** payload, size_t* payload_size) {
auto tensor = var->Get<framework::LoDTensor>();
- // FIXME(wuyi): data types in send_recv.proto is not synced with
+ // FIXME(wuyi): data types in send_recv.proto is copied from
// framework.proto
- request->set_data_type(DataTypeToEnum(tensor.type()));
+ request->set_data_type(
+ static_cast<VarMsg::Type>(framework::ToDataType(tensor.type())));
for (auto& dim : framework::vectorize(tensor.dims())) {
request->add_dims(dim);
}
@@ -96,7 +75,8 @@ void GetSelectedRowsPayload(framework::Variable* var,
const platform::DeviceContext& ctx, VarMsg* request,
void** payload, size_t* payload_size) {
auto* slr = var->GetMutable<framework::SelectedRows>();
- request->set_data_type(DataTypeToEnum(slr->value().type()));
+ request->set_data_type(
+ static_cast<VarMsg::Type>(framework::ToDataType(slr->value().type())));
request->set_lod_level(0);
request->set_slr_height(slr->height());
@@ -170,7 +150,6 @@ void SerializeToByteBuffer(const std::string& name, framework::Variable* var,
ProtoEncodeHelper e(static_cast<char*>(buf), 1024);
e.WriteRawBytes(std::string(header.data(), header.size()));
e.WriteVarlengthBeginning(VarMsg::kSerializedFieldNumber, payload_size);
-
// steal reference of tensor data
::grpc::Slice slices[4]; // metadata, tensor, rows meta, rows
int num_slices = 2; // only SelectedRows have rows buffer
From 62c51e44d28f93f08b1877bbb4b395e82d7e4d21 Mon Sep 17 00:00:00 2001
From: dzhwinter <dongzhihong01@baidu.com>
Date: Thu, 10 May 2018 12:24:16 +0800
Subject: [PATCH 048/195] "add float64 tests" (#10450)
* "add float64 tests"
* "fix based comment"
* "fixed based comment"
---
python/paddle/fluid/executor.py | 8 +-
python/paddle/fluid/optimizer.py | 17 +++--
.../unittests/test_network_with_dtype.py | 74 +++++++++++++++++++
3 files changed, 91 insertions(+), 8 deletions(-)
create mode 100644 python/paddle/fluid/tests/unittests/test_network_with_dtype.py
diff --git a/python/paddle/fluid/executor.py b/python/paddle/fluid/executor.py
index 7ad028714d..93aa5f908e 100644
--- a/python/paddle/fluid/executor.py
+++ b/python/paddle/fluid/executor.py
@@ -299,14 +299,18 @@ class Executor(object):
if feed is None:
feed = {}
if not isinstance(feed, dict):
- raise TypeError("feed should be a map")
+ raise TypeError(
+ "feed requires dict as its Parameter. But you passed in %s" %
+ (type(feed)))
if fetch_list is None:
fetch_list = []
if program is None:
program = default_main_program()
if not isinstance(program, Program):
- raise TypeError()
+ raise TypeError(
+ "Executor requires Program as its Parameter. But you passed in %s"
+ % (type(program)))
if scope is None:
scope = global_scope()
diff --git a/python/paddle/fluid/optimizer.py b/python/paddle/fluid/optimizer.py
index 0a314ddfd7..0fc4805522 100644
--- a/python/paddle/fluid/optimizer.py
+++ b/python/paddle/fluid/optimizer.py
@@ -47,6 +47,8 @@ class Optimizer(object):
raise TypeError("learning rate should be float or Variable")
self.regularization = regularization
self._learning_rate = learning_rate
+ # the learning rate type should be inferenced from loss
+ self._dtype = None
# each program should have a independent learning rate
# program -> Variable(learning_rate)
self._learning_rate_map = dict()
@@ -77,7 +79,7 @@ class Optimizer(object):
name=unique_name.generate("learning_rate"),
shape=[1],
value=float(self._learning_rate),
- dtype='float32',
+ dtype='float32' if self._dtype == None else self._dtype,
persistable=True)
def global_learning_rate(self, program=None):
@@ -200,6 +202,7 @@ class Optimizer(object):
# Create any accumulators
program = loss.block.program
+ self._dtype = loss.dtype
with program_guard(program, startup_program):
global_block = framework.default_main_program().global_block()
start = len(global_block.ops)
@@ -391,7 +394,7 @@ class AdamOptimizer(Optimizer):
beta_shape = [1]
self._beta1_pow_acc = self.helper.create_global_variable(
name=unique_name.generate('beta1_pow_acc'),
- dtype='float32',
+ dtype='float32' if self._dtype == None else self._dtype,
shape=beta_shape,
lod_level=0,
persistable=True)
@@ -400,7 +403,7 @@ class AdamOptimizer(Optimizer):
self._beta2_pow_acc = self.helper.create_global_variable(
name=unique_name.generate('beta2_pow_acc'),
- dtype='float32',
+ dtype='float32' if self._dtype == None else self._dtype,
shape=beta_shape,
lod_level=0,
persistable=True)
@@ -493,7 +496,7 @@ class AdamaxOptimizer(Optimizer):
beta_shape = [1]
self._beta1_pow_acc = self.helper.create_global_variable(
name=unique_name.generate('beta1_pow_acc'),
- dtype='float32',
+ dtype='float32' if self._dtype == None else self._dtype,
shape=beta_shape,
lod_level=0,
persistable=True)
@@ -900,8 +903,10 @@ class ModelAverage(Optimizer):
# param = (sum_1 + sum_2 + sum_3) / (num_accumulates + old_num_accumulates)
tmp = layers.sum(x=[num_accumulates, old_num_accumulates])
sum = layers.sum(x=[sum_1, sum_2, sum_3])
- tmp = layers.cast(x=tmp, dtype='float32')
- sum = layers.cast(x=sum, dtype='float32')
+ tmp = layers.cast(
+ x=tmp, dtype='float32' if self._dtype == None else self._dtype)
+ sum = layers.cast(
+ x=sum, dtype='float32' if self._dtype == None else self._dtype)
layers.elementwise_div(x=sum, y=tmp, out=param)
def _add_average_restore_op(self, block, param_grad):
diff --git a/python/paddle/fluid/tests/unittests/test_network_with_dtype.py b/python/paddle/fluid/tests/unittests/test_network_with_dtype.py
new file mode 100644
index 0000000000..baafcdbb80
--- /dev/null
+++ b/python/paddle/fluid/tests/unittests/test_network_with_dtype.py
@@ -0,0 +1,74 @@
+# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import unittest
+
+import numpy as np
+import paddle
+import paddle.fluid as fluid
+import paddle.fluid.core as core
+from paddle.fluid.executor import Executor
+
+BATCH_SIZE = 20
+
+
+class TestNetWithDtype(unittest.TestCase):
+ def setUp(self):
+ self.dtype = "float64"
+ self.init_dtype()
+ self.x = fluid.layers.data(name='x', shape=[13], dtype=self.dtype)
+ self.y = fluid.layers.data(name='y', shape=[1], dtype=self.dtype)
+ y_predict = fluid.layers.fc(input=self.x, size=1, act=None)
+
+ cost = fluid.layers.square_error_cost(input=y_predict, label=self.y)
+ avg_cost = fluid.layers.mean(cost)
+ self.fetch_list = [avg_cost]
+
+ sgd_optimizer = fluid.optimizer.SGD(learning_rate=0.001)
+ sgd_optimizer.minimize(avg_cost)
+
+ def run_net_on_place(self, place):
+ train_reader = paddle.batch(
+ paddle.dataset.uci_housing.train(), batch_size=BATCH_SIZE)
+ feeder = fluid.DataFeeder(place=place, feed_list=[self.x, self.y])
+ exe = fluid.Executor(place)
+ exe.run(fluid.default_startup_program())
+ for data in train_reader():
+ exe.run(fluid.default_main_program(),
+ feed=feeder.feed(data),
+ fetch_list=self.fetch_list)
+ # the main program is runable, the datatype is fully supported
+ break
+
+ def init_dtype(self):
+ pass
+
+ def test_cpu(self):
+ place = fluid.CPUPlace()
+ self.run_net_on_place(place)
+
+ def test_gpu(self):
+ if not core.is_compiled_with_cuda():
+ return
+ place = fluid.CUDAPlace(0)
+ self.run_net_on_place(place)
+
+
+# TODO(dzhwinter): make sure the fp16 is runable
+# class TestFloat16(SimpleNet):
+# def init_dtype(self):
+# self.dtype = "float16"
+
+if __name__ == '__main__':
+ unittest.main()
From a0c413833dd2995c5c47fb156de3234b515e8f2f Mon Sep 17 00:00:00 2001
From: reyoung <reyoung@126.com>
Date: Thu, 10 May 2018 15:10:43 +0800
Subject: [PATCH 049/195] Polish Dctor
---
paddle/fluid/framework/CMakeLists.txt | 2 +-
paddle/fluid/framework/op_proto_maker.h | 34 ++++++++++++-------------
2 files changed, 18 insertions(+), 18 deletions(-)
diff --git a/paddle/fluid/framework/CMakeLists.txt b/paddle/fluid/framework/CMakeLists.txt
index 340b891e41..ab71e0e63c 100644
--- a/paddle/fluid/framework/CMakeLists.txt
+++ b/paddle/fluid/framework/CMakeLists.txt
@@ -57,7 +57,7 @@ cc_library(data_transform SRCS data_transform.cc DEPS math_function tensor
cc_library(attribute SRCS attribute.cc DEPS framework_proto boost)
cc_test(program_desc_test SRCS program_desc_test.cc DEPS proto_desc
device_context)
-cc_library(op_proto_maker SRCS op_proto_maker.cc DEPS framework_proto attribute)
+cc_library(op_proto_maker SRCS op_proto_maker.cc DEPS framework_proto attribute glog)
cc_test(op_proto_maker_test SRCS op_proto_maker_test.cc DEPS op_proto_maker)
cc_library(op_info SRCS op_info.cc DEPS attribute framework_proto)
cc_library(shape_inference SRCS shape_inference.cc DEPS ddim attribute device_context)
diff --git a/paddle/fluid/framework/op_proto_maker.h b/paddle/fluid/framework/op_proto_maker.h
index cd56776cc6..b01a520bba 100644
--- a/paddle/fluid/framework/op_proto_maker.h
+++ b/paddle/fluid/framework/op_proto_maker.h
@@ -14,9 +14,9 @@ limitations under the License. */
#pragma once
#include <string>
+#include "glog/logging.h"
#include "paddle/fluid/framework/attribute.h"
#include "paddle/fluid/framework/framework.pb.h"
-
namespace paddle {
namespace framework {
@@ -26,45 +26,45 @@ class OpProtoAndCheckerMaker {
virtual void Make() = 0;
virtual ~OpProtoAndCheckerMaker() {
- PADDLE_ENFORCE(validated_, "should call Validate after build");
+ CHECK(validated_) << "should call Validate after build";
}
- void SetProto(proto::OpProto* proto) { proto_ = proto; }
+ void SetProto(proto::OpProto *proto) { proto_ = proto; }
- void SetChecker(OpAttrChecker* attr_checker) { op_checker_ = attr_checker; }
+ void SetChecker(OpAttrChecker *attr_checker) { op_checker_ = attr_checker; }
void Validate();
protected:
struct VariableBuilder {
- proto::OpProto::Var* var_;
+ proto::OpProto::Var *var_;
- VariableBuilder& AsDuplicable() {
+ VariableBuilder &AsDuplicable() {
var_->set_duplicable(true);
return *this;
}
- VariableBuilder& AsIntermediate() {
+ VariableBuilder &AsIntermediate() {
var_->set_intermediate(true);
return *this;
}
- VariableBuilder& AsDispensable() {
+ VariableBuilder &AsDispensable() {
var_->set_dispensable(true);
return *this;
}
};
- VariableBuilder AddInput(const std::string& name, const std::string& comment);
+ VariableBuilder AddInput(const std::string &name, const std::string &comment);
- VariableBuilder AddOutput(const std::string& name,
- const std::string& comment);
+ VariableBuilder AddOutput(const std::string &name,
+ const std::string &comment);
template <typename T>
- TypedAttrChecker<T>& AddAttr(const std::string& name,
- const std::string& comment,
+ TypedAttrChecker<T> &AddAttr(const std::string &name,
+ const std::string &comment,
bool generated = false) {
- auto* attr = proto_->add_attrs();
+ auto *attr = proto_->add_attrs();
attr->set_name(name);
attr->set_comment(comment);
attr->set_generated(generated);
@@ -72,13 +72,13 @@ class OpProtoAndCheckerMaker {
return op_checker_->AddAttrChecker<T>(name);
}
- void AddComment(const std::string& comment) { proto_->set_comment(comment); }
+ void AddComment(const std::string &comment) { proto_->set_comment(comment); }
private:
void CheckNoDuplicatedInOutAttrs();
- proto::OpProto* proto_;
- OpAttrChecker* op_checker_;
+ proto::OpProto *proto_;
+ OpAttrChecker *op_checker_;
bool validated_{false};
};
} // namespace framework
From 9c8383cf06e953b47a5e1731cb2cbf3f4bcfe239 Mon Sep 17 00:00:00 2001
From: yuyang18 <reyoung@126.com>
Date: Thu, 10 May 2018 16:29:04 +0800
Subject: [PATCH 050/195] Parallel Executor revised feeder
---
python/paddle/fluid/data_feeder.py | 58 +++++++++++++++++++
.../tests/unittests/test_parallel_executor.py | 37 ++++++++++++
2 files changed, 95 insertions(+)
diff --git a/python/paddle/fluid/data_feeder.py b/python/paddle/fluid/data_feeder.py
index ac02401c79..0051b69847 100644
--- a/python/paddle/fluid/data_feeder.py
+++ b/python/paddle/fluid/data_feeder.py
@@ -16,6 +16,7 @@ from __future__ import print_function
import core
import numpy
import six.moves as six
+import multiprocessing
from framework import Variable, default_main_program
@@ -116,3 +117,60 @@ class DataFeeder(object):
for each_name, each_converter in six.zip(self.feed_names, converter):
ret_dict[each_name] = each_converter.done()
return ret_dict
+
+ def feed_parallel(self, iterable, num_places=None):
+ if isinstance(self.place, core.CUDAPlace):
+ places = [
+ core.CUDAPlace(i)
+ for i in six.xrange(self._get_number_of_places_(num_places))
+ ]
+ else:
+ places = [
+ core.CPUPlace()
+ for _ in six.xrange(self._get_number_of_places_(num_places))
+ ]
+
+ if len(iterable) != len(places):
+ raise ValueError("feed_parallel takes multiple mini-batches. Each "
+ "mini-batch will be feed on each device. The "
+ "number of devices and number of mini-batches "
+ "must be same.")
+
+ place = self.place
+ for p, batch in six.zip(places, iterable):
+ self.place = p
+ yield self.feed(batch)
+ self.place = place
+
+ def _get_number_of_places_(self, num_places):
+ if num_places is not None:
+ return int(num_places)
+ elif isinstance(self.place, core.CUDAPlace):
+ return core.get_cuda_device_count()
+ else:
+ return multiprocessing.cpu_count()
+
+ def decorate_reader(self,
+ reader,
+ multi_devices,
+ num_places=None,
+ drop_last=True):
+ def __reader_creator__():
+ if not multi_devices:
+ for item in reader():
+ yield self.feed(item)
+ else:
+ num = self._get_number_of_places_(num_places)
+ item = []
+ for batch in reader():
+ item.append(batch)
+ if len(item) == num:
+ yield list(self.feed_parallel(item, num))
+ item = []
+ if not drop_last and len(item) != 0:
+ raise ValueError(
+ "The data batch which cannot fit for devices will be "
+ "dropped is not implementation. Other strategies are "
+ "not implemented")
+
+ return __reader_creator__
diff --git a/python/paddle/fluid/tests/unittests/test_parallel_executor.py b/python/paddle/fluid/tests/unittests/test_parallel_executor.py
index 4eb25a6e00..6db3a13718 100644
--- a/python/paddle/fluid/tests/unittests/test_parallel_executor.py
+++ b/python/paddle/fluid/tests/unittests/test_parallel_executor.py
@@ -796,5 +796,42 @@ class TestFetchOp(unittest.TestCase):
self.parallel_exe(train_inputs, seed=1)
+class TestFeedParallel(unittest.TestCase):
+ def test_main(self):
+ main = fluid.Program()
+ startup = fluid.Program()
+ startup.random_seed = 1
+ with fluid.scope_guard(fluid.core.Scope()):
+ with fluid.program_guard(main, startup):
+ data = fluid.layers.data(
+ name='image', shape=[3, 224, 224], dtype='float32')
+ label = fluid.layers.data(
+ name='label', shape=[1], dtype='int64')
+ out = Lenet(data, class_dim=102)
+ loss = fluid.layers.cross_entropy(input=out, label=label)
+ loss = fluid.layers.mean(loss)
+ opt = fluid.optimizer.Momentum(
+ learning_rate=0.1,
+ momentum=0.9,
+ regularization=fluid.regularizer.L2Decay(1e-4))
+
+ opt.minimize(loss)
+ place = fluid.CUDAPlace(0)
+ feeder = fluid.DataFeeder(place=place, feed_list=[data, label])
+ reader = feeder.decorate_reader(
+ paddle.batch(
+ flowers.train(), batch_size=16), multi_devices=True)
+ exe = fluid.Executor(place)
+ exe.run(startup)
+ pe = fluid.ParallelExecutor(
+ use_cuda=True, loss_name=loss.name, main_program=main)
+
+ for batch_id, data in enumerate(reader()):
+ loss_np = np.array(pe.run(feed=data, fetch_list=[loss.name])[0])
+ print batch_id, loss_np
+ if batch_id == 2:
+ break
+
+
if __name__ == '__main__':
unittest.main()
From 613d3ef084b9863e5473506ff5888eee1b6ec951 Mon Sep 17 00:00:00 2001
From: yuyang18 <reyoung@126.com>
Date: Thu, 10 May 2018 17:14:05 +0800
Subject: [PATCH 051/195] Fix compile error
---
paddle/fluid/operators/batch_size_like.h | 6 +++++-
paddle/fluid/operators/fill_constant_batch_size_like_op.cc | 4 ++--
.../fluid/operators/gaussian_random_batch_size_like_op.cc | 4 ++--
paddle/fluid/operators/uniform_random_batch_size_like_op.cc | 4 ++--
python/paddle/fluid/layers/layer_function_generator.py | 2 +-
5 files changed, 12 insertions(+), 8 deletions(-)
diff --git a/paddle/fluid/operators/batch_size_like.h b/paddle/fluid/operators/batch_size_like.h
index d01b7e4c8d..483c9f8c21 100644
--- a/paddle/fluid/operators/batch_size_like.h
+++ b/paddle/fluid/operators/batch_size_like.h
@@ -53,7 +53,7 @@ class BatchSizeLikeOp : public framework::OperatorWithKernel {
class BatchSizeLikeOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- void Make() override {
+ void Make() final {
AddInput("Input",
"(Tensor) Tensor "
"whose input_dim_idx'th dimension specifies the batch_size");
@@ -67,7 +67,11 @@ class BatchSizeLikeOpMaker : public framework::OpProtoAndCheckerMaker {
AddAttr<int>("output_dim_idx",
"(int, default 0) The index of output's batch size dimension")
.SetDefault(0);
+ Apply();
}
+
+ protected:
+ virtual void Apply() = 0;
};
} // namespace operators
diff --git a/paddle/fluid/operators/fill_constant_batch_size_like_op.cc b/paddle/fluid/operators/fill_constant_batch_size_like_op.cc
index e6bcbecad6..1ae78675a0 100644
--- a/paddle/fluid/operators/fill_constant_batch_size_like_op.cc
+++ b/paddle/fluid/operators/fill_constant_batch_size_like_op.cc
@@ -30,8 +30,8 @@ class FillConstantBatchSizeLikeOp : public BatchSizeLikeOp {
};
class FillConstantBatchSizeLikeOpMaker : public BatchSizeLikeOpMaker {
- public:
- void Make() override {
+ protected:
+ void Apply() override {
AddAttr<int>("dtype",
"(int, default 5 (FP32)) "
"Output data type")
diff --git a/paddle/fluid/operators/gaussian_random_batch_size_like_op.cc b/paddle/fluid/operators/gaussian_random_batch_size_like_op.cc
index 45064fc416..8050f61d45 100644
--- a/paddle/fluid/operators/gaussian_random_batch_size_like_op.cc
+++ b/paddle/fluid/operators/gaussian_random_batch_size_like_op.cc
@@ -32,8 +32,8 @@ class GaussianRandomBatchSizeLikeOp : public BatchSizeLikeOp {
};
class GaussianRandomBatchSizeLikeOpMaker : public BatchSizeLikeOpMaker {
- public:
- void Make() override {
+ protected:
+ void Apply() override {
AddAttr<float>("mean",
"(float, default 0.0) "
"mean of random tensor.")
diff --git a/paddle/fluid/operators/uniform_random_batch_size_like_op.cc b/paddle/fluid/operators/uniform_random_batch_size_like_op.cc
index aa9f794786..78fee77df8 100644
--- a/paddle/fluid/operators/uniform_random_batch_size_like_op.cc
+++ b/paddle/fluid/operators/uniform_random_batch_size_like_op.cc
@@ -32,8 +32,8 @@ class UniformRandomBatchSizeLikeOp : public BatchSizeLikeOp {
};
class UniformRandomBatchSizeLikeOpMaker : public BatchSizeLikeOpMaker {
- public:
- void Make() override {
+ protected:
+ void Apply() override {
AddComment(R"DOC(
Uniform random operator
diff --git a/python/paddle/fluid/layers/layer_function_generator.py b/python/paddle/fluid/layers/layer_function_generator.py
index 35b01a7991..295d1b7190 100644
--- a/python/paddle/fluid/layers/layer_function_generator.py
+++ b/python/paddle/fluid/layers/layer_function_generator.py
@@ -113,7 +113,7 @@ def generate_layer_fn(op_type):
if len(not_intermediate_outputs) != 1:
raise ValueError("Only one non intermediate output operator can be",
- "automatically generated.")
+ "automatically generated. {0}".format(op_type))
if not_intermediate_outputs[0].duplicable:
raise ValueError(
From 535245cd4c1856586efcc2995230d7285e75c954 Mon Sep 17 00:00:00 2001
From: Wu Yi <typhoonzero1986@gmail.com>
Date: Thu, 10 May 2018 17:44:00 +0800
Subject: [PATCH 052/195] Add NCCL2 rdma train doc (#10561)
* add rdma train doc
* update by comment
* fix table
---
.../howto/cluster/nccl2_rdma_training.md | 110 ++++++++++++++++++
1 file changed, 110 insertions(+)
create mode 100644 doc/fluid/howto/cluster/nccl2_rdma_training.md
diff --git a/doc/fluid/howto/cluster/nccl2_rdma_training.md b/doc/fluid/howto/cluster/nccl2_rdma_training.md
new file mode 100644
index 0000000000..cecd5c3a7a
--- /dev/null
+++ b/doc/fluid/howto/cluster/nccl2_rdma_training.md
@@ -0,0 +1,110 @@
+# Distributed Training with NCCL2 and RDMA
+
+When doing distributed multi-GPU training, network bandwith often becomes the
+bottle neck. We introduce a way to use NCCL2 to do such training job to
+achieve best performace.
+
+## Prepare Hardwares with RDMA and Multiple GPUs
+
+I'm using two Linux servers each of them is installed with 8 GPUs and
+one 100Gb RDMA card.
+Base environment is:
+
+* OS: CentOS 7.4
+* RDMA device: "Mellanox Technologies MT27700 Family [ConnectX-4]"
+* Kernel version: `4.4.88-1.el7.elrepo.x86_64`
+* Docker version: `1.12.6`
+* Docker storage driver: `overlay2`
+* IP addresses: 192.168.16.30,192.168.16.34
+
+In general, the steps including:
+
+1. Install GPU drivers
+1. Install RDMA drivers
+1. Install "InfiniBand Support"
+1. Use docker to run tests and make sure GPUs and RDMA can work inside
+ the container.
+
+I'll ommit section "Install GPU drivers" because we can find it easily
+somewhere else.
+
+### Install RDMA drivers
+
+For my case, I've got two machines with device
+"Mellanox Technologies MT27700 Family [ConnectX-4]" installed. The OS was
+"CentOS 7.4" and I updated the kernel to version 4.4 so that docker can
+work with latest overlay2 filesystem.
+
+***NOTE: before you start, make sure you have a way to get a console
+of the server other than ssh because we may need to re-configure the
+network device.***
+
+1. Go to http://www.mellanox.com/page/products_dyn?product_family=26,
+ download `MLNX_OFED` software in the bottom of the page, and upload it
+ onto the server.
+1. Run `./mlnxofedinstall --add-kernel-support` in the software package.
+1. Run `/etc/init.d/openibd restart` to make everything work, note that
+ this operation may cause the network goes down if you are using this
+ RDMA device as default network device and use ssh to login the server.
+1. Re-configure the network interface, for example:
+ `ifconfig eth2 192.168.16.30/20 up`, then add routes if needed:
+ `ip route add default via 192.168.16.1 dev eth2`.
+1. Do the same thing on the other node.
+1. Use `ping` to test if the two nodes have typical ICMP connection.
+1. Use either `udaddy` or `ib_write_bw` to test the network connection is
+ ready and have the desired bandwith.
+
+### Prepare Docker Image to Run RDMA Programs
+
+1. Build a docker image using cuda base image like: `nvidia/cuda:8.0-cudnn5-devel-ubuntu16.04` and install paddlepaddle whl
+ package in it.
+1. Start a docker container and mount GPU driver libs into it (you can
+ skip this step if you are using nvidia-docker).
+1. Mount RDMA dirvers and libs into the docker image (see below section),
+ also `udaddy` and `ib_write_bw` if needed.
+1. Mount GPU devices and RDMA devices into the container using `--device`
+ or just use privileged mode `--privileged`.
+1. Start the container using host network mode: `--net=host`
+
+### RDMA Library Files Needed
+
+Usually, `MLNX_OFED` install latest supported libs under
+`/usr/lib64/mlnx_ofed/valgrind`. Other libs also needed to run RDMA programs
+is listed below. These libs must be mounted into the docker container.
+
+* Libs under `/usr/lib64/mlnx_ofed/valgrind`
+ * libibcm.so
+ * libibverbs.so
+ * libmlx4.so
+ * libmlx5.so
+ * libmlx5-rdmav2.so
+ * librdmacm.so
+* Other libs:
+ * libnl-3.so.200
+ * libnl-route-3.so.200
+ * libnuma.so.1
+
+## Start to Run the Training Job
+
+Setting NCCL environment variables to turn NCCL switches on and off:
+
+
+| Env Name | Description |
+| --- | --- |
+| NCCL_SOCKET_IFNAME | The RDMA device, e.g. eth2 |
+| NCCL_P2P_DISABLE | Set to 1 to disable P2P transfer between GPUs |
+| NCCL_IB_DISABLE | Set to 1 to disable using RDMA |
+| NCCL_IB_CUDA_SUPPORT | Set to 1 to enable GPU Direct if supported |
+| NCCL_DEBUG | Set debug level: VERSION, WARN, INFO |
+
+My two servers are: `192.168.16.30,192.168.16.34`, On node 1, Run :
+
+```bash
+PADDLE_TRAINER_ID=0 PADDLE_PORT=48372 PADDLE_WORKERS=192.168.16.30,192.168.16.34 POD_IP=192.168.16.30 stdbuf -oL python vgg16.py
+```
+
+On node 2, Run:
+
+```bash
+PADDLE_TRAINER_ID=1 PADDLE_PORT=48372 PADDLE_WORKERS=192.168.16.30,192.168.16.34 POD_IP=192.168.16.34 stdbuf -oL python vgg16.py
+```
From 27197290dc70b0250e4969398b0f0fe38424172c Mon Sep 17 00:00:00 2001
From: yuyang18 <reyoung@126.com>
Date: Thu, 10 May 2018 18:29:26 +0800
Subject: [PATCH 053/195] matmul support float16/double
---
paddle/fluid/operators/math/blas_impl.cu.h | 18 ++++-
paddle/fluid/operators/math/math_function.cu | 7 +-
paddle/fluid/operators/matmul_op.cc | 78 +++++++++++---------
3 files changed, 64 insertions(+), 39 deletions(-)
diff --git a/paddle/fluid/operators/math/blas_impl.cu.h b/paddle/fluid/operators/math/blas_impl.cu.h
index c76fc17d78..d84c88cb3b 100644
--- a/paddle/fluid/operators/math/blas_impl.cu.h
+++ b/paddle/fluid/operators/math/blas_impl.cu.h
@@ -96,10 +96,22 @@ struct CUBlas<platform::float16> {
reinterpret_cast<__half *>(C), ldc));
}
- template <typename... ARGS>
- static void GEMM_BATCH(ARGS... args) {
+ static void GEMM_BATCH(cublasHandle_t handle, cublasOperation_t transa,
+ cublasOperation_t transb, int m, int n, int k,
+ const float16 *alpha, const float16 *A, int lda,
+ long long int strideA, const float16 *B, // NOLINT
+ int ldb, long long int strideB, // NOLINT
+ const float16 *beta, float16 *C, int ldc,
+ long long int strideC, // NOLINT
+ int batchCount) {
#if CUDA_VERSION >= 8000
- PADDLE_ENFORCE(platform::dynload::cublasHgemmStridedBatched(args...));
+ PADDLE_ENFORCE(platform::dynload::cublasHgemmStridedBatched(
+ handle, transa, transb, m, n, k,
+ reinterpret_cast<const __half *>(alpha),
+ reinterpret_cast<const __half *>(A), lda, strideA,
+ reinterpret_cast<const __half *>(B), ldb, strideB,
+ reinterpret_cast<const __half *>(beta), reinterpret_cast<__half *>(C),
+ ldc, strideC, batchCount));
#else
PADDLE_THROW("HgemmStridedBatched is not supported on cuda <= 7.5");
#endif
diff --git a/paddle/fluid/operators/math/math_function.cu b/paddle/fluid/operators/math/math_function.cu
index b5bf84e517..d5af718723 100644
--- a/paddle/fluid/operators/math/math_function.cu
+++ b/paddle/fluid/operators/math/math_function.cu
@@ -33,9 +33,10 @@ template struct SetConstant<platform::CUDADeviceContext, int>;
template struct SetConstant<platform::CUDADeviceContext, int64_t>;
template struct SetConstant<platform::CUDADeviceContext, bool>;
-#define DEFINE_GPU_TRANS(RANK) \
- template struct Transpose<platform::CUDADeviceContext, float, RANK>; \
- template struct Transpose<platform::CUDADeviceContext, double, RANK>;
+#define DEFINE_GPU_TRANS(RANK) \
+ template struct Transpose<platform::CUDADeviceContext, float, RANK>; \
+ template struct Transpose<platform::CUDADeviceContext, double, RANK>; \
+ template struct Transpose<platform::CUDADeviceContext, float16, RANK>;
DEFINE_GPU_TRANS(1);
DEFINE_GPU_TRANS(2);
diff --git a/paddle/fluid/operators/matmul_op.cc b/paddle/fluid/operators/matmul_op.cc
index da21b8ad7d..383f0124d9 100644
--- a/paddle/fluid/operators/matmul_op.cc
+++ b/paddle/fluid/operators/matmul_op.cc
@@ -25,7 +25,7 @@ namespace operators {
* Get row matrix shape from a vector shape. If the rank of x_dim > 1, the
* original x_dim is returned.
*/
-static framework::DDim RowMatrixFromVector(const framework::DDim& x_dim) {
+static framework::DDim RowMatrixFromVector(const framework::DDim &x_dim) {
if (x_dim.size() > 1) {
return x_dim;
}
@@ -36,7 +36,7 @@ static framework::DDim RowMatrixFromVector(const framework::DDim& x_dim) {
* Get column matrix shape from a vector shape. If the ran of y_dim > 1, the
* original y_dim is returned.
*/
-static framework::DDim ColumnMatrixFromVector(const framework::DDim& y_dim) {
+static framework::DDim ColumnMatrixFromVector(const framework::DDim &y_dim) {
if (y_dim.size() > 1) {
return y_dim;
}
@@ -46,12 +46,12 @@ static framework::DDim ColumnMatrixFromVector(const framework::DDim& y_dim) {
template <typename DeviceContext, typename T>
class MatMulKernel : public framework::OpKernel<T> {
public:
- void Compute(const framework::ExecutionContext& context) const override {
- auto& x =
+ void Compute(const framework::ExecutionContext &context) const override {
+ auto &x =
detail::Ref(context.Input<framework::Tensor>("X"), "Cannot find X");
- auto& y =
+ auto &y =
detail::Ref(context.Input<framework::Tensor>("Y"), "Cannot find Y");
- auto* out = context.Output<framework::Tensor>("Out");
+ auto *out = context.Output<framework::Tensor>("Out");
out->mutable_data<T>(context.GetPlace());
auto blas = math::GetBlas<DeviceContext, T>(context);
@@ -65,7 +65,7 @@ class MatMulKernel : public framework::OpKernel<T> {
// Reshape a rank-3 tensor from P x M x N to (P * M) x N.
// Identity op if the tensor is not of rank 3.
-static framework::Tensor FoldInitDims(const framework::Tensor& input) {
+static framework::Tensor FoldInitDims(const framework::Tensor &input) {
auto output = input;
auto in_dims = input.dims();
if (in_dims.size() == 3) {
@@ -78,8 +78,8 @@ static framework::Tensor FoldInitDims(const framework::Tensor& input) {
// (Warning: This requires transposing data and writes into new memory.)
// Identity op if the tensor is not of rank 3.
template <typename DeviceContext, typename T>
-static framework::Tensor FoldHeadAndLastDims(const DeviceContext& context,
- const framework::Tensor& input) {
+static framework::Tensor FoldHeadAndLastDims(const DeviceContext &context,
+ const framework::Tensor &input) {
auto in_dims = input.dims();
if (in_dims.size() != 3) {
return input;
@@ -102,7 +102,7 @@ static framework::Tensor FoldHeadAndLastDims(const DeviceContext& context,
* If transposed, `H,W` will be swapped.
*/
static void ReshapeTensorIntoMatrixSequence(
- framework::Tensor* x, const math::MatDescriptor& descriptor) {
+ framework::Tensor *x, const math::MatDescriptor &descriptor) {
int64_t h, w;
h = descriptor.height_;
w = descriptor.width_;
@@ -130,9 +130,9 @@ static void ReshapeTensorIntoMatrixSequence(
* If any of `X` and `Y` has batch size BatchSize, the out will have the
* BatchSize.
*/
-static void ReshapeXYOutIntoMatrixSequence(framework::Tensor* x,
- framework::Tensor* y,
- framework::Tensor* out, bool trans_x,
+static void ReshapeXYOutIntoMatrixSequence(framework::Tensor *x,
+ framework::Tensor *y,
+ framework::Tensor *out, bool trans_x,
bool trans_y) {
auto x_dim = RowMatrixFromVector(x->dims());
auto y_dim = ColumnMatrixFromVector(y->dims());
@@ -177,10 +177,10 @@ static void ReshapeXYOutIntoMatrixSequence(framework::Tensor* x,
template <typename DeviceContext, typename T>
class MatMulGradKernel : public framework::OpKernel<T> {
public:
- void MatMul(const framework::ExecutionContext& context,
- const framework::Tensor& a, bool trans_a,
- const framework::Tensor& b, bool trans_b,
- framework::Tensor* out) const {
+ void MatMul(const framework::ExecutionContext &context,
+ const framework::Tensor &a, bool trans_a,
+ const framework::Tensor &b, bool trans_b,
+ framework::Tensor *out) const {
out->mutable_data<T>(context.GetPlace());
auto blas = math::GetBlas<DeviceContext, T>(context);
auto mat_dim_a = math::CreateMatrixDescriptor(a.dims(), 0, trans_a);
@@ -188,18 +188,18 @@ class MatMulGradKernel : public framework::OpKernel<T> {
blas.MatMul(a, mat_dim_a, b, mat_dim_b, T(1), out, T(0));
}
- void CalcInputGrad(const framework::ExecutionContext& context,
- const framework::Tensor& a, bool trans_a,
- bool is_fold_init_dims_a, const framework::Tensor& b,
+ void CalcInputGrad(const framework::ExecutionContext &context,
+ const framework::Tensor &a, bool trans_a,
+ bool is_fold_init_dims_a, const framework::Tensor &b,
bool trans_b, bool is_fold_init_dims_b,
- framework::Tensor* out) const {
+ framework::Tensor *out) const {
if (out == nullptr) return;
bool need_combine = (a.dims().size() == 3 || b.dims().size() == 3) &&
out->dims().size() == 2;
if (!need_combine) {
MatMul(context, a, trans_a, b, trans_b, out);
} else {
- auto& ctx = context.template device_context<DeviceContext>();
+ auto &ctx = context.template device_context<DeviceContext>();
MatMul(context, is_fold_init_dims_a
? FoldInitDims(a)
: FoldHeadAndLastDims<DeviceContext, T>(ctx, a),
@@ -210,13 +210,13 @@ class MatMulGradKernel : public framework::OpKernel<T> {
}
}
- void Compute(const framework::ExecutionContext& context) const override {
+ void Compute(const framework::ExecutionContext &context) const override {
auto x = *context.Input<framework::Tensor>("X");
auto y = *context.Input<framework::Tensor>("Y");
auto dout =
*context.Input<framework::Tensor>(framework::GradVarName("Out"));
- auto* dx = context.Output<framework::Tensor>(framework::GradVarName("X"));
- auto* dy = context.Output<framework::Tensor>(framework::GradVarName("Y"));
+ auto *dx = context.Output<framework::Tensor>(framework::GradVarName("X"));
+ auto *dy = context.Output<framework::Tensor>(framework::GradVarName("Y"));
bool transpose_x = context.Attr<bool>("transpose_X");
bool transpose_y = context.Attr<bool>("transpose_Y");
@@ -269,7 +269,7 @@ class MatMulOp : public framework::OperatorWithKernel {
using framework::OperatorWithKernel::OperatorWithKernel;
protected:
- void InferShape(framework::InferShapeContext* context) const override {
+ void InferShape(framework::InferShapeContext *context) const override {
PADDLE_ENFORCE(context->HasInput("X"),
"Input(X) of MatMulOp should not be null.");
PADDLE_ENFORCE(context->HasInput("Y"),
@@ -322,7 +322,7 @@ class MatMulOp : public framework::OperatorWithKernel {
class MatMulOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- MatMulOpMaker(OpProto* proto, OpAttrChecker* op_checker)
+ MatMulOpMaker(OpProto *proto, OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
AddInput("X", "The first input of MatMul op");
AddInput("Y", "The second input of MatMul op");
@@ -376,7 +376,7 @@ class MatMulOpGrad : public framework::OperatorWithKernel {
using framework::OperatorWithKernel::OperatorWithKernel;
protected:
- void InferShape(framework::InferShapeContext* context) const override {
+ void InferShape(framework::InferShapeContext *context) const override {
PADDLE_ENFORCE(context->HasInput("X"), "Input(X) should not be null");
PADDLE_ENFORCE(context->HasInput("Y"), "Input(Y) should not be null");
PADDLE_ENFORCE(context->HasInput(framework::GradVarName("Out")),
@@ -402,7 +402,7 @@ class MatMulOpGradMaker : public framework::SingleGradOpDescMaker {
protected:
std::unique_ptr<framework::OpDesc> Apply() const override {
- auto* retv = new framework::OpDesc();
+ auto *retv = new framework::OpDesc();
retv->SetType("matmul_grad");
retv->SetInput("X", Input("X"));
retv->SetInput("Y", Input("Y"));
@@ -421,15 +421,27 @@ REGISTER_OPERATOR(matmul, ops::MatMulOp, ops::MatMulOpMaker,
ops::MatMulOpGradMaker);
REGISTER_OPERATOR(matmul_grad, ops::MatMulOpGrad);
REGISTER_OP_CPU_KERNEL(
- matmul, ops::MatMulKernel<paddle::platform::CPUDeviceContext, float>);
+ matmul, ops::MatMulKernel<paddle::platform::CPUDeviceContext, float>,
+ ops::MatMulKernel<paddle::platform::CPUDeviceContext, double>,
+ ops::MatMulKernel<paddle::platform::CPUDeviceContext,
+ paddle::platform::float16>);
REGISTER_OP_CPU_KERNEL(
matmul_grad,
- ops::MatMulGradKernel<paddle::platform::CPUDeviceContext, float>);
+ ops::MatMulGradKernel<paddle::platform::CPUDeviceContext, float>,
+ ops::MatMulGradKernel<paddle::platform::CPUDeviceContext, double>,
+ ops::MatMulGradKernel<paddle::platform::CPUDeviceContext,
+ paddle::platform::float16>);
#ifdef PADDLE_WITH_CUDA
REGISTER_OP_CUDA_KERNEL(
- matmul, ops::MatMulKernel<paddle::platform::CUDADeviceContext, float>);
+ matmul, ops::MatMulKernel<paddle::platform::CUDADeviceContext, float>,
+ ops::MatMulKernel<paddle::platform::CUDADeviceContext, double>,
+ ops::MatMulKernel<paddle::platform::CUDADeviceContext,
+ paddle::platform::float16>);
REGISTER_OP_CUDA_KERNEL(
matmul_grad,
- ops::MatMulGradKernel<paddle::platform::CUDADeviceContext, float>);
+ ops::MatMulGradKernel<paddle::platform::CUDADeviceContext, float>,
+ ops::MatMulGradKernel<paddle::platform::CUDADeviceContext, double>,
+ ops::MatMulGradKernel<paddle::platform::CUDADeviceContext,
+ paddle::platform::float16>);
#endif
From 13457ef30696214ec410e9df4d165c7c05f6602a Mon Sep 17 00:00:00 2001
From: Yi Wang <yi.wang.2005@gmail.com>
Date: Thu, 10 May 2018 03:40:52 -0700
Subject: [PATCH 054/195] Update .copyright.hook (#10560)
---
.copyright.hook | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/.copyright.hook b/.copyright.hook
index 09afff2072..86b16ebdc4 100644
--- a/.copyright.hook
+++ b/.copyright.hook
@@ -9,7 +9,7 @@ import subprocess
import platform
COPYRIGHT = '''
- Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved.
+Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
From 6d371e452e880eb8dba515408517f8ac418358ed Mon Sep 17 00:00:00 2001
From: Yan Chunwei <yanchunwei@outlook.com>
Date: Thu, 10 May 2018 20:04:44 +0800
Subject: [PATCH 055/195] init Inference top APIs (#10549)
---
contrib/inference/README.md | 27 ++++++++++
contrib/inference/paddle_inference_api.h | 69 ++++++++++++++++++++++++
2 files changed, 96 insertions(+)
create mode 100644 contrib/inference/README.md
create mode 100644 contrib/inference/paddle_inference_api.h
diff --git a/contrib/inference/README.md b/contrib/inference/README.md
new file mode 100644
index 0000000000..20969fac6c
--- /dev/null
+++ b/contrib/inference/README.md
@@ -0,0 +1,27 @@
+# Embed Paddle Inference in Your Application
+
+Paddle inference offers the APIs in `C` and `C++` languages.
+
+One can easily deploy a model trained by Paddle following the steps as below:
+
+1. Optimize the native model;
+2. Write some codes for deployment.
+
+
+Let's explain the steps in detail.
+
+## Optimize the native Fluid Model
+
+The native model that get from the training phase needs to be optimized for that.
+
+- Clean the noise such as the cost operators that do not need inference;
+- Prune unnecessary computation fork that has nothing to do with the output;
+- Remove extraneous variables;
+- Memory reuse for native Fluid executor;
+- Translate the model storage format to some third-party engine's, so that the inference API can utilize the engine for acceleration;
+
+We have an official tool to do the optimization, call `paddle_inference_optimize --help` for more information.
+
+## Write some codes
+
+Read `paddle_inference_api.h` for more information.
diff --git a/contrib/inference/paddle_inference_api.h b/contrib/inference/paddle_inference_api.h
new file mode 100644
index 0000000000..dbaa7c95b9
--- /dev/null
+++ b/contrib/inference/paddle_inference_api.h
@@ -0,0 +1,69 @@
+/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License. */
+
+#pragma once
+
+#include <string>
+#include <vector>
+
+namespace paddle {
+
+class Predictor {
+public:
+ struct Attr;
+ Predictor() = default;
+
+ // Build the network before inference.
+ bool Init(const Attr& attr);
+
+ // Predict an record.
+ // Arguments:
+ // inputs: the name of the input variables.
+ // outputs: the name of the output varaibles.
+ // input_shapes: the shape of the input variables.
+ // output_shapes: the shape of the output variables.
+ // input_data: the data of the input variables.
+ // output_data: the data of the output variables.
+ bool Run(const std::vector<std::string>& inputs,
+ const std::vector<std::string>& outputs,
+ const std::vector<std::vector<int>>& input_shapes,
+ const std::vector<std::vector<int>>& output_shapes,
+ const std::vector<std::vector<float>>& input_data,
+ std::vector<std::vector<float>>* output_data);
+
+ // Clone a predictor that share the model weights.
+ Predictor* Clone();
+
+ // Destroy the Predictor.
+ ~Predictor();
+
+ struct Attr {
+ enum class EngineKind;
+
+ std::string model_dir; // path to the model directory.
+ bool enable_engine{false}; // Enable to execute (part of) the model on
+ // third-party engines.
+ EngineKind engine_kind{Attr::EngineKind::kNone};
+
+ enum class EngineKind {
+ kNone = -1, // Use the native Fluid facility.
+ kAnakin, // Use Anakin for inference.
+ kTensorRT, // Use TensorRT for inference.
+ kAutoMixedAnakin, // Automatically mix Fluid with Anakin.
+ kAutoMixedTensorRT, // Automatically mix Fluid with TensorRT.
+ };
+ };
+};
+
+} // namespace paddle
From a89cd46700524b2fd2bec7407464e344030b8158 Mon Sep 17 00:00:00 2001
From: chengduoZH <zhaochengduo@163.com>
Date: Thu, 10 May 2018 20:34:11 +0800
Subject: [PATCH 056/195] Wait VarDummyHandle generated
---
.../fluid/framework/details/computation_op_handle.cc | 2 +-
paddle/fluid/framework/details/op_handle_base.cc | 2 +-
paddle/fluid/framework/details/send_op_handle.cc | 11 ++++++++++-
3 files changed, 12 insertions(+), 3 deletions(-)
diff --git a/paddle/fluid/framework/details/computation_op_handle.cc b/paddle/fluid/framework/details/computation_op_handle.cc
index ffbe2094a4..df05bb0633 100644
--- a/paddle/fluid/framework/details/computation_op_handle.cc
+++ b/paddle/fluid/framework/details/computation_op_handle.cc
@@ -35,7 +35,7 @@ void ComputationOpHandle::RunImpl() {
bool ComputationOpHandle::NeedWait(VarHandleBase *in_var) {
bool need_wait =
- dynamic_cast<VarHandle *>(in_var) && in_var->generated_op_ &&
+ in_var && in_var->generated_op_ &&
in_var->generated_op_->DeviceContext(place_) != dev_ctxes_[place_];
return need_wait;
}
diff --git a/paddle/fluid/framework/details/op_handle_base.cc b/paddle/fluid/framework/details/op_handle_base.cc
index b05b9d95e7..6b064650b4 100644
--- a/paddle/fluid/framework/details/op_handle_base.cc
+++ b/paddle/fluid/framework/details/op_handle_base.cc
@@ -105,7 +105,7 @@ void OpHandleBase::WaitInputVarGenerated(const platform::Place &place) {
}
bool OpHandleBase::NeedWait(VarHandleBase *in_var) {
- return dynamic_cast<VarHandle *>(in_var) && in_var->generated_op_;
+ return in_var && in_var->generated_op_;
}
void OpHandleBase::RunAndRecordEvent(const std::function<void()> &callback) {
diff --git a/paddle/fluid/framework/details/send_op_handle.cc b/paddle/fluid/framework/details/send_op_handle.cc
index 01f3a9df76..7109659dd7 100644
--- a/paddle/fluid/framework/details/send_op_handle.cc
+++ b/paddle/fluid/framework/details/send_op_handle.cc
@@ -26,8 +26,17 @@ SendOpHandle::SendOpHandle(const framework::OpDesc &op_desc,
place_(place) {}
void SendOpHandle::RunImpl() {
+ // TODO(wuyi): need further analysis whether wait VarDummyHandle.
// Wait input done
- WaitInputVarGenerated(place_);
+ for (auto *in : inputs_) {
+ auto &p = static_cast<VarHandle *>(in)->place_;
+ if (in->DebugString() == "dummy") { // HACK
+ continue;
+ }
+ if (in->generated_op_) {
+ in->generated_op_->RecordWaitEventOnCtx(dev_ctxes_[p]);
+ }
+ }
auto &tmp_scope = local_scope_->FindVar(kLocalExecScopeName)->Get<Scope *>();
// FIXME(wuyi): can not use RunAndRecordEvent here, for it will cause dead
// lock.
From 28a6037bb8e6a3623919dd7bde2c6d36cc35b0bd Mon Sep 17 00:00:00 2001
From: Siddharth Goyal <vi.siddharth78@gmail.com>
Date: Thu, 10 May 2018 13:12:00 -0700
Subject: [PATCH 057/195] Fix lod check in FP16 test for save_op (#10508)
---
paddle/fluid/operators/save_load_op_test.cc | 14 ++++++++++++++
1 file changed, 14 insertions(+)
diff --git a/paddle/fluid/operators/save_load_op_test.cc b/paddle/fluid/operators/save_load_op_test.cc
index 8d5c17490c..c4fcc61af4 100644
--- a/paddle/fluid/operators/save_load_op_test.cc
+++ b/paddle/fluid/operators/save_load_op_test.cc
@@ -70,7 +70,14 @@ TEST(SaveFP16Op, CPU) {
auto var = scope.Var("test_var");
auto tensor = var->GetMutable<paddle::framework::LoDTensor>();
tensor->Resize({3, 10});
+ paddle::framework::LoD expect_lod;
+ expect_lod.resize(1);
+ expect_lod[0].push_back(0);
+ expect_lod[0].push_back(1);
+ expect_lod[0].push_back(2);
+ expect_lod[0].push_back(3);
+ tensor->set_lod(expect_lod);
float* expect = tensor->mutable_data<float>(place);
for (int64_t i = 0; i < tensor->numel(); ++i) {
expect[i] = static_cast<float>(paddle::platform::float16(i));
@@ -93,6 +100,13 @@ TEST(SaveFP16Op, CPU) {
for (int64_t i = 0; i < tensor->numel(); ++i) {
EXPECT_EQ(expect[i], static_cast<float>(actual[i]));
}
+ auto& actual_lod = target->lod();
+ EXPECT_EQ(expect_lod.size(), actual_lod.size());
+ for (size_t i = 0; i < expect_lod.size(); ++i) {
+ for (size_t j = 0; j < expect_lod[i].size(); ++j) {
+ EXPECT_EQ(expect_lod[i][j], actual_lod[i][j]);
+ }
+ }
}
TEST(LoadFP16Op, CPU) {
From 283c4dbe57c0af9f13d121a6ed9f9b85a9406fa2 Mon Sep 17 00:00:00 2001
From: Siddharth Goyal <vi.siddharth78@gmail.com>
Date: Thu, 10 May 2018 13:12:22 -0700
Subject: [PATCH 058/195] Add FP16 option in save_combine_op (#10471)
* Add FP16 option in save_combine_op
* Fix casting issue
---
paddle/fluid/operators/save_combine_op.cc | 28 +++-
.../operators/save_load_combine_op_test.cc | 148 ++++++++++++++----
2 files changed, 141 insertions(+), 35 deletions(-)
diff --git a/paddle/fluid/operators/save_combine_op.cc b/paddle/fluid/operators/save_combine_op.cc
index 94703393bf..36e7522948 100644
--- a/paddle/fluid/operators/save_combine_op.cc
+++ b/paddle/fluid/operators/save_combine_op.cc
@@ -18,6 +18,7 @@ limitations under the License. */
#include <numeric>
#include <sstream>
#include "paddle/fluid/framework/data_type.h"
+#include "paddle/fluid/framework/data_type_transform.h"
#include "paddle/fluid/framework/framework.pb.h"
#include "paddle/fluid/framework/lod_tensor.h"
#include "paddle/fluid/framework/op_registry.h"
@@ -69,6 +70,7 @@ class SaveCombineOp : public framework::OperatorBase {
const platform::Place &place) const override {
auto filename = Attr<std::string>("file_path");
auto overwrite = Attr<bool>("overwrite");
+ auto save_as_fp16 = Attr<bool>("save_as_fp16");
bool is_present = FileExists(filename);
if (is_present && !overwrite) {
@@ -100,8 +102,24 @@ class SaveCombineOp : public framework::OperatorBase {
inp_var_names[i]);
auto &tensor = var->Get<framework::LoDTensor>();
- // Serialize tensor
- framework::SerializeToStream(fout, tensor, dev_ctx);
+ // Serialize tensors one by one
+
+ // Check types to see if a fp16 transformation is required
+ auto in_dtype = framework::ToDataType(tensor.type());
+ auto out_dtype =
+ save_as_fp16 ? framework::proto::VarType::FP16 : in_dtype;
+
+ if (in_dtype != out_dtype) {
+ auto in_kernel_type = framework::OpKernelType(in_dtype, place);
+ auto out_kernel_type = framework::OpKernelType(out_dtype, place);
+ framework::LoDTensor out;
+ // copy LoD info to the new tensor
+ out.set_lod(tensor.lod());
+ framework::TransDataType(in_kernel_type, out_kernel_type, tensor, &out);
+ framework::SerializeToStream(fout, out, dev_ctx);
+ } else {
+ framework::SerializeToStream(fout, tensor, dev_ctx);
+ }
}
fout.close();
}
@@ -125,6 +143,12 @@ to a file on disk.
"(boolean, default true)"
"Overwrite the output file if it exists.")
.SetDefault(true);
+ AddAttr<bool>("save_as_fp16",
+ "(boolean, default false)"
+ "If true, the tensor will be converted to float16 data "
+ "type and then saved. Otherwise, the tensor will be "
+ "directly saved without data type conversion.")
+ .SetDefault(false);
AddAttr<std::string>(
"file_path",
"(string)"
diff --git a/paddle/fluid/operators/save_load_combine_op_test.cc b/paddle/fluid/operators/save_load_combine_op_test.cc
index 2773c32a0a..47618c51d9 100644
--- a/paddle/fluid/operators/save_load_combine_op_test.cc
+++ b/paddle/fluid/operators/save_load_combine_op_test.cc
@@ -17,15 +17,17 @@ limitations under the License. */
#include <vector>
#include "gtest/gtest.h"
#include "paddle/fluid/framework/op_registry.h"
+#include "paddle/fluid/platform/float16.h"
USE_NO_KERNEL_OP(save_combine);
USE_NO_KERNEL_OP(load_combine);
-int* CreateForSaveCombineOp(int x, int y, const std::vector<int>& lod_info,
- std::string var_name,
- const paddle::platform::CPUPlace& place,
- paddle::framework::Scope* scope,
- paddle::framework::LoD* expect_lod) {
+template <typename T, typename U>
+T* CreateForSaveCombineOp(int x, int y, const std::vector<int>& lod_info,
+ std::string var_name,
+ const paddle::platform::CPUPlace& place,
+ paddle::framework::Scope* scope,
+ paddle::framework::LoD* expect_lod) {
auto var = scope->Var(var_name);
auto tensor = var->GetMutable<paddle::framework::LoDTensor>();
tensor->Resize({x, y});
@@ -34,9 +36,10 @@ int* CreateForSaveCombineOp(int x, int y, const std::vector<int>& lod_info,
(*expect_lod)[0].push_back(lod_info[i]);
}
tensor->set_lod(*expect_lod);
- int* expect = tensor->mutable_data<int>(place);
+ T* expect = tensor->mutable_data<T>(place);
for (int64_t i = 0; i < tensor->numel(); ++i) {
- expect[i] = static_cast<int>(i);
+ expect[i] = static_cast<T>(
+ static_cast<U>(i)); // For FP16, we intend to do float(float16(i))
}
return expect;
}
@@ -48,18 +51,20 @@ paddle::framework::LoDTensor* GeneratePlaceholderBeforeLoad(
return target;
}
-int* GetValuesAfterLoadCombineOp(paddle::framework::LoDTensor* target,
- const paddle::framework::Scope& scope,
- paddle::framework::LoD* actual_lod) {
- int* actual = target->data<int>();
+template <typename T>
+T* GetValuesAfterLoadCombineOp(paddle::framework::LoDTensor* target,
+ const paddle::framework::Scope& scope,
+ paddle::framework::LoD* actual_lod) {
+ T* actual = target->data<T>();
*actual_lod = target->lod();
return actual;
}
-void CheckValues(int* expect, int* actual, paddle::framework::LoD expect_lod,
- paddle::framework::LoD actual_lod, const int& numel) {
- for (int64_t i = 0; i < numel; ++i) {
- EXPECT_EQ(expect[i], actual[i]);
+template <typename T, typename U>
+void CheckValues(T* expect, U* actual, const paddle::framework::LoD& expect_lod,
+ const paddle::framework::LoD& actual_lod, const int& numel) {
+ for (int i = 0; i < numel; ++i) {
+ EXPECT_EQ(expect[i], static_cast<T>(actual[i]));
}
EXPECT_EQ(expect_lod.size(), actual_lod.size());
for (size_t i = 0; i < expect_lod.size(); ++i) {
@@ -78,26 +83,26 @@ TEST(SaveLoadCombineOp, CPU) {
std::vector<int> lod1 = {0, 1, 2, 3, 10};
int numel1 = 100;
paddle::framework::LoD expect_lod1;
- int* expect1 = CreateForSaveCombineOp(10, 10, lod1, "test_var1", place,
- &scope, &expect_lod1);
+ int* expect1 = CreateForSaveCombineOp<int, int>(10, 10, lod1, "test_var1",
+ place, &scope, &expect_lod1);
std::vector<int> lod2 = {0, 2, 5, 10};
int numel2 = 200;
paddle::framework::LoD expect_lod2;
- int* expect2 = CreateForSaveCombineOp(10, 20, lod2, "test_var2", place,
- &scope, &expect_lod2);
+ int* expect2 = CreateForSaveCombineOp<int, int>(10, 20, lod2, "test_var2",
+ place, &scope, &expect_lod2);
std::vector<int> lod3 = {0, 2, 3, 20};
int numel3 = 4000;
paddle::framework::LoD expect_lod3;
- int* expect3 = CreateForSaveCombineOp(20, 200, lod3, "test_var3", place,
- &scope, &expect_lod3);
+ int* expect3 = CreateForSaveCombineOp<int, int>(20, 200, lod3, "test_var3",
+ place, &scope, &expect_lod3);
std::vector<int> lod4 = {0, 1, 20};
int numel4 = 1000;
paddle::framework::LoD expect_lod4;
- int* expect4 = CreateForSaveCombineOp(20, 50, lod4, "test_var4", place,
- &scope, &expect_lod4);
+ int* expect4 = CreateForSaveCombineOp<int, int>(20, 50, lod4, "test_var4",
+ place, &scope, &expect_lod4);
// Set attributes
std::string filename = "check_tensor.ls";
@@ -123,15 +128,92 @@ TEST(SaveLoadCombineOp, CPU) {
load_combine_op->Run(scope, place);
paddle::framework::LoD actual_lod1, actual_lod2, actual_lod3, actual_lod4;
- int* actual1 = GetValuesAfterLoadCombineOp(target1, scope, &actual_lod1);
- int* actual2 = GetValuesAfterLoadCombineOp(target2, scope, &actual_lod2);
- int* actual3 = GetValuesAfterLoadCombineOp(target3, scope, &actual_lod3);
- int* actual4 = GetValuesAfterLoadCombineOp(target4, scope, &actual_lod4);
-
- CheckValues(expect1, actual1, expect_lod1, actual_lod1, numel1);
- CheckValues(expect2, actual2, expect_lod2, actual_lod2, numel2);
- CheckValues(expect3, actual3, expect_lod3, actual_lod3, numel3);
- CheckValues(expect4, actual4, expect_lod4, actual_lod4, numel4);
+ int* actual1 = GetValuesAfterLoadCombineOp<int>(target1, scope, &actual_lod1);
+ int* actual2 = GetValuesAfterLoadCombineOp<int>(target2, scope, &actual_lod2);
+ int* actual3 = GetValuesAfterLoadCombineOp<int>(target3, scope, &actual_lod3);
+ int* actual4 = GetValuesAfterLoadCombineOp<int>(target4, scope, &actual_lod4);
+
+ CheckValues<int, int>(expect1, actual1, expect_lod1, actual_lod1, numel1);
+ CheckValues<int, int>(expect2, actual2, expect_lod2, actual_lod2, numel2);
+ CheckValues<int, int>(expect3, actual3, expect_lod3, actual_lod3, numel3);
+ CheckValues<int, int>(expect4, actual4, expect_lod4, actual_lod4, numel4);
+}
+
+// FP16 version of SaveLoadCombineOp Test
+TEST(SaveLoadCombineFP16Op, CPU) {
+ paddle::framework::Scope scope;
+ paddle::platform::CPUPlace place;
+
+ std::vector<int> lod1 = {0, 1, 2, 3, 10};
+ int numel1 = 100;
+ paddle::framework::LoD expect_lod1;
+ float* expect1 = CreateForSaveCombineOp<float, paddle::platform::float16>(
+ 10, 10, lod1, "test_var1", place, &scope, &expect_lod1);
+
+ std::vector<int> lod2 = {0, 2, 5, 10};
+ int numel2 = 200;
+ paddle::framework::LoD expect_lod2;
+ float* expect2 = CreateForSaveCombineOp<float, paddle::platform::float16>(
+ 10, 20, lod2, "test_var2", place, &scope, &expect_lod2);
+
+ std::vector<int> lod3 = {0, 20};
+ int numel3 = 4000;
+ paddle::framework::LoD expect_lod3;
+ float* expect3 = CreateForSaveCombineOp<float, paddle::platform::float16>(
+ 20, 200, lod3, "test_var3", place, &scope, &expect_lod3);
+
+ std::vector<int> lod4 = {0, 1, 20};
+ int numel4 = 1000;
+ paddle::framework::LoD expect_lod4;
+ float* expect4 = CreateForSaveCombineOp<float, paddle::platform::float16>(
+ 20, 50, lod4, "test_var4", place, &scope, &expect_lod4);
+
+ // Set attributes
+ std::string filename = "check_tensor_fp16.ls";
+ paddle::framework::AttributeMap attrs;
+ attrs.insert({"file_path", std::string(filename)});
+ attrs.insert({"save_as_fp16", true});
+
+ // Run the save_combine_op
+ auto save_combine_op = paddle::framework::OpRegistry::CreateOp(
+ "save_combine",
+ {{"X", {"test_var1", "test_var2", "test_var3", "test_var4"}}}, {}, attrs);
+ save_combine_op->Run(scope, place);
+
+ // Set up output vars
+ auto target1 = GeneratePlaceholderBeforeLoad("out_var1", &scope);
+ auto target2 = GeneratePlaceholderBeforeLoad("out_var2", &scope);
+ auto target3 = GeneratePlaceholderBeforeLoad("out_var3", &scope);
+ auto target4 = GeneratePlaceholderBeforeLoad("out_var4", &scope);
+
+ // Run the load_combine_op
+ auto load_combine_op = paddle::framework::OpRegistry::CreateOp(
+ "load_combine", {},
+ {{"Out", {"out_var1", "out_var2", "out_var3", "out_var4"}}}, attrs);
+ load_combine_op->Run(scope, place);
+
+ paddle::framework::LoD actual_lod1, actual_lod2, actual_lod3, actual_lod4;
+ paddle::platform::float16* actual1 =
+ GetValuesAfterLoadCombineOp<paddle::platform::float16>(target1, scope,
+ &actual_lod1);
+ paddle::platform::float16* actual2 =
+ GetValuesAfterLoadCombineOp<paddle::platform::float16>(target2, scope,
+ &actual_lod2);
+ paddle::platform::float16* actual3 =
+ GetValuesAfterLoadCombineOp<paddle::platform::float16>(target3, scope,
+ &actual_lod3);
+ paddle::platform::float16* actual4 =
+ GetValuesAfterLoadCombineOp<paddle::platform::float16>(target4, scope,
+ &actual_lod4);
+
+ CheckValues<float, paddle::platform::float16>(expect1, actual1, expect_lod1,
+ actual_lod1, numel1);
+ CheckValues<float, paddle::platform::float16>(expect2, actual2, expect_lod2,
+ actual_lod2, numel2);
+ CheckValues<float, paddle::platform::float16>(expect3, actual3, expect_lod3,
+ actual_lod3, numel3);
+ CheckValues<float, paddle::platform::float16>(expect4, actual4, expect_lod4,
+ actual_lod4, numel4);
}
// Test with original SaveLoadTest
@@ -141,7 +223,7 @@ TEST(SaveLoadTestWithCombineOp, CPU) {
auto var = scope.Var("test_var");
auto tensor = var->GetMutable<paddle::framework::LoDTensor>();
- tensor->Resize({3, 10});
+ tensor->Resize({3, 4000});
paddle::framework::LoD expect_lod;
expect_lod.resize(1);
expect_lod[0].push_back(0);
From 95314a2385cf775eca8834fb92de846f98d2fca1 Mon Sep 17 00:00:00 2001
From: Tao Luo <luotao02@baidu.com>
Date: Fri, 11 May 2018 04:37:38 +0800
Subject: [PATCH 059/195] fix dead link of mkldnn and others (#10567)
---
doc/fluid/design/motivation/api.md | 3 +--
doc/fluid/design/multi_devices/operator_kernel_type.md | 2 +-
2 files changed, 2 insertions(+), 3 deletions(-)
diff --git a/doc/fluid/design/motivation/api.md b/doc/fluid/design/motivation/api.md
index e6a4638d91..bc222564e3 100644
--- a/doc/fluid/design/motivation/api.md
+++ b/doc/fluid/design/motivation/api.md
@@ -77,8 +77,7 @@ print "The sematic-vector of testA: ", paddle.infer(fA, parameters, testA)
### Example 2. Sharing Parameters between "Models"
-We use [GAN](https://github.com/PaddlePaddle/book/tree/develop/gan) in
-this example. In the following example program, `d0` and `d1`
+We use GAN in this example. In the following example program, `d0` and `d1`
correspond to the two networks in the following figure:
<img src="https://github.com/wangyang59/book/raw/00036f4b0da5225041a6824587c1a01cf20159b1/gan/image/gan_ig.png" width=400 />
diff --git a/doc/fluid/design/multi_devices/operator_kernel_type.md b/doc/fluid/design/multi_devices/operator_kernel_type.md
index 8c1bc8f76a..5e391bd62b 100644
--- a/doc/fluid/design/multi_devices/operator_kernel_type.md
+++ b/doc/fluid/design/multi_devices/operator_kernel_type.md
@@ -75,7 +75,7 @@ Different layout leads to different implementation of the operator kernel. There
- The inference of Layout is at run-time, not at compile-time.
-- Every operator has to implement different kernels for different layouts. Let's take MKLDNN as an example. If we want to implement an MKLDNN convolution operator, we have to implement all the kernels for different layouts, which are listed [here](http://01org.github.io/mkl-dnn/structmkldnn_1_1memory.html). And we will have a special macro to register kernels for MKLDNN operators.
+- Every operator has to implement different kernels for different layouts. Let's take MKLDNN as an example. If we want to implement an MKLDNN convolution operator, we have to implement all the kernels for different layouts, which are listed [here](http://intel.github.io/mkl-dnn/structmkldnn_1_1memory.html). And we will have a special macro to register kernels for MKLDNN operators.
`Layout` is also defined as a enum variable:
From f3ffec23cf3d2975019c67ab2e07c263ca09e74f Mon Sep 17 00:00:00 2001
From: Lei Wang <bestwanglei@gmail.com>
Date: Thu, 10 May 2018 19:20:03 -0700
Subject: [PATCH 060/195] CI: exit when fail any step. (#10579)
---
paddle/fluid/inference/tensorrt/test_engine.cc | 2 +-
paddle/scripts/paddle_build.sh | 1 +
paddle/scripts/paddle_docker_build.sh | 2 +-
3 files changed, 3 insertions(+), 2 deletions(-)
diff --git a/paddle/fluid/inference/tensorrt/test_engine.cc b/paddle/fluid/inference/tensorrt/test_engine.cc
index 69dbb9a3f2..e635f0f87d 100644
--- a/paddle/fluid/inference/tensorrt/test_engine.cc
+++ b/paddle/fluid/inference/tensorrt/test_engine.cc
@@ -98,7 +98,7 @@ TEST_F(TensorRTEngineTest, add_layer_multi_dim) {
float x_v[2] = {1.0, 2.0};
engine_->SetInputFromCPU("x", reinterpret_cast<void*>(&x_v),
- 2 * sizeof(float));
+ 2 * sizeof(float));
engine_->Execute(1);
LOG(INFO) << "to get output";
diff --git a/paddle/scripts/paddle_build.sh b/paddle/scripts/paddle_build.sh
index c9b49adef7..5bef232cd8 100755
--- a/paddle/scripts/paddle_build.sh
+++ b/paddle/scripts/paddle_build.sh
@@ -473,6 +473,7 @@ EOF
}
function main() {
+ set -e
local CMD=$1
init
case $CMD in
diff --git a/paddle/scripts/paddle_docker_build.sh b/paddle/scripts/paddle_docker_build.sh
index 0bf8c79892..ac32bf0292 100755
--- a/paddle/scripts/paddle_docker_build.sh
+++ b/paddle/scripts/paddle_docker_build.sh
@@ -59,7 +59,7 @@ EOL
if [ ! -d "${HOME}/.ccache" ]; then
mkdir ${HOME}/.ccache
fi
- set -x
+ set -ex
${DOCKER_CMD} run -it \
--name $CONTAINER_ID \
${DOCKER_ENV} \
From ba57348f8f534e4d658d88f481f68361ac7904f1 Mon Sep 17 00:00:00 2001
From: fengjiayi <fengjiayi@baidu.com>
Date: Fri, 11 May 2018 10:25:52 +0800
Subject: [PATCH 061/195] trainer.test() (#10453)
* a draft of trainer.test()
* polish trainer.test()
* polish trainer.test()
* update code format
* update
* polish code
* polish code
* polish code
* Make trainer.test follow the rule of returning [loss, metric, metric, ..]
---
python/paddle/fluid/framework.py | 31 ++++++-
python/paddle/fluid/layers/io.py | 4 +-
.../word2vec/no_test_word2vec_new_api.py | 14 +++-
python/paddle/fluid/trainer.py | 82 +++++++++++++++----
4 files changed, 104 insertions(+), 27 deletions(-)
diff --git a/python/paddle/fluid/framework.py b/python/paddle/fluid/framework.py
index d7eda619c3..28e54f5492 100644
--- a/python/paddle/fluid/framework.py
+++ b/python/paddle/fluid/framework.py
@@ -160,6 +160,7 @@ class Variable(object):
persistable=None,
error_clip=None,
stop_gradient=False,
+ is_data=False,
**kwargs):
self.block = block
self.error_clip = error_clip
@@ -238,6 +239,7 @@ class Variable(object):
self.block.vars[name] = self
self.op = None
self.stop_gradient = stop_gradient
+ self.is_data = is_data
def __str__(self):
return self.to_string(True)
@@ -475,7 +477,7 @@ class Operator(object):
if isinstance(attrs[attr_name], Block):
self.desc.set_block_attr(attr_name, attrs[attr_name].desc)
elif isinstance(attrs[attr_name], core.BlockDesc) or \
- isinstance(attrs[attr_name], core.ProgramDesc):
+ isinstance(attrs[attr_name], core.ProgramDesc):
self.desc.set_serialized_attr(
attr_name, attrs[attr_name].serialize_to_string())
else:
@@ -978,7 +980,8 @@ class Block(object):
shape=var.shape,
dtype=var.dtype,
type=var.type,
- persistable=True)
+ persistable=True,
+ is_data=var.is_data)
else:
ret_var = self.create_var(
name=var.name,
@@ -986,7 +989,8 @@ class Block(object):
dtype=var.dtype,
type=var.type,
lod_level=var.lod_level,
- persistable=True)
+ persistable=True,
+ is_data=var.is_data)
return ret_var
@@ -1051,6 +1055,7 @@ class Program(object):
p.sync_with_cpp()
p.copy_param_info_from(self)
+ p.copy_data_info_from(self)
return p
def prune(self, targets):
@@ -1172,6 +1177,26 @@ class Program(object):
"program, with represent the same topology")
self.global_block().copy_param_info_from(other.global_block())
+ def copy_data_info_from(self, other):
+ """
+ Copy the information of data variables from other program.
+ Args:
+ other(Program): Other program
+
+ Returns:
+ None
+ """
+ if not isinstance(other, Program):
+ raise TypeError("copy_param_info_from should be invoked with "
+ "Program")
+
+ if len(self.blocks) != len(other.blocks):
+ raise ValueError("copy_param_info_from should be invoked with two "
+ "program, with represent the same topology")
+ for var in other.global_block().vars.itervalues():
+ if var.is_data:
+ self.global_block().var(var.name).is_data = True
+
def list_vars(self):
for each_block in self.blocks:
for each_var in each_block.vars.itervalues():
diff --git a/python/paddle/fluid/layers/io.py b/python/paddle/fluid/layers/io.py
index 0a6befd148..4d6ee3c51b 100644
--- a/python/paddle/fluid/layers/io.py
+++ b/python/paddle/fluid/layers/io.py
@@ -78,8 +78,8 @@ def data(name,
dtype=dtype,
type=type,
stop_gradient=stop_gradient,
- lod_level=lod_level)
- data_var.is_data = True
+ lod_level=lod_level,
+ is_data=True)
return data_var
diff --git a/python/paddle/fluid/tests/book/high-level-api/word2vec/no_test_word2vec_new_api.py b/python/paddle/fluid/tests/book/high-level-api/word2vec/no_test_word2vec_new_api.py
index 35e163dc9d..93f7757a66 100644
--- a/python/paddle/fluid/tests/book/high-level-api/word2vec/no_test_word2vec_new_api.py
+++ b/python/paddle/fluid/tests/book/high-level-api/word2vec/no_test_word2vec_new_api.py
@@ -80,8 +80,11 @@ def inference_program(is_sparse):
def train_program(is_sparse):
- next_word = fluid.layers.data(name='nextw', shape=[1], dtype='int64')
+ # The declaration of 'next_word' must be after the invoking of inference_program,
+ # or the data input order of train program would be [next_word, firstw, secondw,
+ # thirdw, forthw], which is not correct.
predict_word = inference_program(is_sparse)
+ next_word = fluid.layers.data(name='nextw', shape=[1], dtype='int64')
cost = fluid.layers.cross_entropy(input=predict_word, label=next_word)
avg_cost = fluid.layers.mean(cost)
return avg_cost
@@ -90,14 +93,17 @@ def train_program(is_sparse):
def train(use_cuda, is_sparse, save_path):
train_reader = paddle.batch(
paddle.dataset.imikolov.train(word_dict, N), BATCH_SIZE)
+ test_reader = paddle.batch(
+ paddle.dataset.imikolov.test(word_dict, N), BATCH_SIZE)
place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
def event_handler(event):
- print type(event)
+ # print type(event)
if isinstance(event, fluid.EndEpochEvent):
- avg_cost = trainer.test(reader=paddle.dataset.imikolov.test(
- word_dict, N))
+ outs = trainer.test(reader=test_reader)
+ avg_cost = outs[0]
+ print("loss= ", avg_cost)
if avg_cost < 5.0:
trainer.save_params(save_path)
diff --git a/python/paddle/fluid/trainer.py b/python/paddle/fluid/trainer.py
index d44cb16bfb..30b58b465e 100644
--- a/python/paddle/fluid/trainer.py
+++ b/python/paddle/fluid/trainer.py
@@ -75,11 +75,15 @@ class Trainer(object):
self.train_program = framework.Program()
with framework.program_guard(self.train_program, self.startup_program):
- loss = program_func()
+ program_func_outs = program_func()
+ self.test_outputs = program_func_outs if isinstance(
+ program_func_outs, list) else [program_func_outs]
+ self.test_program = self.train_program.clone()
if not isinstance(optimizer, opt_module.Optimizer):
raise TypeError(
"The optimizer should be an instance of Optimizer")
-
+ # The fisrt element of program_func_outs is loss.
+ loss = self.test_outputs[0]
optimize_ops, params_grads = optimizer.minimize(loss)
self.place = Trainer._check_and_get_place(place)
@@ -168,8 +172,17 @@ class Trainer(object):
self._train_by_executor(num_epochs, event_handler, reader, feed_order)
- def test(self, reader):
- pass
+ def test(self, reader, feed_order=None):
+ """
+ Test the model on given test data
+
+ Args:
+ reader: The reader that yields test data.
+ feed_order: Feeding order of reader. None will following the defining
+ order in program
+ """
+
+ return self._test_by_executor(reader, feed_order, self.test_outputs)
def save_params(self, param_path):
# reference: save_persistables in io.py
@@ -225,22 +238,10 @@ class Trainer(object):
"""
with self._prog_and_scope_guard():
- exe = executor.Executor(self.place)
- if feed_order is None:
- feed_var_list = [
- var
- for var in self.train_program.global_block(
- ).vars.itervalues()
- if hasattr(var, 'is_data') and var.is_data
- ]
- else:
- feed_var_list = [
- self.train_program.global_block().var(var_name)
- for var_name in feed_order
- ]
-
+ feed_var_list = build_feed_var_list(self.train_program, feed_order)
feeder = data_feeder.DataFeeder(
feed_list=feed_var_list, place=self.place)
+ exe = executor.Executor(self.place)
for epoch_id in range(num_epochs):
event_handler(BeginEpochEvent(epoch_id))
for step_id, data in enumerate(reader()):
@@ -248,3 +249,48 @@ class Trainer(object):
exe.run(feed=feeder.feed(data), fetch_list=[])
event_handler(EndStepEvent(epoch_id, step_id))
event_handler(EndEpochEvent(epoch_id))
+
+ def _test_by_executor(self, reader, feed_order, fetch_list):
+ with executor.scope_guard(self.scope):
+ feed_var_list = build_feed_var_list(self.test_program, feed_order)
+ feeder = data_feeder.DataFeeder(
+ feed_list=feed_var_list, place=self.place)
+ exe = executor.Executor(self.place)
+ accumulated = len(fetch_list) * [0]
+ count = 0
+ for data in reader():
+ outs = exe.run(program=self.test_program,
+ feed=feeder.feed(data),
+ fetch_list=fetch_list)
+ accumulated = [x[0] + x[1][0] for x in zip(accumulated, outs)]
+ count += 1
+
+ return [x / count for x in accumulated]
+
+
+def build_feed_var_list(program, feed_order):
+ if not isinstance(program, framework.Program):
+ raise TypeError("The 'program' should be an object of Program")
+
+ if feed_order is None:
+ feed_var_list = [
+ var for var in program.global_block().vars.itervalues()
+ if var.is_data
+ ]
+ elif isinstance(feed_order, list):
+ feed_var_list = [
+ program.global_block().var(var_name) for var_name in feed_order
+ ]
+ else:
+ if not isinstance(feed_order, dict):
+ raise TypeError(
+ "The 'feed_order' should be either None, list or dict.")
+ if not sorted(feed_order.values()) == range(len(feed_order)):
+ raise ValueError(
+ "The values of 'feed_order' should be a permutation of [0, len(feed_order))"
+ )
+ sorted_pair_list = sorted(feed_order.items(), key=lambda item: item[1])
+ feed_var_list = [
+ program.global_block().var(pair[0]) for pair in sorted_pair_list
+ ]
+ return feed_var_list
From 66590a0b88f459461ac950d6ba502d32cbc7cb81 Mon Sep 17 00:00:00 2001
From: yuyang18 <reyoung@126.com>
Date: Fri, 11 May 2018 10:58:18 +0800
Subject: [PATCH 062/195] Fix typo in blas_impl.h
---
paddle/fluid/operators/math/blas_impl.h | 6 +++---
1 file changed, 3 insertions(+), 3 deletions(-)
diff --git a/paddle/fluid/operators/math/blas_impl.h b/paddle/fluid/operators/math/blas_impl.h
index 577cbe3beb..14b3624b42 100644
--- a/paddle/fluid/operators/math/blas_impl.h
+++ b/paddle/fluid/operators/math/blas_impl.h
@@ -172,9 +172,9 @@ void Blas<platform::CPUDeviceContext>::BatchedGEMM(
c_array.data(), &ldc, 1 /* group_count */, &batchCount);
#else
for (int k = 0; k < batchCount; ++k) {
- const float *Ak = &A[k * strideA];
- const float *Bk = &B[k * strideB];
- float *Ck = &C[k * M * N];
+ auto *Ak = &A[k * strideA];
+ auto *Bk = &B[k * strideB];
+ auto *Ck = &C[k * M * N];
this->template GEMM<T>(transA, transB, M, N, K, alpha, Ak, Bk, beta, Ck);
}
#endif
From 329655dd7b4d960f4373b394280bccd444946c00 Mon Sep 17 00:00:00 2001
From: Luo Tao <luotao02@baidu.com>
Date: Thu, 10 May 2018 18:50:49 +0800
Subject: [PATCH 063/195] update mklml version disable building tests and
examples when install mkldnn skip -Werror=unused-result
---
cmake/external/mkldnn.cmake | 7 ++++---
cmake/external/mklml.cmake | 2 +-
2 files changed, 5 insertions(+), 4 deletions(-)
diff --git a/cmake/external/mkldnn.cmake b/cmake/external/mkldnn.cmake
index 83c1cf1457..966c0bafd3 100644
--- a/cmake/external/mkldnn.cmake
+++ b/cmake/external/mkldnn.cmake
@@ -45,9 +45,9 @@ IF(${CBLAS_PROVIDER} STREQUAL "MKLML")
ELSE()
MESSAGE(FATAL_ERROR "Should enable MKLML when build MKLDNN")
ENDIF()
-
-SET(MKLDNN_CFLAG "${CMAKE_C_FLAGS} -Wno-error=strict-overflow")
-SET(MKLDNN_CXXFLAG "${CMAKE_CXX_FLAGS} -Wno-error=strict-overflow")
+SET(MKLDNN_FLAG "-Wno-error=strict-overflow -Wno-error=unused-result -Wno-unused-result")
+SET(MKLDNN_CFLAG "${CMAKE_C_FLAGS} ${MKLDNN_FLAG}")
+SET(MKLDNN_CXXFLAG "${CMAKE_CXX_FLAGS} ${MKLDNN_FLAG}")
ExternalProject_Add(
${MKLDNN_PROJECT}
${EXTERNAL_PROJECT_LOG_ARGS}
@@ -61,6 +61,7 @@ ExternalProject_Add(
CMAKE_ARGS -DMKLROOT=${MKLML_ROOT}
CMAKE_ARGS -DCMAKE_C_FLAGS=${MKLDNN_CFLAG}
CMAKE_ARGS -DCMAKE_CXX_FLAGS=${MKLDNN_CXXFLAG}
+ CMAKE_ARGS -DWITH_TEST=OFF -DWITH_EXAMPLE=OFF
CMAKE_CACHE_ARGS -DCMAKE_INSTALL_PREFIX:PATH=${MKLDNN_INSTALL_DIR}
-DMKLROOT:PATH=${MKLML_ROOT}
)
diff --git a/cmake/external/mklml.cmake b/cmake/external/mklml.cmake
index 796bcf28a1..cebde27504 100644
--- a/cmake/external/mklml.cmake
+++ b/cmake/external/mklml.cmake
@@ -27,7 +27,7 @@ ENDIF()
INCLUDE(ExternalProject)
SET(MKLML_PROJECT "extern_mklml")
-SET(MKLML_VER "mklml_lnx_2018.0.1.20171007")
+SET(MKLML_VER "mklml_lnx_2018.0.3.20180406")
SET(MKLML_URL "http://paddlepaddledeps.bj.bcebos.com/${MKLML_VER}.tgz")
SET(MKLML_SOURCE_DIR "${THIRD_PARTY_PATH}/mklml")
SET(MKLML_DOWNLOAD_DIR "${MKLML_SOURCE_DIR}/src/${MKLML_PROJECT}")
From 07d94bdd821ab4012ae5801a3115353c842e2f84 Mon Sep 17 00:00:00 2001
From: qiaolongfei <qiaolongfei@baidu.com>
Date: Fri, 11 May 2018 11:30:10 +0800
Subject: [PATCH 064/195] fix compile fetch_op_handle on mac
---
paddle/fluid/framework/details/fetch_op_handle.h | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/paddle/fluid/framework/details/fetch_op_handle.h b/paddle/fluid/framework/details/fetch_op_handle.h
index e696a7a9ce..e09bdd1d33 100644
--- a/paddle/fluid/framework/details/fetch_op_handle.h
+++ b/paddle/fluid/framework/details/fetch_op_handle.h
@@ -42,7 +42,7 @@ struct FetchOpHandle : public OpHandleBase {
protected:
void RunImpl() override;
- virtual void WaitInputVarGenerated(const platform::Place &place);
+ void WaitInputVarGenerated(const platform::Place &place) override;
private:
FeedFetchList *data_;
From 3c2a6109ece48d71f80709607aeace650e933763 Mon Sep 17 00:00:00 2001
From: qiaolongfei <qiaolongfei@baidu.com>
Date: Fri, 11 May 2018 12:02:29 +0800
Subject: [PATCH 065/195] fix build computation_op_handle
---
paddle/fluid/framework/details/computation_op_handle.h | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/paddle/fluid/framework/details/computation_op_handle.h b/paddle/fluid/framework/details/computation_op_handle.h
index 36e6f1bf59..f048f973fd 100644
--- a/paddle/fluid/framework/details/computation_op_handle.h
+++ b/paddle/fluid/framework/details/computation_op_handle.h
@@ -36,7 +36,7 @@ struct ComputationOpHandle : public OpHandleBase {
protected:
void RunImpl() override;
- virtual bool NeedWait(VarHandleBase *in_var);
+ bool NeedWait(VarHandleBase *in_var) override;
private:
std::unique_ptr<OperatorBase> op_;
From 711d86bb568fb669f89b5bc034a24b6b85bc67a2 Mon Sep 17 00:00:00 2001
From: yuyang18 <reyoung@126.com>
Date: Thu, 10 May 2018 19:12:00 +0800
Subject: [PATCH 066/195] Polish data_type.h
---
paddle/fluid/framework/CMakeLists.txt | 6 +-
paddle/fluid/framework/data_type.cc | 82 +++++++++++++++++++++++++++
paddle/fluid/framework/data_type.h | 66 +--------------------
3 files changed, 88 insertions(+), 66 deletions(-)
create mode 100644 paddle/fluid/framework/data_type.cc
diff --git a/paddle/fluid/framework/CMakeLists.txt b/paddle/fluid/framework/CMakeLists.txt
index 340b891e41..0dfcf27b1c 100644
--- a/paddle/fluid/framework/CMakeLists.txt
+++ b/paddle/fluid/framework/CMakeLists.txt
@@ -5,11 +5,11 @@ proto_library(framework_proto SRCS framework.proto)
cc_library(ddim SRCS ddim.cc DEPS eigen3 boost)
cc_test(ddim_test SRCS ddim_test.cc DEPS ddim)
nv_test(dim_test SRCS dim_test.cu DEPS ddim)
-
+cc_library(data_type SRCS data_type.cc DEPS framework_proto ddim)
if(WITH_GPU)
- nv_library(tensor SRCS tensor.cc tensor_util.cu DEPS ddim place memory device_context framework_proto)
+ nv_library(tensor SRCS tensor.cc tensor_util.cu DEPS place memory device_context data_type)
else()
- cc_library(tensor SRCS tensor.cc tensor_util.cc DEPS ddim place memory device_context framework_proto)
+ cc_library(tensor SRCS tensor.cc tensor_util.cc DEPS place memory device_context data_type)
endif()
cc_test(tensor_test SRCS tensor_test.cc DEPS tensor)
diff --git a/paddle/fluid/framework/data_type.cc b/paddle/fluid/framework/data_type.cc
new file mode 100644
index 0000000000..b60c618658
--- /dev/null
+++ b/paddle/fluid/framework/data_type.cc
@@ -0,0 +1,82 @@
+// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+// http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include "paddle/fluid/framework/data_type.h"
+
+namespace paddle {
+namespace framework {
+
+struct DataTypeMap {
+ std::unordered_map<std::type_index, proto::VarType::Type> cpp_to_proto_;
+ std::unordered_map<proto::VarType::Type, std::type_index> proto_to_cpp_;
+ std::unordered_map<proto::VarType::Type, std::string> proto_to_str_;
+};
+
+static DataTypeMap g_data_type_map_;
+
+template <typename T>
+static inline void RegisterType(proto::VarType::Type proto_type,
+ const std::string &name) {
+ g_data_type_map_.proto_to_cpp_.emplace(proto_type, typeid(T));
+ g_data_type_map_.cpp_to_proto_.emplace(typeid(T), proto_type);
+ g_data_type_map_.proto_to_str_.emplace(proto_type, name);
+}
+
+static int RegisterAllTypes() {
+#define RegType(cc_type, proto_type) RegisterType<cc_type>(proto_type, #cc_type)
+
+ RegType(platform::float16, proto::VarType::FP16);
+ RegType(float, proto::VarType::FP32);
+ RegType(double, proto::VarType::FP64);
+ RegType(int, proto::VarType::INT32);
+ RegType(int64_t, proto::VarType::INT64);
+ RegType(bool, proto::VarType::BOOL);
+
+#undef RegType
+ return 0;
+}
+
+static std::once_flag register_once_flag_;
+
+proto::VarType::Type ToDataType(std::type_index type) {
+ std::call_once(register_once_flag_, RegisterAllTypes);
+ auto it = g_data_type_map_.cpp_to_proto_.find(type);
+ if (it != g_data_type_map_.cpp_to_proto_.end()) {
+ return it->second;
+ }
+ PADDLE_THROW("Not support %s as tensor type", type.name());
+}
+
+std::type_index ToTypeIndex(proto::VarType::Type type) {
+ std::call_once(register_once_flag_, RegisterAllTypes);
+ auto it = g_data_type_map_.proto_to_cpp_.find(type);
+ if (it != g_data_type_map_.proto_to_cpp_.end()) {
+ return it->second;
+ }
+ PADDLE_THROW("Not support proto::VarType::Type(%d) as tensor type",
+ static_cast<int>(type));
+}
+
+std::string DataTypeToString(const proto::VarType::Type type) {
+ std::call_once(register_once_flag_, RegisterAllTypes);
+ auto it = g_data_type_map_.proto_to_str_.find(type);
+ if (it != g_data_type_map_.proto_to_str_.end()) {
+ return it->second;
+ }
+ PADDLE_THROW("Not support proto::VarType::Type(%d) as tensor type",
+ static_cast<int>(type));
+}
+
+} // namespace framework
+} // namespace paddle
diff --git a/paddle/fluid/framework/data_type.h b/paddle/fluid/framework/data_type.h
index 2a528eb3aa..06cc5940b7 100644
--- a/paddle/fluid/framework/data_type.h
+++ b/paddle/fluid/framework/data_type.h
@@ -22,47 +22,8 @@ limitations under the License. */
namespace paddle {
namespace framework {
-inline proto::VarType::Type ToDataType(std::type_index type) {
- if (typeid(platform::float16).hash_code() == type.hash_code()) {
- return proto::VarType::FP16;
- } else if (typeid(const float).hash_code() == type.hash_code()) {
- // CPPLint complains Using C-style cast. Use static_cast<float>() instead
- // One fix to this is to replace float with const float because
- // typeid(T) == typeid(const T)
- // http://en.cppreference.com/w/cpp/language/typeid
- return proto::VarType::FP32;
- } else if (typeid(const double).hash_code() == type.hash_code()) {
- return proto::VarType::FP64;
- } else if (typeid(const int).hash_code() == type.hash_code()) {
- return proto::VarType::INT32;
- } else if (typeid(const int64_t).hash_code() == type.hash_code()) {
- return proto::VarType::INT64;
- } else if (typeid(const bool).hash_code() == type.hash_code()) {
- return proto::VarType::BOOL;
- } else {
- PADDLE_THROW("Not supported");
- }
-}
-
-inline std::type_index ToTypeIndex(proto::VarType::Type type) {
- switch (type) {
- case proto::VarType::FP16:
- return typeid(platform::float16);
- case proto::VarType::FP32:
- return typeid(float);
- case proto::VarType::FP64:
- return typeid(double);
- case proto::VarType::INT32:
- return typeid(int);
- case proto::VarType::INT64:
- return typeid(int64_t);
- case proto::VarType::BOOL:
- return typeid(bool);
- default:
- PADDLE_THROW("Not support type %d", type);
- }
-}
-
+extern proto::VarType::Type ToDataType(std::type_index type);
+extern std::type_index ToTypeIndex(proto::VarType::Type type);
template <typename Visitor>
inline void VisitDataType(proto::VarType::Type type, Visitor visitor) {
switch (type) {
@@ -89,32 +50,11 @@ inline void VisitDataType(proto::VarType::Type type, Visitor visitor) {
}
}
-inline std::string DataTypeToString(const proto::VarType::Type type) {
- switch (type) {
- case proto::VarType::FP16:
- return "float16";
- case proto::VarType::FP32:
- return "float32";
- case proto::VarType::FP64:
- return "float64";
- case proto::VarType::INT16:
- return "int16";
- case proto::VarType::INT32:
- return "int32";
- case proto::VarType::INT64:
- return "int64";
- case proto::VarType::BOOL:
- return "bool";
- default:
- PADDLE_THROW("Not support type %d", type);
- }
-}
-
+extern std::string DataTypeToString(const proto::VarType::Type type);
inline std::ostream& operator<<(std::ostream& out,
const proto::VarType::Type& type) {
out << DataTypeToString(type);
return out;
}
-
} // namespace framework
} // namespace paddle
From c4d6daac58f89c234e8a250c4e1d2c080d83972b Mon Sep 17 00:00:00 2001
From: yuyang18 <reyoung@126.com>
Date: Fri, 11 May 2018 12:28:25 +0800
Subject: [PATCH 067/195] Polish SizeOfType
---
paddle/fluid/framework/data_type.cc | 12 ++++++++
paddle/fluid/framework/data_type.h | 3 ++
paddle/fluid/framework/tensor_impl.h | 44 ++--------------------------
3 files changed, 17 insertions(+), 42 deletions(-)
diff --git a/paddle/fluid/framework/data_type.cc b/paddle/fluid/framework/data_type.cc
index b60c618658..f322584900 100644
--- a/paddle/fluid/framework/data_type.cc
+++ b/paddle/fluid/framework/data_type.cc
@@ -21,6 +21,7 @@ struct DataTypeMap {
std::unordered_map<std::type_index, proto::VarType::Type> cpp_to_proto_;
std::unordered_map<proto::VarType::Type, std::type_index> proto_to_cpp_;
std::unordered_map<proto::VarType::Type, std::string> proto_to_str_;
+ std::unordered_map<std::type_index, size_t> cpp_to_size_;
};
static DataTypeMap g_data_type_map_;
@@ -31,11 +32,13 @@ static inline void RegisterType(proto::VarType::Type proto_type,
g_data_type_map_.proto_to_cpp_.emplace(proto_type, typeid(T));
g_data_type_map_.cpp_to_proto_.emplace(typeid(T), proto_type);
g_data_type_map_.proto_to_str_.emplace(proto_type, name);
+ g_data_type_map_.cpp_to_size_.emplace(typeid(T), sizeof(T));
}
static int RegisterAllTypes() {
#define RegType(cc_type, proto_type) RegisterType<cc_type>(proto_type, #cc_type)
+ // NOTE: Add your customize type here.
RegType(platform::float16, proto::VarType::FP16);
RegType(float, proto::VarType::FP32);
RegType(double, proto::VarType::FP64);
@@ -78,5 +81,14 @@ std::string DataTypeToString(const proto::VarType::Type type) {
static_cast<int>(type));
}
+size_t SizeOfType(std::type_index type) {
+ std::call_once(register_once_flag_, RegisterAllTypes);
+ auto it = g_data_type_map_.cpp_to_size_.find(type);
+ if (it != g_data_type_map_.cpp_to_size_.end()) {
+ return it->second;
+ }
+ PADDLE_THROW("Not support %s as tensor type", type.name());
+}
+
} // namespace framework
} // namespace paddle
diff --git a/paddle/fluid/framework/data_type.h b/paddle/fluid/framework/data_type.h
index 06cc5940b7..4b9f572ec5 100644
--- a/paddle/fluid/framework/data_type.h
+++ b/paddle/fluid/framework/data_type.h
@@ -17,6 +17,7 @@ limitations under the License. */
#include <typeindex>
#include "paddle/fluid/framework/framework.pb.h"
#include "paddle/fluid/platform/enforce.h"
+
#include "paddle/fluid/platform/float16.h"
namespace paddle {
@@ -24,6 +25,7 @@ namespace framework {
extern proto::VarType::Type ToDataType(std::type_index type);
extern std::type_index ToTypeIndex(proto::VarType::Type type);
+
template <typename Visitor>
inline void VisitDataType(proto::VarType::Type type, Visitor visitor) {
switch (type) {
@@ -51,6 +53,7 @@ inline void VisitDataType(proto::VarType::Type type, Visitor visitor) {
}
extern std::string DataTypeToString(const proto::VarType::Type type);
+extern size_t SizeOfType(std::type_index type);
inline std::ostream& operator<<(std::ostream& out,
const proto::VarType::Type& type) {
out << DataTypeToString(type);
diff --git a/paddle/fluid/framework/tensor_impl.h b/paddle/fluid/framework/tensor_impl.h
index f49d1a47a3..0a1db7758b 100644
--- a/paddle/fluid/framework/tensor_impl.h
+++ b/paddle/fluid/framework/tensor_impl.h
@@ -13,54 +13,14 @@ See the License for the specific language governing permissions and
limitations under the License. */
#pragma once
+#include "paddle/fluid/framework/data_type.h"
#include "paddle/fluid/memory/memcpy.h"
#include "paddle/fluid/platform/enforce.h"
#include "paddle/fluid/platform/float16.h"
namespace paddle {
namespace framework {
-
-template <typename... T>
-struct SizeOfTypeFunctor;
-
-template <typename T>
-struct SizeOfTypeFunctor<T> {
- size_t operator()(std::type_index type) const {
- if (typeid(T).hash_code() == type.hash_code()) {
- return sizeof(T);
- } else {
- return 0UL;
- }
- }
-};
-
-template <>
-struct SizeOfTypeFunctor<> {
- size_t operator()(std::type_index type) const { return 0UL; }
-};
-
-template <typename HEAD, typename... TAIL>
-struct SizeOfTypeFunctor<HEAD, TAIL...> {
- size_t operator()(std::type_index type) const {
- SizeOfTypeFunctor<HEAD> head;
- size_t head_size = head(type);
- if (head_size != 0) {
- return head_size;
- }
- SizeOfTypeFunctor<TAIL...> tail;
- return tail(type);
- }
-};
-
-static inline size_t SizeOfType(std::type_index type) {
- SizeOfTypeFunctor<int, float, double, int16_t, int64_t, bool, size_t,
- platform::float16>
- functor;
- size_t size = functor(type);
- PADDLE_ENFORCE(size != 0UL, "Cannot get size of type %s", type.name());
- return size;
-}
-
+extern size_t SizeOfType(std::type_index type);
inline void Tensor::check_memory_size() const {
PADDLE_ENFORCE_NOT_NULL(
holder_, "Tensor holds no memory. Call Tensor::mutable_data first.");
From 97cb5479ae0d16e28b3e3de3854e6390bc76b5ed Mon Sep 17 00:00:00 2001
From: chengduoZH <zhaochengduo@163.com>
Date: Wed, 9 May 2018 23:57:40 +0800
Subject: [PATCH 068/195] change PE strategy
---
.../details/multi_devices_graph_builder.cc | 73 +++++++++++--
.../details/multi_devices_graph_builder.h | 11 +-
paddle/fluid/framework/parallel_executor.cc | 11 +-
paddle/fluid/framework/parallel_executor.h | 3 +-
paddle/fluid/pybind/pybind.cc | 6 +-
python/paddle/fluid/parallel_executor.py | 9 +-
.../tests/unittests/test_parallel_executor.py | 100 +++++++++++++-----
7 files changed, 168 insertions(+), 45 deletions(-)
diff --git a/paddle/fluid/framework/details/multi_devices_graph_builder.cc b/paddle/fluid/framework/details/multi_devices_graph_builder.cc
index 21197d587b..4755559f8d 100644
--- a/paddle/fluid/framework/details/multi_devices_graph_builder.cc
+++ b/paddle/fluid/framework/details/multi_devices_graph_builder.cc
@@ -37,20 +37,26 @@ MultiDevSSAGraphBuilder::MultiDevSSAGraphBuilder(
const std::string &loss_var_name,
const std::unordered_set<std::string> ¶ms,
const std::vector<Scope *> &local_scopes,
- platform::NCCLContextMap *nccl_ctxs, bool use_default_grad_scale)
+ platform::NCCLContextMap *nccl_ctxs, bool use_default_grad_scale,
+ bool balance_parameter_opt_between_cards)
: loss_var_name_(loss_var_name),
places_(places),
local_scopes_(local_scopes),
- nccl_ctxs_(nccl_ctxs) {
+ nccl_ctxs_(nccl_ctxs),
+ balance_parameter_opt_between_cards_(
+ balance_parameter_opt_between_cards) {
#else
MultiDevSSAGraphBuilder::MultiDevSSAGraphBuilder(
const std::vector<platform::Place> &places,
const std::string &loss_var_name,
const std::unordered_set<std::string> ¶ms,
- const std::vector<Scope *> &local_scopes, bool use_default_grad_scale)
+ const std::vector<Scope *> &local_scopes, bool use_default_grad_scale,
+ bool balance_parameter_opt_between_cards)
: loss_var_name_(loss_var_name),
places_(places),
- local_scopes_(local_scopes) {
+ local_scopes_(local_scopes),
+ balance_parameter_opt_between_cards_(
+ balance_parameter_opt_between_cards) {
#endif
for (auto &p : params) {
grad_names_.insert(GradVarName(p));
@@ -124,6 +130,12 @@ std::unique_ptr<SSAGraph> MultiDevSSAGraphBuilder::Build(
// Find "send" op first for split is in front of send.
OpDesc *send_op = GetSendOpDesc(program);
+ size_t cur_device_id = 0;
+ std::vector<std::unordered_set<std::string>> var_name_on_devices;
+ std::vector<std::unordered_set<std::string>> bcast_var_name_set;
+ var_name_on_devices.resize(places_.size());
+ bcast_var_name_set.resize(places_.size());
+
bool is_forwarding = true;
for (auto *op : program.Block(0).AllOps()) {
if (op->Type() == "send") {
@@ -139,17 +151,33 @@ std::unique_ptr<SSAGraph> MultiDevSSAGraphBuilder::Build(
}
is_forwarding = false;
} else {
- CreateComputationalOps(&result, *op, places_.size());
+ int op_dev_id = GetOpDeviceID(var_name_on_devices, *op);
+ if (op_dev_id == -1) { // var on all device
+ CreateComputationalOps(&result, *op, places_.size());
+ } else {
+ CreateComputationalOp(&result, *op, op_dev_id);
+ for (auto &var_name : op->OutputArgumentNames()) {
+ var_name_on_devices[op_dev_id].emplace(var_name);
+ }
+ }
if (!is_forwarding && places_.size() > 1) {
// Currently, we assume that once gradient is generated, it can be
// broadcast, and each gradient is only broadcast once.
for (auto &og : op->OutputArgumentNames()) {
if (IsParameterGradientOnce(og, &og_has_been_broadcast)) {
- if (IsSparseGradient(var_types, og)) {
- CreateReduceOp(&result, og, 0);
- CreateBroadcastOp(&result, og, 0);
+ if (balance_parameter_opt_between_cards_) {
+ CreateReduceOp(&result, og, cur_device_id);
+ var_name_on_devices[cur_device_id].emplace(og);
+ bcast_var_name_set[cur_device_id].emplace(
+ og.substr(0, og.size() - strlen(kGradVarSuffix)));
+ cur_device_id = (cur_device_id + 1) % places_.size();
} else {
- InsertNCCLAllReduceOp(&result, og);
+ if (IsSparseGradient(var_types, og)) {
+ CreateReduceOp(&result, og, 0);
+ CreateBroadcastOp(&result, og, 0);
+ } else {
+ InsertNCCLAllReduceOp(&result, og);
+ }
}
}
}
@@ -157,6 +185,13 @@ std::unique_ptr<SSAGraph> MultiDevSSAGraphBuilder::Build(
}
}
+ // Insert BCast Ops
+ for (size_t dev_id = 0; dev_id < bcast_var_name_set.size(); ++dev_id) {
+ auto &to_bcast_set = bcast_var_name_set[dev_id];
+ for (auto &bcast_name : to_bcast_set) {
+ CreateBroadcastOp(&result, bcast_name, dev_id);
+ }
+ }
/*
Dependency graph has been constructed. However, there are still data
harzaeds need to be handled.
@@ -265,6 +300,26 @@ bool MultiDevSSAGraphBuilder::IsParameterGradientOnce(
return is_pg_once;
}
+int MultiDevSSAGraphBuilder::GetOpDeviceID(
+ const std::vector<std::unordered_set<std::string>> &var_name_on_devices,
+ const OpDesc &op) const {
+ if (!balance_parameter_opt_between_cards_) {
+ return -1;
+ }
+
+ int var_dev_id = -1;
+ for (auto &var_name : op.InputArgumentNames()) {
+ if (var_dev_id != -1) break;
+ for (size_t i = 0; i < var_name_on_devices.size(); ++i) {
+ if (var_name_on_devices[i].count(var_name)) {
+ var_dev_id = static_cast<int>(i);
+ break;
+ }
+ }
+ }
+ return var_dev_id;
+}
+
void MultiDevSSAGraphBuilder::CreateScaleLossGradOp(SSAGraph *result) const {
for (size_t i = 0; i < places_.size(); ++i) {
// Insert ScaleCost OpHandle
diff --git a/paddle/fluid/framework/details/multi_devices_graph_builder.h b/paddle/fluid/framework/details/multi_devices_graph_builder.h
index 674e2779a1..3a3e9e3b85 100644
--- a/paddle/fluid/framework/details/multi_devices_graph_builder.h
+++ b/paddle/fluid/framework/details/multi_devices_graph_builder.h
@@ -36,13 +36,15 @@ class MultiDevSSAGraphBuilder : public SSAGraphBuilder {
const std::unordered_set<std::string> ¶ms,
const std::vector<Scope *> &local_scopes,
platform::NCCLContextMap *nccl_ctxs,
- bool use_default_grad_scale);
+ bool use_default_grad_scale,
+ bool balance_parameter_opt_between_cards);
#else
MultiDevSSAGraphBuilder(const std::vector<platform::Place> &places,
const std::string &loss_var_name,
const std::unordered_set<std::string> ¶ms,
const std::vector<Scope *> &local_scopes,
- bool use_default_grad_scale);
+ bool use_default_grad_scale,
+ bool balance_parameter_opt_between_cards);
#endif
std::unique_ptr<SSAGraph> Build(const ProgramDesc &program) const override;
@@ -60,6 +62,7 @@ class MultiDevSSAGraphBuilder : public SSAGraphBuilder {
#ifdef PADDLE_WITH_CUDA
platform::NCCLContextMap *nccl_ctxs_;
#endif
+ bool balance_parameter_opt_between_cards_;
bool use_default_grad_scale_;
bool IsScaleLossOp(const OpDesc &op) const;
@@ -84,6 +87,10 @@ class MultiDevSSAGraphBuilder : public SSAGraphBuilder {
const std::string &og,
std::unordered_set<std::string> *og_has_been_broadcast) const;
+ int GetOpDeviceID(
+ const std::vector<std::unordered_set<std::string>> &var_name_on_devices,
+ const OpDesc &op) const;
+
void InsertNCCLAllReduceOp(SSAGraph *result, const std::string &og) const;
void CreateBroadcastOp(SSAGraph *result, const std::string &p_name,
diff --git a/paddle/fluid/framework/parallel_executor.cc b/paddle/fluid/framework/parallel_executor.cc
index 9eea8d1c18..20ef7e09f6 100644
--- a/paddle/fluid/framework/parallel_executor.cc
+++ b/paddle/fluid/framework/parallel_executor.cc
@@ -58,7 +58,7 @@ ParallelExecutor::ParallelExecutor(
const std::unordered_set<std::string> &bcast_vars,
const ProgramDesc &main_program, const std::string &loss_var_name,
Scope *scope, const std::vector<Scope *> &local_scopes, bool allow_op_delay,
- bool use_default_grad_scale)
+ bool use_default_grad_scale, bool balance_parameter_opt_between_cards)
: member_(new ParallelExecutorPrivate(places)) {
member_->global_scope_ = scope;
@@ -93,11 +93,12 @@ ParallelExecutor::ParallelExecutor(
#ifdef PADDLE_WITH_CUDA
details::MultiDevSSAGraphBuilder builder(
member_->places_, loss_var_name, params, member_->local_scopes_,
- member_->nccl_ctxs_.get(), use_default_grad_scale);
+ member_->nccl_ctxs_.get(), use_default_grad_scale,
+ balance_parameter_opt_between_cards);
#else
- details::MultiDevSSAGraphBuilder builder(member_->places_, loss_var_name,
- params, member_->local_scopes_,
- use_default_grad_scale);
+ details::MultiDevSSAGraphBuilder builder(
+ member_->places_, loss_var_name, params, member_->local_scopes_,
+ use_default_grad_scale, balance_parameter_opt_between_cards);
#endif
auto graph = builder.Build(main_program);
diff --git a/paddle/fluid/framework/parallel_executor.h b/paddle/fluid/framework/parallel_executor.h
index ecd107d81f..b251fc9141 100644
--- a/paddle/fluid/framework/parallel_executor.h
+++ b/paddle/fluid/framework/parallel_executor.h
@@ -40,7 +40,8 @@ class ParallelExecutor {
const ProgramDesc& main_program,
const std::string& loss_var_name, Scope* scope,
const std::vector<Scope*>& local_scopes,
- bool allow_op_delay, bool use_default_grad_scale);
+ bool allow_op_delay, bool use_default_grad_scale,
+ bool balance_parameter_opt_between_cards);
~ParallelExecutor();
diff --git a/paddle/fluid/pybind/pybind.cc b/paddle/fluid/pybind/pybind.cc
index c925686f83..3e2eed31b4 100644
--- a/paddle/fluid/pybind/pybind.cc
+++ b/paddle/fluid/pybind/pybind.cc
@@ -502,11 +502,13 @@ All parameter, weight, gradient are variables in Paddle.
const std::unordered_set<std::string> &bcast_vars,
const ProgramDesc &main_program, const std::string &loss_var_name,
Scope *scope, std::vector<Scope *> &local_scopes,
- bool allow_op_delay, bool use_default_grad_scale) {
+ bool allow_op_delay, bool use_default_grad_scale,
+ bool balance_parameter_opt_between_cards) {
new (&self) ParallelExecutor(
num_threads, use_event, places, params, bcast_vars,
main_program, loss_var_name, scope, local_scopes,
- allow_op_delay, use_default_grad_scale);
+ allow_op_delay, use_default_grad_scale,
+ balance_parameter_opt_between_cards);
})
.def("bcast_params", &ParallelExecutor::BCastParamsToGPUs)
// NOTE: even we return a vec<Scope*>* to Python use reference policy.
diff --git a/python/paddle/fluid/parallel_executor.py b/python/paddle/fluid/parallel_executor.py
index 6b80b007e9..5b43f860e7 100644
--- a/python/paddle/fluid/parallel_executor.py
+++ b/python/paddle/fluid/parallel_executor.py
@@ -30,7 +30,8 @@ class ParallelExecutor(object):
num_threads=None,
allow_op_delay=False,
share_vars_from=None,
- use_default_grad_scale=True):
+ use_default_grad_scale=True,
+ balance_parameter_opt_between_cards=False):
"""
ParallelExecutor can run program in parallel.
@@ -51,6 +52,9 @@ class ParallelExecutor(object):
gradients of each device and scaled gradients would be
aggregated. Otherwise, a customized scale value should be fed
to the network.
+ balance_parameter_opt_between_cards(bool, default True): Whether
+ updating different gradients on different cards. Currently, it
+ is not recommended.
Returns:
A ParallelExecutor object.
@@ -129,7 +133,8 @@ class ParallelExecutor(object):
scope,
local_scopes,
allow_op_delay,
- use_default_grad_scale)
+ use_default_grad_scale,
+ balance_parameter_opt_between_cards)
self.scope = scope
diff --git a/python/paddle/fluid/tests/unittests/test_parallel_executor.py b/python/paddle/fluid/tests/unittests/test_parallel_executor.py
index 4eb25a6e00..c39192eb0f 100644
--- a/python/paddle/fluid/tests/unittests/test_parallel_executor.py
+++ b/python/paddle/fluid/tests/unittests/test_parallel_executor.py
@@ -205,7 +205,8 @@ class TestParallelExecutorBase(unittest.TestCase):
allow_op_delay=False,
feed_dict=None,
seed=None,
- use_parallel_executor=True):
+ use_parallel_executor=True,
+ balance_parameter_opt_between_cards=False):
def run_executor(exe, feed, fetch_list, program=None):
if isinstance(exe, fluid.ParallelExecutor):
res = exe.run(fetch_list=fetch_list, feed=feed)
@@ -234,7 +235,11 @@ class TestParallelExecutorBase(unittest.TestCase):
if use_parallel_executor:
exe = fluid.ParallelExecutor(
- True, loss_name=loss.name, allow_op_delay=allow_op_delay)
+ True,
+ loss_name=loss.name,
+ allow_op_delay=allow_op_delay,
+ balance_parameter_opt_between_cards=balance_parameter_opt_between_cards
+ )
else:
exe = fluid.Executor(place=place)
@@ -280,20 +285,27 @@ class TestMNIST(TestParallelExecutorBase):
fluid.recordio_writer.convert_reader_to_recordio_file(
'./mnist.recordio', reader, feeder)
- def check_simple_fc_convergence(self):
+ def check_simple_fc_convergence(self, balance_parameter_opt_between_cards):
self.check_network_convergence(simple_fc_net)
self.check_network_convergence(simple_fc_net, allow_op_delay=True)
img = np.zeros(shape=[32, 784], dtype='float32')
label = np.ones(shape=[32, 1], dtype='int64')
self.check_network_convergence(
- simple_fc_net, feed_dict={"image": img,
- "label": label})
+ simple_fc_net,
+ feed_dict={"image": img,
+ "label": label},
+ balance_parameter_opt_between_cards=balance_parameter_opt_between_cards
+ )
def test_simple_fc(self):
- self.check_simple_fc_convergence()
+ self.check_simple_fc_convergence(False)
+
+ def test_simple_fc_with_new_strategy(self):
+ self.check_simple_fc_convergence(True)
- def check_simple_fc_parallel_accuracy(self):
+ def check_simple_fc_parallel_accuracy(self,
+ balance_parameter_opt_between_cards):
img = np.zeros(shape=[32, 784], dtype='float32')
label = np.ones(shape=[32, 1], dtype='int64')
single_first_loss, single_last_loss = self.check_network_convergence(
@@ -307,7 +319,9 @@ class TestMNIST(TestParallelExecutorBase):
seed=1000,
feed_dict={"image": img,
"label": label},
- use_parallel_executor=True)
+ use_parallel_executor=True,
+ balance_parameter_opt_between_cards=balance_parameter_opt_between_cards
+ )
for p_f in parallel_first_loss:
self.assertAlmostEquals(p_f, single_first_loss[0], delta=1e-6)
@@ -315,18 +329,28 @@ class TestMNIST(TestParallelExecutorBase):
self.assertAlmostEquals(p_l, single_last_loss[0], delta=1e-6)
def test_simple_fc_parallel_accuracy(self):
- self.check_simple_fc_parallel_accuracy()
+ self.check_simple_fc_parallel_accuracy(False)
- def check_batchnorm_fc_convergence(self):
+ def test_simple_fc_parallel_accuracy_with_new_strategy(self):
+ self.check_simple_fc_parallel_accuracy(True)
+
+ def check_batchnorm_fc_convergence(self,
+ balance_parameter_opt_between_cards):
self.check_network_convergence(fc_with_batchnorm)
img = np.zeros(shape=[32, 784], dtype='float32')
label = np.ones(shape=[32, 1], dtype='int64')
self.check_network_convergence(
- fc_with_batchnorm, feed_dict={"image": img,
- "label": label})
+ fc_with_batchnorm,
+ feed_dict={"image": img,
+ "label": label},
+ balance_parameter_opt_between_cards=balance_parameter_opt_between_cards
+ )
def test_batchnorm_fc(self):
- self.check_batchnorm_fc_convergence()
+ self.check_batchnorm_fc_convergence(False)
+
+ def test_batchnorm_fc_with_new_strategy(self):
+ self.check_batchnorm_fc_convergence(True)
class TestResnet(TestParallelExecutorBase):
@@ -348,17 +372,22 @@ class TestResnet(TestParallelExecutorBase):
# fluid.recordio_writer.convert_reader_to_recordio_file(
# "./flowers.recordio", reader, feeder, compressor=fluid.core.RecordIOWriter.Compressor.NoCompress)
- def check_resnet_convergence(self):
+ def check_resnet_convergence(self, balance_parameter_opt_between_cards):
import functools
batch_size = 2
self.check_network_convergence(
functools.partial(
SE_ResNeXt50Small, batch_size=batch_size),
iter=20,
- batch_size=batch_size)
+ batch_size=batch_size,
+ balance_parameter_opt_between_cards=balance_parameter_opt_between_cards
+ )
def test_resnet(self):
- self.check_resnet_convergence()
+ self.check_resnet_convergence(False)
+
+ def test_resnet_with_new_strategy(self):
+ self.check_resnet_convergence(True)
class ModelHyperParams(object):
@@ -519,7 +548,7 @@ class TestTransformer(TestParallelExecutorBase):
class ParallelExecutorTestingDuringTraining(unittest.TestCase):
- def check_network_convergence(self):
+ def check_network_convergence(self, balance_parameter_opt_between_cards):
main = fluid.Program()
startup = fluid.Program()
with fluid.program_guard(main, startup):
@@ -539,12 +568,18 @@ class ParallelExecutorTestingDuringTraining(unittest.TestCase):
feed_dict = {'image': image, 'label': label}
train_exe = fluid.ParallelExecutor(
- use_cuda=True, loss_name=loss.name, main_program=main)
+ use_cuda=True,
+ loss_name=loss.name,
+ main_program=main,
+ balance_parameter_opt_between_cards=balance_parameter_opt_between_cards
+ )
test_exe = fluid.ParallelExecutor(
use_cuda=True,
main_program=test_program,
- share_vars_from=train_exe)
+ share_vars_from=train_exe,
+ balance_parameter_opt_between_cards=balance_parameter_opt_between_cards
+ )
for i in xrange(5):
test_loss, = test_exe.run([loss.name], feed=feed_dict)
@@ -558,8 +593,11 @@ class ParallelExecutorTestingDuringTraining(unittest.TestCase):
"Train loss: " + str(train_loss) + "\n Test loss:" +
str(test_loss))
- def test_parallel(self):
- self.check_network_convergence()
+ def test_parallel_testing(self):
+ self.check_network_convergence(False)
+
+ def test_parallel_testing_with_new_strategy(self):
+ self.check_network_convergence(True)
import paddle.dataset.conll05 as conll05
@@ -579,7 +617,7 @@ embedding_name = 'emb'
def db_lstm(word, predicate, ctx_n2, ctx_n1, ctx_0, ctx_p1, ctx_p2, mark,
- is_sparse, **ignored):
+ is_sparse, balance_parameter_opt_between_cards, **ignored):
# 8 features
predicate_embedding = fluid.layers.embedding(
input=predicate,
@@ -648,7 +686,9 @@ def db_lstm(word, predicate, ctx_n2, ctx_n1, ctx_0, ctx_p1, ctx_p2, mark,
class TestCRFModel(unittest.TestCase):
- def check_network_convergence(self, is_sparse):
+ def check_network_convergence(self,
+ is_sparse,
+ balance_parameter_opt_between_cards=False):
main = fluid.Program()
startup = fluid.Program()
with fluid.program_guard(main, startup):
@@ -696,7 +736,11 @@ class TestCRFModel(unittest.TestCase):
exe = fluid.Executor(place)
exe.run(startup)
- pe = fluid.ParallelExecutor(use_cuda=True, loss_name=avg_cost.name)
+ pe = fluid.ParallelExecutor(
+ use_cuda=True,
+ loss_name=avg_cost.name,
+ balance_parameter_opt_between_cards=balance_parameter_opt_between_cards
+ )
feeder = fluid.DataFeeder(
feed_list=[
@@ -718,6 +762,14 @@ class TestCRFModel(unittest.TestCase):
def test_update_dense_parameter(self):
self.check_network_convergence(is_sparse=False)
+ def test_update_sparse_parameter_with_new_strategy(self):
+ self.check_network_convergence(
+ is_sparse=False, balance_parameter_opt_between_cards=True)
+
+ def test_update_dense_parameter_with_new_strategy(self):
+ self.check_network_convergence(
+ is_sparse=False, balance_parameter_opt_between_cards=True)
+
# test fetch all the variables of global_block
From 9f705a4bb937aade91126595a0fb0e4b994d9793 Mon Sep 17 00:00:00 2001
From: yuyang18 <reyoung@126.com>
Date: Fri, 11 May 2018 13:20:41 +0800
Subject: [PATCH 069/195] Use int instead of VarType as unordered_map key
---
paddle/fluid/framework/data_type.cc | 13 +++++++------
1 file changed, 7 insertions(+), 6 deletions(-)
diff --git a/paddle/fluid/framework/data_type.cc b/paddle/fluid/framework/data_type.cc
index f322584900..9e5f255891 100644
--- a/paddle/fluid/framework/data_type.cc
+++ b/paddle/fluid/framework/data_type.cc
@@ -19,8 +19,8 @@ namespace framework {
struct DataTypeMap {
std::unordered_map<std::type_index, proto::VarType::Type> cpp_to_proto_;
- std::unordered_map<proto::VarType::Type, std::type_index> proto_to_cpp_;
- std::unordered_map<proto::VarType::Type, std::string> proto_to_str_;
+ std::unordered_map<int, std::type_index> proto_to_cpp_;
+ std::unordered_map<int, std::string> proto_to_str_;
std::unordered_map<std::type_index, size_t> cpp_to_size_;
};
@@ -29,9 +29,10 @@ static DataTypeMap g_data_type_map_;
template <typename T>
static inline void RegisterType(proto::VarType::Type proto_type,
const std::string &name) {
- g_data_type_map_.proto_to_cpp_.emplace(proto_type, typeid(T));
+ g_data_type_map_.proto_to_cpp_.emplace(static_cast<int>(proto_type),
+ typeid(T));
g_data_type_map_.cpp_to_proto_.emplace(typeid(T), proto_type);
- g_data_type_map_.proto_to_str_.emplace(proto_type, name);
+ g_data_type_map_.proto_to_str_.emplace(static_cast<int>(proto_type), name);
g_data_type_map_.cpp_to_size_.emplace(typeid(T), sizeof(T));
}
@@ -63,7 +64,7 @@ proto::VarType::Type ToDataType(std::type_index type) {
std::type_index ToTypeIndex(proto::VarType::Type type) {
std::call_once(register_once_flag_, RegisterAllTypes);
- auto it = g_data_type_map_.proto_to_cpp_.find(type);
+ auto it = g_data_type_map_.proto_to_cpp_.find(static_cast<int>(type));
if (it != g_data_type_map_.proto_to_cpp_.end()) {
return it->second;
}
@@ -73,7 +74,7 @@ std::type_index ToTypeIndex(proto::VarType::Type type) {
std::string DataTypeToString(const proto::VarType::Type type) {
std::call_once(register_once_flag_, RegisterAllTypes);
- auto it = g_data_type_map_.proto_to_str_.find(type);
+ auto it = g_data_type_map_.proto_to_str_.find(static_cast<int>(type));
if (it != g_data_type_map_.proto_to_str_.end()) {
return it->second;
}
From f60b9a4208b34ce42e0e2f5bbc94ee77c5cee90c Mon Sep 17 00:00:00 2001
From: Luo Tao <luotao02@baidu.com>
Date: Fri, 11 May 2018 15:14:38 +0800
Subject: [PATCH 070/195] fix unittest-error: test_network_with_dtype
---
.../paddle/fluid/tests/unittests/test_network_with_dtype.py | 4 +++-
1 file changed, 3 insertions(+), 1 deletion(-)
diff --git a/python/paddle/fluid/tests/unittests/test_network_with_dtype.py b/python/paddle/fluid/tests/unittests/test_network_with_dtype.py
index baafcdbb80..af487919a9 100644
--- a/python/paddle/fluid/tests/unittests/test_network_with_dtype.py
+++ b/python/paddle/fluid/tests/unittests/test_network_with_dtype.py
@@ -24,7 +24,7 @@ BATCH_SIZE = 20
class TestNetWithDtype(unittest.TestCase):
- def setUp(self):
+ def set_network(self):
self.dtype = "float64"
self.init_dtype()
self.x = fluid.layers.data(name='x', shape=[13], dtype=self.dtype)
@@ -55,12 +55,14 @@ class TestNetWithDtype(unittest.TestCase):
pass
def test_cpu(self):
+ self.set_network()
place = fluid.CPUPlace()
self.run_net_on_place(place)
def test_gpu(self):
if not core.is_compiled_with_cuda():
return
+ self.set_network()
place = fluid.CUDAPlace(0)
self.run_net_on_place(place)
From 7ec73d23517fab07a43571d253bd50b9343f7d9b Mon Sep 17 00:00:00 2001
From: weixing02 <wx_crome@163.com>
Date: Fri, 11 May 2018 15:44:49 +0800
Subject: [PATCH 071/195] Fix two deadlinks in paddle/README.md
---
README.md | 4 ++--
1 file changed, 2 insertions(+), 2 deletions(-)
diff --git a/README.md b/README.md
index a3b13fe79c..8d89c6b1ec 100644
--- a/README.md
+++ b/README.md
@@ -62,9 +62,9 @@ Please refer to our [release announcement](https://github.com/PaddlePaddle/Paddl
## Installation
It is recommended to check out the
-[Docker installation guide](http://www.paddlepaddle.org/docs/develop/documentation/en/getstarted/build_and_install/docker_install_en.html)
+[Docker installation guide](http://www.paddlepaddle.org/docs/develop/documentation/fluid/en/build_and_install/docker_install_en.html)
before looking into the
-[build from source guide](http://www.paddlepaddle.org/docs/develop/documentation/en/getstarted/build_and_install/build_from_source_en.html).
+[build from source guide](http://www.paddlepaddle.org/docs/develop/documentation/fluid/en/build_and_install/build_from_source_en.html).
## Documentation
From f5840d89258b4d2dd8e3da77db8645d58bbf0d4d Mon Sep 17 00:00:00 2001
From: typhoonzero <typhoonzero1986@gmail.com>
Date: Fri, 11 May 2018 19:54:35 +0800
Subject: [PATCH 072/195] follow comments
---
paddle/fluid/framework/parallel_executor.cc | 2 +-
paddle/fluid/operators/CMakeLists.txt | 2 +-
.../fluid/operators/detail/sendrecvop_utils.cc | 4 ++--
paddle/fluid/operators/gen_nccl_id_op.cc | 9 ++++++---
paddle/fluid/operators/test_send_nccl_id.cc | 6 +++---
paddle/fluid/platform/nccl_helper.h | 16 ++++++++--------
python/paddle/fluid/parallel_executor.py | 8 ++++----
7 files changed, 25 insertions(+), 22 deletions(-)
diff --git a/paddle/fluid/framework/parallel_executor.cc b/paddle/fluid/framework/parallel_executor.cc
index b080e516de..4d62edfef4 100644
--- a/paddle/fluid/framework/parallel_executor.cc
+++ b/paddle/fluid/framework/parallel_executor.cc
@@ -80,7 +80,7 @@ ParallelExecutor::ParallelExecutor(
// Bcast Parameters to all GPUs
#ifdef PADDLE_WITH_CUDA
- auto *nccl_id_var = scope->FindVar("NCCLID");
+ auto *nccl_id_var = scope->FindVar(NCCL_ID_VARNAME);
ncclUniqueId *nccl_id = nullptr;
if (nccl_id_var != nullptr) {
nccl_id = nccl_id_var->GetMutable<ncclUniqueId>();
diff --git a/paddle/fluid/operators/CMakeLists.txt b/paddle/fluid/operators/CMakeLists.txt
index 2b8df6c35f..48d0af1a5b 100644
--- a/paddle/fluid/operators/CMakeLists.txt
+++ b/paddle/fluid/operators/CMakeLists.txt
@@ -187,7 +187,7 @@ if(WITH_DISTRIBUTE)
if(WITH_GPU)
op_library(gen_nccl_id_op DEPS nccl_common)
else()
- set(DEPS_OPS ${DEPS_OPS} gen_nccl_id_op)
+ set(DEPS_OPS ${DEPS_OPS} gen_nccl_id_op)
endif()
set(DISTRIBUTE_DEPS sendrecvop_grpc grpc++_unsecure grpc_unsecure gpr cares zlib protobuf)
set(DISTRIBUTE_COMPILE_FLAGS "-Wno-non-virtual-dtor -Wno-error=non-virtual-dtor -Wno-error=delete-non-virtual-dtor")
diff --git a/paddle/fluid/operators/detail/sendrecvop_utils.cc b/paddle/fluid/operators/detail/sendrecvop_utils.cc
index 247130f571..f3ac149947 100644
--- a/paddle/fluid/operators/detail/sendrecvop_utils.cc
+++ b/paddle/fluid/operators/detail/sendrecvop_utils.cc
@@ -162,8 +162,8 @@ void SerializeToByteBuffer(const std::string& name, framework::Variable* var,
if (var->IsType<ncclUniqueId>()) {
e.WriteVarlengthBeginning(VarMsg::kSerializedFieldNumber,
NCCL_UNIQUE_ID_BYTES);
- ncclUniqueId* uid = var->GetMutable<ncclUniqueId>();
- e.WriteRawBytes(std::string(uid->internal, NCCL_UNIQUE_ID_BYTES));
+ ncclUniqueId& uid = var->Get<ncclUniqueId>();
+ e.WriteRawBytes(std::string(uid.internal, NCCL_UNIQUE_ID_BYTES));
// for serialize NCCL_ID
::grpc::Slice slices(e.size());
diff --git a/paddle/fluid/operators/gen_nccl_id_op.cc b/paddle/fluid/operators/gen_nccl_id_op.cc
index cfdeaee00b..1cddc998e4 100644
--- a/paddle/fluid/operators/gen_nccl_id_op.cc
+++ b/paddle/fluid/operators/gen_nccl_id_op.cc
@@ -52,17 +52,17 @@ class GenNCCLIdOp : public framework::OperatorBase {
private:
void GenerateAndSend(framework::Scope* scope,
const platform::DeviceContext& dev_ctx) const {
- auto var = scope->FindVar("NCCLID");
+ auto var = scope->FindVar(NCCL_ID_VARNAME);
PADDLE_ENFORCE_NOT_NULL(var);
auto id = var->GetMutable<ncclUniqueId>();
- platform::dynload::ncclGetUniqueId(id);
+ PADDLE_ENFORCE(platform::dynload::ncclGetUniqueId(id));
std::vector<std::string> endpoint_list =
Attr<std::vector<std::string>>("endpoint_list");
detail::RPCClient client;
for (auto& ep : endpoint_list) {
VLOG(3) << "sending nccl id to " << ep;
- client.AsyncSendVariable(ep, dev_ctx, *scope, "NCCLID");
+ client.AsyncSendVariable(ep, dev_ctx, *scope, NCCL_ID_VARNAME);
}
client.Wait();
VLOG(3) << "sending completed...";
@@ -71,6 +71,9 @@ class GenNCCLIdOp : public framework::OperatorBase {
void GetIdByServer(framework::Scope* scope,
const platform::DeviceContext& dev_ctx) const {
std::string endpoint = Attr<std::string>("endpoint");
+ // NOTE: Can not use unique_ptr here because the default
+ // deleter will call GRPC Server's base class's dtor and
+ // that will cause a wired crash.
rpc_service_ = new detail::AsyncGRPCServer(endpoint, true);
framework::ProgramDesc empty_program;
framework::Executor executor(dev_ctx.GetPlace());
diff --git a/paddle/fluid/operators/test_send_nccl_id.cc b/paddle/fluid/operators/test_send_nccl_id.cc
index 6781f85c4a..2c3c5ea0a0 100644
--- a/paddle/fluid/operators/test_send_nccl_id.cc
+++ b/paddle/fluid/operators/test_send_nccl_id.cc
@@ -39,7 +39,7 @@ std::unique_ptr<detail::AsyncGRPCServer> rpc_service;
void StartServer() {
f::Scope scope;
p::CPUPlace place;
- scope.Var("NCCLID");
+ scope.Var(NCCL_ID_VARNAME);
p::DeviceContextPool& pool = p::DeviceContextPool::Instance();
auto& dev_ctx = *pool.Get(p::CPUPlace());
@@ -71,7 +71,7 @@ TEST(SendNcclId, Normal) {
p::DeviceContextPool& pool = p::DeviceContextPool::Instance();
auto& dev_ctx = *pool.Get(p::CPUPlace());
- auto var = scope.Var("NCCLID");
+ auto var = scope.Var(NCCL_ID_VARNAME);
// var->SetType(f::proto::VarType_Type_RAW);
auto id = var->GetMutable<ncclUniqueId>();
p::dynload::ncclGetUniqueId(id);
@@ -80,7 +80,7 @@ TEST(SendNcclId, Normal) {
std::string ep = string::Sprintf("127.0.0.1:%d", port);
detail::RPCClient client;
- client.AsyncSendVariable(ep, dev_ctx, scope, "NCCLID");
+ client.AsyncSendVariable(ep, dev_ctx, scope, NCCL_ID_VARNAME);
client.Wait();
server_thread.join();
auto* ptr = rpc_service.release();
diff --git a/paddle/fluid/platform/nccl_helper.h b/paddle/fluid/platform/nccl_helper.h
index 094c47007e..408721be8b 100644
--- a/paddle/fluid/platform/nccl_helper.h
+++ b/paddle/fluid/platform/nccl_helper.h
@@ -21,6 +21,8 @@
#include "paddle/fluid/platform/dynload/nccl.h"
#include "paddle/fluid/platform/enforce.h"
+#define NCCL_ID_VARNAME "NCCLID"
+
namespace paddle {
namespace platform {
@@ -76,7 +78,7 @@ struct NCCLContextMap {
explicit NCCLContextMap(const std::vector<platform::Place> &places,
ncclUniqueId *nccl_id = nullptr,
- size_t node_count = 0, size_t trainer_id = 0) {
+ size_t num_trainers = 0, size_t trainer_id = 0) {
PADDLE_ENFORCE(!places.empty());
order_.reserve(places.size());
for (auto &p : places) {
@@ -94,16 +96,14 @@ struct NCCLContextMap {
std::unique_ptr<ncclComm_t[]> comms(new ncclComm_t[order_.size()]);
// if pass nccl_id here, can assume we are doing multi node training
if (nccl_id == nullptr) {
- {
- std::lock_guard<std::mutex> guard(NCCLGroupGuard::NCCLMutex());
- PADDLE_ENFORCE(platform::dynload::ncclCommInitAll(
- comms.get(), static_cast<int>(order_.size()), order_.data()));
- }
+ std::lock_guard<std::mutex> guard(NCCLGroupGuard::NCCLMutex());
+ PADDLE_ENFORCE(platform::dynload::ncclCommInitAll(
+ comms.get(), static_cast<int>(order_.size()), order_.data()));
} else {
- PADDLE_ENFORCE_GT(node_count, 0);
+ PADDLE_ENFORCE_GT(num_trainers, 0);
// TODO(wuyi): need to ensure each node have same number of GPUs
{
- int nranks = node_count * order_.size();
+ int nranks = num_trainers * order_.size();
NCCLGroupGuard gurad;
for (auto &gpu_id : order_) {
int rank = trainer_id * order_.size() + gpu_id;
diff --git a/python/paddle/fluid/parallel_executor.py b/python/paddle/fluid/parallel_executor.py
index bd92ac548d..4f6db7c2be 100644
--- a/python/paddle/fluid/parallel_executor.py
+++ b/python/paddle/fluid/parallel_executor.py
@@ -31,7 +31,7 @@ class ParallelExecutor(object):
allow_op_delay=False,
share_vars_from=None,
use_default_grad_scale=True,
- num_nodes=0,
+ num_trainers=0,
trainer_id=0):
"""
ParallelExecutor can run program in parallel.
@@ -53,10 +53,10 @@ class ParallelExecutor(object):
gradients of each device and scaled gradients would be
aggregated. Otherwise, a customized scale value should be fed
to the network.
- num_nodes(int, default 0): If greater than 0, NCCL will be
+ num_trainers(int, default 0): If greater than 0, NCCL will be
initialized with multpile rank of nodes, each node should have
same number of GPUs. Distributed training will be enabled then.
- trainer_id(int, default 0): Must use together with num_nodes.
+ trainer_id(int, default 0): Must use together with num_trainers.
trainer_id is the "rank" of current node starts from 0.
Returns:
@@ -137,7 +137,7 @@ class ParallelExecutor(object):
local_scopes,
allow_op_delay,
use_default_grad_scale,
- num_nodes,
+ num_trainers,
trainer_id)
self.scope = scope
From 7a7d27b33e26e5008b905cc105ff9667f6b0ec2a Mon Sep 17 00:00:00 2001
From: typhoonzero <typhoonzero1986@gmail.com>
Date: Fri, 11 May 2018 19:56:21 +0800
Subject: [PATCH 073/195] update op
---
paddle/fluid/operators/gen_nccl_id_op.cc | 3 +--
1 file changed, 1 insertion(+), 2 deletions(-)
diff --git a/paddle/fluid/operators/gen_nccl_id_op.cc b/paddle/fluid/operators/gen_nccl_id_op.cc
index 1cddc998e4..77cd4a460a 100644
--- a/paddle/fluid/operators/gen_nccl_id_op.cc
+++ b/paddle/fluid/operators/gen_nccl_id_op.cc
@@ -102,8 +102,7 @@ class GenNCCLIdOp : public framework::OperatorBase {
class GenNCCLIdOpMaker : public framework::OpProtoAndCheckerMaker {
public:
- GenNCCLIdOpMaker(OpProto* proto, OpAttrChecker* op_checker)
- : OpProtoAndCheckerMaker(proto, op_checker) {
+ void Make() override {
AddOutput("NCCLID", "Raw variable contains a NCCL UniqueId instaces.");
AddComment(R"DOC(
GenNCCLId operator
From 7bf00c3a93c4770cb06e8dd17e988e11f79cbf03 Mon Sep 17 00:00:00 2001
From: Jacek Czaja <jacek.czaja@intel.com>
Date: Tue, 8 May 2018 10:34:01 -0700
Subject: [PATCH 074/195] - First draft of reusing of softmax mkldnn primitives
- Added hash function inside of MKLDNN softmax op to be used as handle for primitives stroing in a
context
- Style fixes to softmax mkldnn op
- Fixes after review
- Coding style
- Fix to style
- style fixes
- style fix
- style fixes
- Fix to cody style check
- Rephrasing a comment
---
paddle/fluid/operators/softmax_mkldnn_op.cc | 73 +++++++++++++++------
1 file changed, 54 insertions(+), 19 deletions(-)
diff --git a/paddle/fluid/operators/softmax_mkldnn_op.cc b/paddle/fluid/operators/softmax_mkldnn_op.cc
index 71b541d98f..14b57b11fe 100644
--- a/paddle/fluid/operators/softmax_mkldnn_op.cc
+++ b/paddle/fluid/operators/softmax_mkldnn_op.cc
@@ -53,25 +53,60 @@ class SoftmaxMKLDNNKernel : public paddle::framework::OpKernel<T> {
"Softmax input and output dimensions should match");
// Same memory descriptor to be used for input and output
memory::dims softmax_tz = {src_tz[0], src_tz[1]};
- // Currently only supports NC data format
- // TODO(jczaja-intel): support more formats
- auto softmax_md =
- MKLDNNMemDesc({softmax_tz}, memory::f32, memory::format::nc);
- // Normalization is made after innermost dimension eg. C out of NC
- auto softmax_desc = softmax_forward::desc(prop_kind::forward_scoring,
- softmax_md, 1 /*dim: C*/);
- // create memory primitives
- auto softmax_src_memory =
- memory({softmax_md, mkldnn_engine},
- static_cast<void*>(const_cast<T*>(input_data)));
- auto softmax_dst_memory =
- memory({softmax_md, mkldnn_engine},
- static_cast<void*>(const_cast<T*>(output_data)));
- auto softmax_prim_desc =
- softmax_forward::primitive_desc(softmax_desc, mkldnn_engine);
- auto softmax = softmax_forward(softmax_prim_desc, softmax_src_memory,
- softmax_dst_memory);
- std::vector<primitive> pipeline{softmax};
+ // Generate keys for storing/retriving primitives for this operator
+ // TODO(jczaja): Each MKLDNN operator may have diffrent hashing function
+ auto gethash = [](memory::dims& operand_dims) {
+ return std::string(std::to_string(operand_dims[0]) + "-" +
+ std::to_string(operand_dims[1]));
+ };
+ const std::string key = gethash(softmax_tz);
+ const std::string key_softmax_p = key + "@softmax_p";
+ const std::string key_softmax_src_mem_p = key + "@softmax_src_mem_p";
+ const std::string key_softmax_dst_mem_p = key + "@softmax_dst_mem_p";
+
+ std::shared_ptr<void> softmax_p = dev_ctx.GetBlob(key_softmax_p);
+ if (softmax_p == nullptr) {
+ // Currently only NC data format is supported
+ auto softmax_md =
+ MKLDNNMemDesc({softmax_tz}, memory::f32, memory::format::nc);
+ // Normalization is made after innermost dimension eg. C out of NC
+ auto softmax_desc = softmax_forward::desc(prop_kind::forward_scoring,
+ softmax_md, 1 /*dim: C*/);
+ // create memory primitives
+ auto softmax_src_memory_p = std::make_shared<memory>(
+ memory::primitive_desc{softmax_md, mkldnn_engine},
+ static_cast<void*>(const_cast<T*>(input_data)));
+ dev_ctx.SetBlob(key_softmax_src_mem_p, softmax_src_memory_p);
+ auto softmax_dst_memory_p = std::make_shared<memory>(
+ memory::primitive_desc{softmax_md, mkldnn_engine},
+ static_cast<void*>(output_data));
+ dev_ctx.SetBlob(key_softmax_dst_mem_p, softmax_dst_memory_p);
+
+ auto softmax_forward_pd =
+ std::make_shared<softmax_forward::primitive_desc>(softmax_desc,
+ mkldnn_engine);
+ softmax_p = std::make_shared<softmax_forward>(
+ *(softmax_forward_pd.get()),
+ *(static_cast<memory*>(softmax_src_memory_p.get())),
+ *(static_cast<memory*>(softmax_dst_memory_p.get())));
+ dev_ctx.SetBlob(key_softmax_p, softmax_p);
+ } else {
+ // Primitives already exist
+ auto src_memory_p = std::static_pointer_cast<memory>(
+ dev_ctx.GetBlob(key_softmax_src_mem_p));
+ PADDLE_ENFORCE(src_memory_p != nullptr,
+ "Fail to find softmax src mem_p in device context");
+ auto dst_memory_p = std::static_pointer_cast<memory>(
+ dev_ctx.GetBlob(key_softmax_dst_mem_p));
+ PADDLE_ENFORCE(dst_memory_p != nullptr,
+ "Fail to find softmax dst mem_p in device context");
+ src_memory_p->set_data_handle(
+ reinterpret_cast<void*>(const_cast<T*>(input_data)));
+ dst_memory_p->set_data_handle(output_data);
+ }
+
+ std::vector<primitive> pipeline{
+ *(static_cast<softmax_forward::primitive*>(softmax_p.get()))};
stream(stream::kind::eager).submit(pipeline).wait();
const bool is_test = ctx.Attr<bool>("is_test");
From 6ef60de6f1cb4552b2ecb0b02e6282072b062b3a Mon Sep 17 00:00:00 2001
From: "yi.wu" <yi.wu@baifendian.com>
Date: Sat, 12 May 2018 00:05:43 +0800
Subject: [PATCH 075/195] update
---
.clang_format.hook | 2 +-
paddle/fluid/operators/detail/sendrecvop_utils.cc | 2 +-
paddle/fluid/operators/gen_nccl_id_op.cc | 1 +
3 files changed, 3 insertions(+), 2 deletions(-)
diff --git a/.clang_format.hook b/.clang_format.hook
index 1d92821686..edec286b77 100755
--- a/.clang_format.hook
+++ b/.clang_format.hook
@@ -1,7 +1,7 @@
#!/bin/bash
set -e
-readonly VERSION="3.8"
+readonly VERSION="7.0"
version=$(clang-format -version)
diff --git a/paddle/fluid/operators/detail/sendrecvop_utils.cc b/paddle/fluid/operators/detail/sendrecvop_utils.cc
index f3ac149947..07c43554bc 100644
--- a/paddle/fluid/operators/detail/sendrecvop_utils.cc
+++ b/paddle/fluid/operators/detail/sendrecvop_utils.cc
@@ -162,7 +162,7 @@ void SerializeToByteBuffer(const std::string& name, framework::Variable* var,
if (var->IsType<ncclUniqueId>()) {
e.WriteVarlengthBeginning(VarMsg::kSerializedFieldNumber,
NCCL_UNIQUE_ID_BYTES);
- ncclUniqueId& uid = var->Get<ncclUniqueId>();
+ const ncclUniqueId& uid = var->Get<ncclUniqueId>();
e.WriteRawBytes(std::string(uid.internal, NCCL_UNIQUE_ID_BYTES));
// for serialize NCCL_ID
diff --git a/paddle/fluid/operators/gen_nccl_id_op.cc b/paddle/fluid/operators/gen_nccl_id_op.cc
index 77cd4a460a..6d50bd13e8 100644
--- a/paddle/fluid/operators/gen_nccl_id_op.cc
+++ b/paddle/fluid/operators/gen_nccl_id_op.cc
@@ -23,6 +23,7 @@ limitations under the License. */
#include "paddle/fluid/framework/threadpool.h"
#include "paddle/fluid/operators/detail/grpc_client.h"
#include "paddle/fluid/operators/detail/grpc_server.h"
+#include "paddle/fluid/platform/nccl_helper.h"
namespace paddle {
namespace operators {
From 6387a15be237031ff11847f7ee88f113bbd65b50 Mon Sep 17 00:00:00 2001
From: "yi.wu" <yi.wu@baifendian.com>
Date: Sat, 12 May 2018 00:19:01 +0800
Subject: [PATCH 076/195] update
---
.clang_format.hook | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/.clang_format.hook b/.clang_format.hook
index edec286b77..1d92821686 100755
--- a/.clang_format.hook
+++ b/.clang_format.hook
@@ -1,7 +1,7 @@
#!/bin/bash
set -e
-readonly VERSION="7.0"
+readonly VERSION="3.8"
version=$(clang-format -version)
From 2a971f3084adc216950c450288bc63ea94212752 Mon Sep 17 00:00:00 2001
From: Qiao Longfei <qiaolongfei@baidu.com>
Date: Sat, 12 May 2018 02:47:26 +0800
Subject: [PATCH 077/195] Add inferencer infer (#10445)
* add Inference.infer
* optimize code
* update no_test_word2vec_new_api.py
* update trainer
* split check_and_get_place
* use inference_program to save inference model in Trainer
* update demo
* update save_inference_model
* clean code
---
python/paddle/fluid/inferencer.py | 53 +++++++-----
python/paddle/fluid/io.py | 10 ++-
.../word2vec/no_test_word2vec_new_api.py | 28 +++----
python/paddle/fluid/trainer.py | 83 ++++++++++++-------
4 files changed, 104 insertions(+), 70 deletions(-)
diff --git a/python/paddle/fluid/inferencer.py b/python/paddle/fluid/inferencer.py
index b38526bc57..1b8b9c0762 100644
--- a/python/paddle/fluid/inferencer.py
+++ b/python/paddle/fluid/inferencer.py
@@ -16,31 +16,42 @@ import core
import framework
import executor
import io
+from trainer import check_and_get_place
+
__all__ = ['Inferencer', ]
class Inferencer(object):
- def __init__(self, network_func, param_path=None, place=None):
- # 1. we need to generate a framework.Program by calling
- # network_func. Reference: fluid.program_guard in test_word2vec.py
-
- # 2. move the default_main_program to self.program.
-
- # 3. run the default_startup program.
-
- # 4. load params from param_path into scope
+ def __init__(self, param_path, place=None):
+ """
+ :param param_path: the path where the inference model is saved by fluid.io.save_inference_model
+ :param place: place to do the inference
+ """
+ self.param_path = param_path
self.scope = core.Scope()
- self.place = place
- self.startup_program = framework.Program()
- # TODO: generate the startup_program with network_func
-
- exe = executor.Executor(place)
- exe.run(self.startup_program, scope=self.scope)
- if param_path:
+ self.exe = executor.Executor(check_and_get_place(place))
+ with executor.scope_guard(self.scope):
# load params from param_path into scope
- io.load_persistables(exe, dirname=param_path)
-
- def infer(self, inputs):
- # run self.program
- pass
+ [self.inference_program, _,
+ self.fetch_targets] = io.load_inference_model(
+ executor=self.exe, dirname=param_path)
+
+ def infer(self, inputs, return_numpy=True):
+ """
+ :param inputs: a map of {"input_name": input_var} that will be feed into the inference program
+ to get the predict value
+ :param return_numpy: if return numpy value for row tensor
+ :return: the predict value of the inference model
+ """
+ if not isinstance(inputs, dict):
+ raise ValueError(
+ "inputs should be a map of {'input_name': input_var}")
+
+ with executor.scope_guard(self.scope):
+ results = self.exe.run(self.inference_program,
+ feed=inputs,
+ fetch_list=self.fetch_targets,
+ return_numpy=return_numpy)
+
+ return results
diff --git a/python/paddle/fluid/io.py b/python/paddle/fluid/io.py
index 08b8a878b6..54506e97ed 100644
--- a/python/paddle/fluid/io.py
+++ b/python/paddle/fluid/io.py
@@ -263,6 +263,9 @@ def get_inference_program(target_vars, main_program=None):
def prepend_feed_ops(inference_program,
feed_target_names,
feed_holder_name='feed'):
+ if len(feed_target_names) == 0:
+ return
+
global_block = inference_program.global_block()
feed_var = global_block.create_var(
name=feed_holder_name,
@@ -323,9 +326,10 @@ def save_inference_model(dirname,
if isinstance(feeded_var_names, basestring):
feeded_var_names = [feeded_var_names]
else:
- if not (bool(feeded_var_names) and all(
- isinstance(name, basestring) for name in feeded_var_names)):
- raise ValueError("'feed_var_names' should be a list of str.")
+ if len(feeded_var_names) > 0:
+ if not (bool(feeded_var_names) and all(
+ isinstance(name, basestring) for name in feeded_var_names)):
+ raise ValueError("'feed_var_names' should be a list of str.")
if isinstance(target_vars, Variable):
target_vars = [target_vars]
diff --git a/python/paddle/fluid/tests/book/high-level-api/word2vec/no_test_word2vec_new_api.py b/python/paddle/fluid/tests/book/high-level-api/word2vec/no_test_word2vec_new_api.py
index 93f7757a66..00ba4acf88 100644
--- a/python/paddle/fluid/tests/book/high-level-api/word2vec/no_test_word2vec_new_api.py
+++ b/python/paddle/fluid/tests/book/high-level-api/word2vec/no_test_word2vec_new_api.py
@@ -99,45 +99,45 @@ def train(use_cuda, is_sparse, save_path):
place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
def event_handler(event):
- # print type(event)
if isinstance(event, fluid.EndEpochEvent):
outs = trainer.test(reader=test_reader)
avg_cost = outs[0]
print("loss= ", avg_cost)
if avg_cost < 5.0:
- trainer.save_params(save_path)
+ trainer.save_inference_model(save_path)
return
if math.isnan(avg_cost):
sys.exit("got NaN loss, training failed.")
trainer = fluid.Trainer(
partial(train_program, is_sparse),
+ partial(inference_program, is_sparse),
fluid.optimizer.SGD(learning_rate=0.001),
place=place)
trainer.train(
- reader=train_reader, num_epochs=100, event_handler=event_handler)
+ reader=train_reader, num_epochs=1, event_handler=event_handler)
def infer(use_cuda, is_sparse, save_path):
place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
- inferencer = fluid.Inferencer(
- partial(inference_program, is_sparse),
- param_path=save_path,
- place=place)
+ inferencer = fluid.Inferencer(param_path=save_path, place=place)
lod = [0, 1]
first_word = create_random_lodtensor(lod, place, low=0, high=dict_size - 1)
second_word = create_random_lodtensor(lod, place, low=0, high=dict_size - 1)
third_word = create_random_lodtensor(lod, place, low=0, high=dict_size - 1)
fourth_word = create_random_lodtensor(lod, place, low=0, high=dict_size - 1)
- result = inferencer.infer({
- 'firstw': first_word,
- 'secondw': second_word,
- 'thirdw': third_word,
- 'forthw': fourth_word
- })
- print(result)
+
+ result = inferencer.infer(
+ {
+ 'firstw': first_word,
+ 'secondw': second_word,
+ 'thirdw': third_word,
+ 'forthw': fourth_word
+ },
+ return_numpy=False)
+ print(np.array(result[0]))
def main(use_cuda, is_sparse):
diff --git a/python/paddle/fluid/trainer.py b/python/paddle/fluid/trainer.py
index 30b58b465e..67d8be82d5 100644
--- a/python/paddle/fluid/trainer.py
+++ b/python/paddle/fluid/trainer.py
@@ -19,7 +19,7 @@ import executor
import data_feeder
import contextlib
import io
-import transpiler
+import unique_name
# optimizer is same as the parameter of Trainer.__init__. Rename it to opt_module
import optimizer as opt_module
@@ -56,26 +56,62 @@ class EndStepEvent(object):
self.step = step_id
+def check_and_get_place(place):
+ """
+ Check the type of place or get the default place
+ Args:
+ place(None|core.CUDAPlace|core.CPUPlace): the place that trainer will be executed on.
+
+ Raises:
+ TypeError if the type mismatched.
+
+ Returns:
+ the original place if it is not None.
+ if fluid is compiled with CUDA, returns CUDAPlace(0) by default.
+ Otherwise returns CPUPlace by default.
+ """
+ if place is None:
+ if core.is_compiled_with_cuda():
+ return core.CUDAPlace(0)
+ else:
+ return core.CPUPlace()
+ else:
+ if not isinstance(place, core.CUDAPlace) and not isinstance(
+ place, core.CPUPlace):
+ raise TypeError("Place should be either CUDAPlace or CPUPlace")
+ return place
+
+
class Trainer(object):
"""
Args:
- program_func(callable): A function which will return loss. The loss must be a scaler.
+ train_func(callable): A function which will return loss. The loss must be a scalar.
+ infer_func(callable): A function which will return predict, used to save inference model
optimizer(optimizer.Optimizer): The optimizer should be an instance of Optimizer
place: The device place of this trainer.
"""
- def __init__(self, program_func, optimizer, param_path=None, place=None):
+ def __init__(self,
+ train_func,
+ infer_func,
+ optimizer,
+ param_path=None,
+ place=None):
# 1. we need to generate a framework.Program by calling
# program_func. Reference: fluid.program_guard in
# test_word2vec.py
+ if not isinstance(optimizer, opt_module.Optimizer):
+ raise TypeError("The optimizer should be an instance of Optimizer")
+
+ self.infer_func = infer_func
self.scope = core.Scope()
self.startup_program = framework.Program()
self.train_program = framework.Program()
with framework.program_guard(self.train_program, self.startup_program):
- program_func_outs = program_func()
+ program_func_outs = train_func()
self.test_outputs = program_func_outs if isinstance(
program_func_outs, list) else [program_func_outs]
self.test_program = self.train_program.clone()
@@ -86,9 +122,9 @@ class Trainer(object):
loss = self.test_outputs[0]
optimize_ops, params_grads = optimizer.minimize(loss)
- self.place = Trainer._check_and_get_place(place)
+ self.place = check_and_get_place(place)
- self.dist_transpile_if_necessary(optimize_ops, params_grads)
+ self._dist_transpile_if_necessary(optimize_ops, params_grads)
# 2. move the default_main_program to self.program and run the
# default_startup program on an empty core.Scope()
@@ -101,7 +137,7 @@ class Trainer(object):
# load params from param_path into scope
io.load_persistables(exe, dirname=param_path)
- def dist_transpile_if_necessary(self, optimize_ops, params_grads):
+ def _dist_transpile_if_necessary(self, optimize_ops, params_grads):
if "PADDLE_TRAINING_ROLE" not in os.environ:
return
@@ -190,31 +226,14 @@ class Trainer(object):
exe = executor.Executor(self.place)
io.save_persistables(exe, dirname=param_path)
- @staticmethod
- def _check_and_get_place(place):
- """
- Check the type of place or get the default place
- Args:
- place(None|core.CUDAPlace|core.CPUPlace): the place that trainer will be executed on.
-
- Raises:
- TypeError if the type mismatched.
-
- Returns:
- the original place if it is not None.
- if fluid is compiled with CUDA, returns CUDAPlace(0) by default.
- Otherwise returns CPUPlace by default.
- """
- if place is None:
- if core.is_compiled_with_cuda():
- return core.CUDAPlace(0)
- else:
- return core.CPUPlace()
- else:
- if not isinstance(place, core.CUDAPlace) and not isinstance(
- place, core.CPUPlace):
- raise TypeError("Place should be either CUDAPlace or CPUPlace")
- return place
+ def save_inference_model(self, model_path):
+ inference_program = framework.Program()
+ with framework.program_guard(inference_program):
+ with unique_name.guard():
+ predict_var = self.infer_func()
+ predict_var = self.train_program.block(0).var(predict_var.name)
+ exe = executor.Executor(self.place)
+ io.save_inference_model(model_path, [], [predict_var], exe)
@contextlib.contextmanager
def _prog_and_scope_guard(self):
From 236dc7be458d7e508ac62db03d3b7c9c51f88941 Mon Sep 17 00:00:00 2001
From: Xiaohu Zhu <xhzhu.nju@gmail.com>
Date: Sat, 12 May 2018 02:51:19 +0800
Subject: [PATCH 078/195] typo fixed (#10600)
typo fixed
---
doc/fluid/design/concepts/lod_tensor.md | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/doc/fluid/design/concepts/lod_tensor.md b/doc/fluid/design/concepts/lod_tensor.md
index a88292e788..d606d7a790 100644
--- a/doc/fluid/design/concepts/lod_tensor.md
+++ b/doc/fluid/design/concepts/lod_tensor.md
@@ -155,7 +155,7 @@ into offsets
3 2+3 4+5 1+9 2+10 3+12
```
-so we know that the first sentence is from word 0 to word 3, and the second sentence from work 3 to word 5.
+so we know that the first sentence is from word 0 to word 3, and the second sentence from word 3 to word 5.
Similarly, the lengths in the top level LoD
From 177324b0674d9f325823a02336d32319f4925601 Mon Sep 17 00:00:00 2001
From: Jeff Wang <wangjeff@baidu.com>
Date: Fri, 11 May 2018 14:52:32 -0700
Subject: [PATCH 079/195] [Test-driven] Recognize Digit: update mnist test
cases with the new API syntax. (#10507)
* Update the mnist test cases with the new API syntax.
* Turn on the tests for MNIST
* delete the test files got merged accidently.
* Enable the mnist tests. ready for test driven development.
* Comment out the infer first
This is to confirm that the Trainer.train is working
* Add CMake file to include the tests
* Make the train program only return avg_cost for now
* Update the tests to use the latest syntax
---
python/paddle/fluid/tests/book/CMakeLists.txt | 2 +
.../tests/book/high-level-api/CMakeLists.txt | 9 +++
.../recognize_digits/CMakeLists.txt | 7 ++
..._conv.py => test_recognize_digits_conv.py} | 77 +++++++++++--------
...ts_mlp.py => test_recognize_digits_mlp.py} | 76 ++++++++++--------
5 files changed, 111 insertions(+), 60 deletions(-)
create mode 100644 python/paddle/fluid/tests/book/high-level-api/CMakeLists.txt
create mode 100644 python/paddle/fluid/tests/book/high-level-api/recognize_digits/CMakeLists.txt
rename python/paddle/fluid/tests/book/high-level-api/recognize_digits/{notest_recognize_digits_conv.py => test_recognize_digits_conv.py} (57%)
rename python/paddle/fluid/tests/book/high-level-api/recognize_digits/{notest_recognize_digits_mlp.py => test_recognize_digits_mlp.py} (54%)
diff --git a/python/paddle/fluid/tests/book/CMakeLists.txt b/python/paddle/fluid/tests/book/CMakeLists.txt
index 673c965b66..ee734f3c78 100644
--- a/python/paddle/fluid/tests/book/CMakeLists.txt
+++ b/python/paddle/fluid/tests/book/CMakeLists.txt
@@ -5,3 +5,5 @@ string(REPLACE ".py" "" TEST_OPS "${TEST_OPS}")
foreach(src ${TEST_OPS})
py_test(${src} SRCS ${src}.py)
endforeach()
+
+add_subdirectory(high-level-api)
diff --git a/python/paddle/fluid/tests/book/high-level-api/CMakeLists.txt b/python/paddle/fluid/tests/book/high-level-api/CMakeLists.txt
new file mode 100644
index 0000000000..9ab00325a2
--- /dev/null
+++ b/python/paddle/fluid/tests/book/high-level-api/CMakeLists.txt
@@ -0,0 +1,9 @@
+file(GLOB TEST_OPS RELATIVE "${CMAKE_CURRENT_SOURCE_DIR}" "test_*.py")
+string(REPLACE ".py" "" TEST_OPS "${TEST_OPS}")
+
+# default test
+foreach(src ${TEST_OPS})
+ py_test(${src} SRCS ${src}.py)
+endforeach()
+
+add_subdirectory(recognize_digits)
diff --git a/python/paddle/fluid/tests/book/high-level-api/recognize_digits/CMakeLists.txt b/python/paddle/fluid/tests/book/high-level-api/recognize_digits/CMakeLists.txt
new file mode 100644
index 0000000000..673c965b66
--- /dev/null
+++ b/python/paddle/fluid/tests/book/high-level-api/recognize_digits/CMakeLists.txt
@@ -0,0 +1,7 @@
+file(GLOB TEST_OPS RELATIVE "${CMAKE_CURRENT_SOURCE_DIR}" "test_*.py")
+string(REPLACE ".py" "" TEST_OPS "${TEST_OPS}")
+
+# default test
+foreach(src ${TEST_OPS})
+ py_test(${src} SRCS ${src}.py)
+endforeach()
diff --git a/python/paddle/fluid/tests/book/high-level-api/recognize_digits/notest_recognize_digits_conv.py b/python/paddle/fluid/tests/book/high-level-api/recognize_digits/test_recognize_digits_conv.py
similarity index 57%
rename from python/paddle/fluid/tests/book/high-level-api/recognize_digits/notest_recognize_digits_conv.py
rename to python/paddle/fluid/tests/book/high-level-api/recognize_digits/test_recognize_digits_conv.py
index a8282c71f8..1f91f471f2 100644
--- a/python/paddle/fluid/tests/book/high-level-api/recognize_digits/notest_recognize_digits_conv.py
+++ b/python/paddle/fluid/tests/book/high-level-api/recognize_digits/test_recognize_digits_conv.py
@@ -21,7 +21,6 @@ import unittest
import math
import sys
import os
-import paddle.v2.dataset as dataset
BATCH_SIZE = 64
@@ -54,47 +53,65 @@ def train_program():
predict = inference_program()
cost = fluid.layers.cross_entropy(input=predict, label=label)
avg_cost = fluid.layers.mean(cost)
- acc = fluid.layers.accuracy(input=predict, label=label)
- return avg_cost, acc
+ # acc = fluid.layers.accuracy(input=predict, label=label)
+ # return avg_cost, acc
+ return avg_cost
def train(use_cuda, save_dirname):
place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
-
optimizer = fluid.optimizer.Adam(learning_rate=0.001)
- trainer = fluid.Trainer(train_program, place=place, optimizer=optimizer)
+
+ trainer = fluid.Trainer(
+ train_func=train_program,
+ infer_func=inference_program,
+ place=place,
+ optimizer=optimizer)
def event_handler(event):
- if isinstance(event, fluid.EndIteration):
- avg_cost, acc = event.values
- print("avg_cost: %s" % avg_cost)
- print("acc : %s" % acc)
-
- if (event.batch_id + 1) % 10 == 0:
- test_metrics = trainer.test(reader=dataset.mnist.test())
- avg_cost_set = test_metrics[0]
- acc_set = test_metrics[1]
-
- # get test acc and loss
- acc = numpy.array(acc_set).mean()
- avg_cost = numpy.array(avg_cost_set).mean()
- if float(acc) > 0.2: # Smaller value to increase CI speed
- trainer.save_params(save_dirname)
- else:
- print('BatchID {0}, Test Loss {1:0.2}, Acc {2:0.2}'.format(
- event.batch_id + 1, float(avg_cost), float(acc)))
- if math.isnan(float(avg_cost)):
- sys.exit("got NaN loss, training failed.")
+ if isinstance(event, fluid.EndEpochEvent):
+ # if (event.epoch + 1) % 10 == 0:
+ # trainer.save_params(save_dirname)
+ trainer.save_inference_model(save_dirname)
+
+ # TODO: Uncomment this part once we are sure that .train is working
+ # test_reader = paddle.batch(
+ # paddle.dataset.mnist.test(), batch_size=BATCH_SIZE)
+ # test_metrics = trainer.test(reader=test_reader)
+ # avg_cost_set = test_metrics[0]
+ # acc_set = test_metrics[1]
+ #
+ # # get test acc and loss
+ # acc = numpy.array(acc_set).mean()
+ # avg_cost = numpy.array(avg_cost_set).mean()
+ #
+ # print("avg_cost: %s" % avg_cost)
+ # print("acc : %s" % acc)
+ #
+ # if float(acc) > 0.2: # Smaller value to increase CI speed
+ # trainer.save_params(save_dirname)
+ # else:
+ # print('BatchID {0}, Test Loss {1:0.2}, Acc {2:0.2}'.format(
+ # event.epoch + 1, float(avg_cost), float(acc)))
+ # if math.isnan(float(avg_cost)):
+ # sys.exit("got NaN loss, training failed.")
+
+ train_reader = paddle.batch(
+ paddle.reader.shuffle(
+ paddle.dataset.mnist.train(), buf_size=500),
+ batch_size=BATCH_SIZE)
trainer.train(
- reader=dataset.mnist.train(), num_pass=100, event_handler=event_handler)
+ num_epochs=1,
+ event_handler=event_handler,
+ reader=train_reader,
+ feed_order=['img', 'label'])
def infer(use_cuda, save_dirname=None):
place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
- inferencer = fluid.Inferencer(
- inference_program, param_path=save_dirname, place=place)
+ inferencer = fluid.Inferencer(param_path=save_dirname, place=place)
batch_size = 1
tensor_img = numpy.random.uniform(-1.0, 1.0,
@@ -114,5 +131,5 @@ def main(use_cuda):
if __name__ == '__main__':
- for use_cuda in (False, True):
- main(use_cuda=use_cuda)
+ # for use_cuda in (False, True):
+ main(use_cuda=False)
diff --git a/python/paddle/fluid/tests/book/high-level-api/recognize_digits/notest_recognize_digits_mlp.py b/python/paddle/fluid/tests/book/high-level-api/recognize_digits/test_recognize_digits_mlp.py
similarity index 54%
rename from python/paddle/fluid/tests/book/high-level-api/recognize_digits/notest_recognize_digits_mlp.py
rename to python/paddle/fluid/tests/book/high-level-api/recognize_digits/test_recognize_digits_mlp.py
index 3efa931d58..f072d70abd 100644
--- a/python/paddle/fluid/tests/book/high-level-api/recognize_digits/notest_recognize_digits_mlp.py
+++ b/python/paddle/fluid/tests/book/high-level-api/recognize_digits/test_recognize_digits_mlp.py
@@ -21,7 +21,6 @@ import unittest
import math
import sys
import os
-import paddle.v2.dataset as dataset
BATCH_SIZE = 64
@@ -41,47 +40,64 @@ def train_program():
predict = inference_program()
cost = fluid.layers.cross_entropy(input=predict, label=label)
avg_cost = fluid.layers.mean(cost)
- acc = fluid.layers.accuracy(input=predict, label=label)
- return avg_cost, acc
+ # acc = fluid.layers.accuracy(input=predict, label=label)
+ # return avg_cost, acc
+ return avg_cost
def train(use_cuda, save_dirname):
place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
-
optimizer = fluid.optimizer.Adam(learning_rate=0.001)
- trainer = fluid.Trainer(train_program, place=place, optimizer=optimizer)
+
+ trainer = fluid.Trainer(
+ train_func=train_program,
+ infer_func=inference_program,
+ place=place,
+ optimizer=optimizer)
def event_handler(event):
- if isinstance(event, fluid.EndIteration):
- avg_cost, acc = event.values
- print("avg_cost: %s" % avg_cost)
- print("acc : %s" % acc)
-
- if (event.batch_id + 1) % 10 == 0:
- test_metrics = trainer.test(reader=dataset.mnist.test())
- avg_cost_set = test_metrics[0]
- acc_set = test_metrics[1]
-
- # get test acc and loss
- acc = numpy.array(acc_set).mean()
- avg_cost = numpy.array(avg_cost_set).mean()
- if float(acc) > 0.2: # Smaller value to increase CI speed
- trainer.save_params(save_dirname)
- else:
- print('BatchID {0}, Test Loss {1:0.2}, Acc {2:0.2}'.format(
- event.batch_id + 1, float(avg_cost), float(acc)))
- if math.isnan(float(avg_cost)):
- sys.exit("got NaN loss, training failed.")
+ if isinstance(event, fluid.EndEpochEvent):
+ # if (event.epoch + 1) % 10 == 0:
+ trainer.save_inference_model(save_dirname)
+
+ # TODO: Uncomment this part once we are sure that .train is working
+ # test_reader = paddle.batch(
+ # paddle.dataset.mnist.test(), batch_size=BATCH_SIZE)
+ # test_metrics = trainer.test(reader=test_reader)
+ # avg_cost_set = test_metrics[0]
+ # acc_set = test_metrics[1]
+ #
+ # # get test acc and loss
+ # acc = numpy.array(acc_set).mean()
+ # avg_cost = numpy.array(avg_cost_set).mean()
+ #
+ # print("avg_cost: %s" % avg_cost)
+ # print("acc : %s" % acc)
+ #
+ # if float(acc) > 0.2: # Smaller value to increase CI speed
+ # trainer.save_params(save_dirname)
+ # else:
+ # print('BatchID {0}, Test Loss {1:0.2}, Acc {2:0.2}'.format(
+ # event.epoch + 1, float(avg_cost), float(acc)))
+ # if math.isnan(float(avg_cost)):
+ # sys.exit("got NaN loss, training failed.")
+
+ train_reader = paddle.batch(
+ paddle.reader.shuffle(
+ paddle.dataset.mnist.train(), buf_size=500),
+ batch_size=BATCH_SIZE)
trainer.train(
- reader=dataset.mnist.train(), num_pass=100, event_handler=event_handler)
+ num_epochs=1,
+ event_handler=event_handler,
+ reader=train_reader,
+ feed_order=['img', 'label'])
def infer(use_cuda, save_dirname=None):
place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
- inferencer = fluid.Inferencer(
- inference_program, param_path=save_dirname, place=place)
+ inferencer = fluid.Inferencer(param_path=save_dirname, place=place)
batch_size = 1
tensor_img = numpy.random.uniform(-1.0, 1.0,
@@ -101,5 +117,5 @@ def main(use_cuda):
if __name__ == '__main__':
- for use_cuda in (False, True):
- main(use_cuda=use_cuda)
+ # for use_cuda in (False, True):
+ main(use_cuda=False)
From 5ae0c664b01d36a0fbdaf78886b08bc9e5d3b883 Mon Sep 17 00:00:00 2001
From: "yi.wu" <yi.wu@baifendian.com>
Date: Sat, 12 May 2018 09:02:39 +0800
Subject: [PATCH 080/195] fix build and merge develop
---
paddle/fluid/operators/test_send_nccl_id.cc | 12 +++++++++---
1 file changed, 9 insertions(+), 3 deletions(-)
diff --git a/paddle/fluid/operators/test_send_nccl_id.cc b/paddle/fluid/operators/test_send_nccl_id.cc
index 2c3c5ea0a0..bbae1d54aa 100644
--- a/paddle/fluid/operators/test_send_nccl_id.cc
+++ b/paddle/fluid/operators/test_send_nccl_id.cc
@@ -24,6 +24,7 @@ limitations under the License. */
#include "paddle/fluid/operators/listen_and_serv_op.h"
#include "paddle/fluid/operators/math/math_function.h"
#include "paddle/fluid/operators/math/selected_rows_functor.h"
+#include "paddle/fluid/platform/nccl_helper.h"
#include "paddle/fluid/string/printf.h"
USE_NO_KERNEL_OP(listen_and_serv);
@@ -36,7 +37,7 @@ namespace string = paddle::string;
std::unique_ptr<detail::AsyncGRPCServer> rpc_service;
-void StartServer() {
+void StartServer(std::atomic<bool>* initialized) {
f::Scope scope;
p::CPUPlace place;
scope.Var(NCCL_ID_VARNAME);
@@ -54,6 +55,7 @@ void StartServer() {
std::thread server_thread(
std::bind(&detail::AsyncGRPCServer::RunSyncUpdate, rpc_service.get()));
+ *initialized = true;
rpc_service->SetCond(0);
auto recv = rpc_service->Get();
LOG(INFO) << "got nccl id and stop server...";
@@ -62,9 +64,13 @@ void StartServer() {
}
TEST(SendNcclId, Normal) {
- std::thread server_thread(StartServer);
+ std::atomic<bool> initialized{false};
+ std::thread server_thread(StartServer, &initialized);
+ while (!initialized) {
+ }
// wait server to start
- rpc_service.WaitServerReady();
+ // sleep(2);
+ rpc_service->WaitServerReady();
f::Scope scope;
p::CPUPlace place;
From 43b6d4f8cb39b18bd192b070f40ae8e3f228068a Mon Sep 17 00:00:00 2001
From: baiyf <baiyfbupt@gmail.com>
Date: Sat, 12 May 2018 02:11:23 -0500
Subject: [PATCH 081/195] put detection op together (#10595)
---
paddle/fluid/operators/CMakeLists.txt | 5 ++++
.../fluid/operators/detection/CMakeLists.txt | 29 +++++++++++++++++++
.../{ => detection}/bipartite_match_op.cc | 0
.../operators/{ => detection}/box_coder_op.cc | 2 +-
.../operators/{ => detection}/box_coder_op.cu | 2 +-
.../operators/{ => detection}/box_coder_op.h | 0
.../{ => detection}/iou_similarity_op.cc | 2 +-
.../{ => detection}/iou_similarity_op.cu | 2 +-
.../{ => detection}/iou_similarity_op.h | 0
.../{ => detection}/mine_hard_examples_op.cc | 0
.../{ => detection}/multiclass_nms_op.cc | 0
.../operators/{ => detection}/prior_box_op.cc | 2 +-
.../operators/{ => detection}/prior_box_op.cu | 2 +-
.../operators/{ => detection}/prior_box_op.h | 0
.../{ => detection}/target_assign_op.cc | 2 +-
.../{ => detection}/target_assign_op.cu | 2 +-
.../{ => detection}/target_assign_op.h | 0
17 files changed, 42 insertions(+), 8 deletions(-)
create mode 100644 paddle/fluid/operators/detection/CMakeLists.txt
rename paddle/fluid/operators/{ => detection}/bipartite_match_op.cc (100%)
rename paddle/fluid/operators/{ => detection}/box_coder_op.cc (99%)
rename paddle/fluid/operators/{ => detection}/box_coder_op.cu (99%)
rename paddle/fluid/operators/{ => detection}/box_coder_op.h (100%)
rename paddle/fluid/operators/{ => detection}/iou_similarity_op.cc (98%)
rename paddle/fluid/operators/{ => detection}/iou_similarity_op.cu (92%)
rename paddle/fluid/operators/{ => detection}/iou_similarity_op.h (100%)
rename paddle/fluid/operators/{ => detection}/mine_hard_examples_op.cc (100%)
rename paddle/fluid/operators/{ => detection}/multiclass_nms_op.cc (100%)
rename paddle/fluid/operators/{ => detection}/prior_box_op.cc (99%)
rename paddle/fluid/operators/{ => detection}/prior_box_op.cu (99%)
rename paddle/fluid/operators/{ => detection}/prior_box_op.h (100%)
rename paddle/fluid/operators/{ => detection}/target_assign_op.cc (98%)
rename paddle/fluid/operators/{ => detection}/target_assign_op.cu (97%)
rename paddle/fluid/operators/{ => detection}/target_assign_op.h (100%)
diff --git a/paddle/fluid/operators/CMakeLists.txt b/paddle/fluid/operators/CMakeLists.txt
index fbeacb66ce..c14a2b7786 100644
--- a/paddle/fluid/operators/CMakeLists.txt
+++ b/paddle/fluid/operators/CMakeLists.txt
@@ -270,6 +270,11 @@ foreach(src ${READER_LIBRARY})
set(OP_LIBRARY ${src} ${OP_LIBRARY})
endforeach()
+add_subdirectory(detection)
+foreach(src ${DETECTION_LIBRARY})
+ set(OP_LIBRARY ${src} ${OP_LIBRARY})
+endforeach()
+
set(GLOB_OP_LIB ${OP_LIBRARY} CACHE INTERNAL "Global OP library")
cc_test(gather_test SRCS gather_test.cc DEPS tensor)
diff --git a/paddle/fluid/operators/detection/CMakeLists.txt b/paddle/fluid/operators/detection/CMakeLists.txt
new file mode 100644
index 0000000000..a5bb58c2f4
--- /dev/null
+++ b/paddle/fluid/operators/detection/CMakeLists.txt
@@ -0,0 +1,29 @@
+set(LOCAL_DETECTION_LIBS)
+
+function(detection_library TARGET_NAME)
+ set(oneValueArgs "")
+ set(multiValueArgs SRCS DEPS)
+ set(options "")
+ set(common_deps op_registry)
+ set(pybind_flag 0)
+ cmake_parse_arguments(detection_library "${options}" "${oneValueArgs}"
+ "${multiValueArgs}" ${ARGN})
+ op_library(${TARGET_NAME} SRCS ${detection_library_SRCS} DEPS ${common_deps} ${detection_library_DEPS})
+ set(LOCAL_DETECTION_LIBS
+ ${TARGET_NAME}
+ ${LOCAL_DETECTION_LIBS}
+ PARENT_SCOPE)
+endfunction()
+
+detection_library(bipartite_match_op SRCS bipartite_match_op.cc)
+detection_library(box_coder_op SRCS box_coder_op.cc box_coder_op.cu)
+detection_library(iou_similarity_op SRCS iou_similarity_op.cc
+iou_similarity_op.cu)
+detection_library(mine_hard_examples_op SRCS mine_hard_examples_op.cc)
+detection_library(multiclass_nms_op SRCS multiclass_nms_op.cc)
+detection_library(prior_box_op SRCS prior_box_op.cc prior_box_op.cu)
+detection_library(target_assign_op SRCS target_assign_op.cc
+target_assign_op.cu)
+
+# Export local libraries to parent
+set(DETECTION_LIBRARY ${LOCAL_DETECTION_LIBS} PARENT_SCOPE)
diff --git a/paddle/fluid/operators/bipartite_match_op.cc b/paddle/fluid/operators/detection/bipartite_match_op.cc
similarity index 100%
rename from paddle/fluid/operators/bipartite_match_op.cc
rename to paddle/fluid/operators/detection/bipartite_match_op.cc
diff --git a/paddle/fluid/operators/box_coder_op.cc b/paddle/fluid/operators/detection/box_coder_op.cc
similarity index 99%
rename from paddle/fluid/operators/box_coder_op.cc
rename to paddle/fluid/operators/detection/box_coder_op.cc
index ce9bf10dc3..74848005d0 100644
--- a/paddle/fluid/operators/box_coder_op.cc
+++ b/paddle/fluid/operators/detection/box_coder_op.cc
@@ -9,7 +9,7 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
-#include "paddle/fluid/operators/box_coder_op.h"
+#include "paddle/fluid/operators/detection/box_coder_op.h"
namespace paddle {
namespace operators {
diff --git a/paddle/fluid/operators/box_coder_op.cu b/paddle/fluid/operators/detection/box_coder_op.cu
similarity index 99%
rename from paddle/fluid/operators/box_coder_op.cu
rename to paddle/fluid/operators/detection/box_coder_op.cu
index 708c7a5fa9..8cef8e0343 100644
--- a/paddle/fluid/operators/box_coder_op.cu
+++ b/paddle/fluid/operators/detection/box_coder_op.cu
@@ -9,7 +9,7 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
-#include "paddle/fluid/operators/box_coder_op.h"
+#include "paddle/fluid/operators/detection/box_coder_op.h"
#include "paddle/fluid/platform/cuda_primitives.h"
namespace paddle {
diff --git a/paddle/fluid/operators/box_coder_op.h b/paddle/fluid/operators/detection/box_coder_op.h
similarity index 100%
rename from paddle/fluid/operators/box_coder_op.h
rename to paddle/fluid/operators/detection/box_coder_op.h
diff --git a/paddle/fluid/operators/iou_similarity_op.cc b/paddle/fluid/operators/detection/iou_similarity_op.cc
similarity index 98%
rename from paddle/fluid/operators/iou_similarity_op.cc
rename to paddle/fluid/operators/detection/iou_similarity_op.cc
index 007e0af7a5..8e58605fce 100644
--- a/paddle/fluid/operators/iou_similarity_op.cc
+++ b/paddle/fluid/operators/detection/iou_similarity_op.cc
@@ -12,7 +12,7 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
-#include "paddle/fluid/operators/iou_similarity_op.h"
+#include "paddle/fluid/operators/detection/iou_similarity_op.h"
namespace paddle {
namespace operators {
diff --git a/paddle/fluid/operators/iou_similarity_op.cu b/paddle/fluid/operators/detection/iou_similarity_op.cu
similarity index 92%
rename from paddle/fluid/operators/iou_similarity_op.cu
rename to paddle/fluid/operators/detection/iou_similarity_op.cu
index f40a388d62..8342b4138c 100644
--- a/paddle/fluid/operators/iou_similarity_op.cu
+++ b/paddle/fluid/operators/detection/iou_similarity_op.cu
@@ -12,7 +12,7 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
-#include "paddle/fluid/operators/iou_similarity_op.h"
+#include "paddle/fluid/operators/detection/iou_similarity_op.h"
namespace ops = paddle::operators;
REGISTER_OP_CUDA_KERNEL(
diff --git a/paddle/fluid/operators/iou_similarity_op.h b/paddle/fluid/operators/detection/iou_similarity_op.h
similarity index 100%
rename from paddle/fluid/operators/iou_similarity_op.h
rename to paddle/fluid/operators/detection/iou_similarity_op.h
diff --git a/paddle/fluid/operators/mine_hard_examples_op.cc b/paddle/fluid/operators/detection/mine_hard_examples_op.cc
similarity index 100%
rename from paddle/fluid/operators/mine_hard_examples_op.cc
rename to paddle/fluid/operators/detection/mine_hard_examples_op.cc
diff --git a/paddle/fluid/operators/multiclass_nms_op.cc b/paddle/fluid/operators/detection/multiclass_nms_op.cc
similarity index 100%
rename from paddle/fluid/operators/multiclass_nms_op.cc
rename to paddle/fluid/operators/detection/multiclass_nms_op.cc
diff --git a/paddle/fluid/operators/prior_box_op.cc b/paddle/fluid/operators/detection/prior_box_op.cc
similarity index 99%
rename from paddle/fluid/operators/prior_box_op.cc
rename to paddle/fluid/operators/detection/prior_box_op.cc
index a0b069da0d..4e35c38e4e 100644
--- a/paddle/fluid/operators/prior_box_op.cc
+++ b/paddle/fluid/operators/detection/prior_box_op.cc
@@ -12,7 +12,7 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
-#include "paddle/fluid/operators/prior_box_op.h"
+#include "paddle/fluid/operators/detection/prior_box_op.h"
namespace paddle {
namespace operators {
diff --git a/paddle/fluid/operators/prior_box_op.cu b/paddle/fluid/operators/detection/prior_box_op.cu
similarity index 99%
rename from paddle/fluid/operators/prior_box_op.cu
rename to paddle/fluid/operators/detection/prior_box_op.cu
index 0ea8909296..f67e6ca91c 100644
--- a/paddle/fluid/operators/prior_box_op.cu
+++ b/paddle/fluid/operators/detection/prior_box_op.cu
@@ -12,7 +12,7 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
-#include "paddle/fluid/operators/prior_box_op.h"
+#include "paddle/fluid/operators/detection/prior_box_op.h"
namespace paddle {
namespace operators {
diff --git a/paddle/fluid/operators/prior_box_op.h b/paddle/fluid/operators/detection/prior_box_op.h
similarity index 100%
rename from paddle/fluid/operators/prior_box_op.h
rename to paddle/fluid/operators/detection/prior_box_op.h
diff --git a/paddle/fluid/operators/target_assign_op.cc b/paddle/fluid/operators/detection/target_assign_op.cc
similarity index 98%
rename from paddle/fluid/operators/target_assign_op.cc
rename to paddle/fluid/operators/detection/target_assign_op.cc
index 9fce216e88..3670019392 100644
--- a/paddle/fluid/operators/target_assign_op.cc
+++ b/paddle/fluid/operators/detection/target_assign_op.cc
@@ -12,7 +12,7 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
-#include "paddle/fluid/operators/target_assign_op.h"
+#include "paddle/fluid/operators/detection/target_assign_op.h"
namespace paddle {
namespace operators {
diff --git a/paddle/fluid/operators/target_assign_op.cu b/paddle/fluid/operators/detection/target_assign_op.cu
similarity index 97%
rename from paddle/fluid/operators/target_assign_op.cu
rename to paddle/fluid/operators/detection/target_assign_op.cu
index 24664f99b2..ddf6889942 100644
--- a/paddle/fluid/operators/target_assign_op.cu
+++ b/paddle/fluid/operators/detection/target_assign_op.cu
@@ -12,7 +12,7 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
-#include "paddle/fluid/operators/target_assign_op.h"
+#include "paddle/fluid/operators/detection/target_assign_op.h"
namespace paddle {
namespace operators {
diff --git a/paddle/fluid/operators/target_assign_op.h b/paddle/fluid/operators/detection/target_assign_op.h
similarity index 100%
rename from paddle/fluid/operators/target_assign_op.h
rename to paddle/fluid/operators/detection/target_assign_op.h
From ca7c5a24e0b721bfff8dc33f7aaef4e25bd365b6 Mon Sep 17 00:00:00 2001
From: yangyaming <mxscmxsc@gmail.com>
Date: Sat, 12 May 2018 07:31:23 +0000
Subject: [PATCH 082/195] Fix order of prior boxes.
---
paddle/gserver/layers/PriorBox.cpp | 33 ++++++++++++++++++++----------
1 file changed, 22 insertions(+), 11 deletions(-)
diff --git a/paddle/gserver/layers/PriorBox.cpp b/paddle/gserver/layers/PriorBox.cpp
index af2cc05a95..56a4d942f0 100644
--- a/paddle/gserver/layers/PriorBox.cpp
+++ b/paddle/gserver/layers/PriorBox.cpp
@@ -28,7 +28,7 @@ namespace paddle {
*/
class PriorBoxLayer : public Layer {
-public:
+public: // NOLINT
explicit PriorBoxLayer(const LayerConfig& config) : Layer(config) {}
bool init(const LayerMap& layerMap,
const ParameterMap& parameterMap) override;
@@ -36,7 +36,7 @@ public:
void forward(PassType passType) override;
void backward(const UpdateCallback& callback) override {}
-protected:
+protected: // NOLINT
int numPriors_;
std::vector<int> minSize_;
std::vector<int> maxSize_;
@@ -109,11 +109,18 @@ void PriorBoxLayer::forward(PassType passType) {
real boxWidth = minSize;
real boxHeight = minSize;
- // priors with different aspect ratios
- for (size_t r = 0; r < aspectRatio_.size(); r++) {
- real ar = aspectRatio_[r];
- boxWidth = minSize * sqrt(ar);
- boxHeight = minSize / sqrt(ar);
+ // first prior: aspect_ratio == 1.0, compatible to old logic
+ tmpPtr[idx++] = (centerX - boxWidth / 2.) / imageWidth;
+ tmpPtr[idx++] = (centerY - boxHeight / 2.) / imageHeight;
+ tmpPtr[idx++] = (centerX + boxWidth / 2.) / imageWidth;
+ tmpPtr[idx++] = (centerY + boxHeight / 2.) / imageHeight;
+ // set the variance.
+ for (int t = 0; t < 4; t++) tmpPtr[idx++] = variance_[t];
+
+ if (maxSize_.size() > 0) {
+ // square prior with size sqrt(minSize * maxSize)
+ real maxSize = maxSize_[s];
+ boxWidth = boxHeight = sqrt(minSize * maxSize);
tmpPtr[idx++] = (centerX - boxWidth / 2.) / imageWidth;
tmpPtr[idx++] = (centerY - boxHeight / 2.) / imageHeight;
tmpPtr[idx++] = (centerX + boxWidth / 2.) / imageWidth;
@@ -122,10 +129,14 @@ void PriorBoxLayer::forward(PassType passType) {
for (int t = 0; t < 4; t++) tmpPtr[idx++] = variance_[t];
}
- if (maxSize_.size() > 0) {
- // square prior with size sqrt(minSize * maxSize)
- real maxSize = maxSize_[s];
- boxWidth = boxHeight = sqrt(minSize * maxSize);
+ // priors with different aspect ratios
+ for (size_t r = 0; r < aspectRatio_.size(); r++) {
+ real ar = aspectRatio_[r];
+ if (fabs(ar - 1.0) < 1e-6) {
+ continue;
+ }
+ boxWidth = minSize * sqrt(ar);
+ boxHeight = minSize / sqrt(ar);
tmpPtr[idx++] = (centerX - boxWidth / 2.) / imageWidth;
tmpPtr[idx++] = (centerY - boxHeight / 2.) / imageHeight;
tmpPtr[idx++] = (centerX + boxWidth / 2.) / imageWidth;
From e5281b3c2d14fdd0cc515268307e29521eb40305 Mon Sep 17 00:00:00 2001
From: yuyang18 <reyoung@126.com>
Date: Mon, 14 May 2018 13:23:07 +0800
Subject: [PATCH 083/195] Clean code & add execution strategy
---
.../framework/details/execution_strategy.h | 29 ++++++++++
.../details/threaded_ssa_graph_executor.cc | 17 +++---
.../details/threaded_ssa_graph_executor.h | 11 ++--
paddle/fluid/framework/parallel_executor.cc | 9 ++--
paddle/fluid/framework/parallel_executor.h | 36 +++++++------
paddle/fluid/pybind/pybind.cc | 43 +++++++++------
python/paddle/fluid/__init__.py | 54 ++++++++++---------
python/paddle/fluid/parallel_executor.py | 51 ++++++++++--------
.../tests/unittests/test_parallel_executor.py | 8 +--
9 files changed, 154 insertions(+), 104 deletions(-)
create mode 100644 paddle/fluid/framework/details/execution_strategy.h
diff --git a/paddle/fluid/framework/details/execution_strategy.h b/paddle/fluid/framework/details/execution_strategy.h
new file mode 100644
index 0000000000..e8d510ec95
--- /dev/null
+++ b/paddle/fluid/framework/details/execution_strategy.h
@@ -0,0 +1,29 @@
+// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+// http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#pragma once
+
+namespace paddle {
+namespace framework {
+namespace details {
+
+struct ExecutionStrategy {
+ size_t num_threads_{0};
+ bool use_event_{true};
+ bool allow_op_delay_{false};
+};
+
+} // namespace details
+} // namespace framework
+} // namespace paddle
diff --git a/paddle/fluid/framework/details/threaded_ssa_graph_executor.cc b/paddle/fluid/framework/details/threaded_ssa_graph_executor.cc
index e90523ebe8..ef263d82c5 100644
--- a/paddle/fluid/framework/details/threaded_ssa_graph_executor.cc
+++ b/paddle/fluid/framework/details/threaded_ssa_graph_executor.cc
@@ -18,18 +18,17 @@ namespace paddle {
namespace framework {
namespace details {
ThreadedSSAGraphExecutor::ThreadedSSAGraphExecutor(
- size_t num_threads, bool use_event,
- const std::vector<Scope *> &local_scopes,
+ const ExecutionStrategy &strategy, const std::vector<Scope *> &local_scopes,
const std::vector<platform::Place> &places,
- std::unique_ptr<SSAGraph> &&graph, bool allow_op_delay)
+ std::unique_ptr<SSAGraph> &&graph)
: SSAGraphExecutor(std::move(graph)),
- pool_(num_threads >= 2 ? new ::ThreadPool(num_threads) : nullptr),
+ pool_(strategy.num_threads_ >= 2 ? new ::ThreadPool(strategy.num_threads_)
+ : nullptr),
local_scopes_(local_scopes),
places_(places),
fetch_ctxs_(places),
- use_event_(use_event),
running_ops_(0),
- allow_op_delay_(allow_op_delay) {}
+ strategy_(strategy) {}
FeedFetchList ThreadedSSAGraphExecutor::Run(
const std::vector<std::string> &fetch_tensors) {
@@ -86,7 +85,7 @@ FeedFetchList ThreadedSSAGraphExecutor::Run(
//
// NOTE: DelayedOps have a lower priority. It will be scheduled after all
// ready_ops have been performed.
- if (ready_ops.empty() && allow_op_delay_ && running_ops_ == 0) {
+ if (ready_ops.empty() && strategy_.allow_op_delay_ && running_ops_ == 0) {
run_all_ops(delayed_ops);
} else {
run_all_ops(ready_ops);
@@ -113,7 +112,7 @@ FeedFetchList ThreadedSSAGraphExecutor::Run(
auto &deps = pending_ops[op];
--deps;
if (deps == 0) {
- if (op->IsMultiDeviceTransfer() && allow_op_delay_) {
+ if (op->IsMultiDeviceTransfer() && strategy_.allow_op_delay_) {
delayed_ops.insert(op);
} else {
ready_ops.insert(op);
@@ -191,7 +190,7 @@ void ThreadedSSAGraphExecutor::RunOp(
auto op_run = [ready_var_q, op, this] {
try {
VLOG(10) << op << " " << op->Name() << " : " << op->DebugString();
- op->Run(use_event_);
+ op->Run(strategy_.use_event_);
VLOG(10) << op << " " << op->Name() << " Done ";
running_ops_--;
ready_var_q->Extend(op->Outputs());
diff --git a/paddle/fluid/framework/details/threaded_ssa_graph_executor.h b/paddle/fluid/framework/details/threaded_ssa_graph_executor.h
index f18a88526b..1f7f88d752 100644
--- a/paddle/fluid/framework/details/threaded_ssa_graph_executor.h
+++ b/paddle/fluid/framework/details/threaded_ssa_graph_executor.h
@@ -23,6 +23,7 @@
#include <functional>
#include "ThreadPool.h" // ThreadPool in thrird party
#include "paddle/fluid/framework/blocking_queue.h"
+#include "paddle/fluid/framework/details/execution_strategy.h"
#include "paddle/fluid/framework/details/fetch_op_handle.h"
#include "paddle/fluid/framework/details/ssa_graph_executor.h"
@@ -34,11 +35,10 @@ namespace details {
class ThreadedSSAGraphExecutor : public SSAGraphExecutor {
public:
- ThreadedSSAGraphExecutor(size_t num_threads, bool use_event,
+ ThreadedSSAGraphExecutor(const ExecutionStrategy &strategy,
const std::vector<Scope *> &local_scopes,
const std::vector<platform::Place> &places,
- std::unique_ptr<SSAGraph> &&graph,
- bool allow_op_delay);
+ std::unique_ptr<SSAGraph> &&graph);
// Run a SSAGraph by a thread pool
// Use topological sort algorithm
@@ -55,10 +55,8 @@ class ThreadedSSAGraphExecutor : public SSAGraphExecutor {
std::vector<Scope *> local_scopes_;
std::vector<platform::Place> places_;
platform::DeviceContextPool fetch_ctxs_;
- const bool use_event_;
std::unique_ptr<platform::EnforceNotMet> exception_;
std::atomic<int> running_ops_;
- bool allow_op_delay_;
void InsertPendingOp(std::unordered_map<OpHandleBase *, size_t> *pending_ops,
OpHandleBase *op_instance) const;
@@ -74,6 +72,9 @@ class ThreadedSSAGraphExecutor : public SSAGraphExecutor {
std::unordered_map<OpHandleBase *, size_t> *pending_ops,
std::unordered_set<VarHandleBase *> *pending_vars,
BlockingQueue<VarHandleBase *> *ready_vars, FeedFetchList *fetch_data);
+
+ private:
+ ExecutionStrategy strategy_;
};
} // namespace details
diff --git a/paddle/fluid/framework/parallel_executor.cc b/paddle/fluid/framework/parallel_executor.cc
index 20ef7e09f6..cdfd0a8c07 100644
--- a/paddle/fluid/framework/parallel_executor.cc
+++ b/paddle/fluid/framework/parallel_executor.cc
@@ -52,13 +52,13 @@ std::vector<Scope *> &ParallelExecutor::GetLocalScopes() {
}
ParallelExecutor::ParallelExecutor(
- size_t num_threads, bool use_event,
const std::vector<platform::Place> &places,
const std::unordered_set<std::string> ¶ms,
const std::unordered_set<std::string> &bcast_vars,
const ProgramDesc &main_program, const std::string &loss_var_name,
- Scope *scope, const std::vector<Scope *> &local_scopes, bool allow_op_delay,
- bool use_default_grad_scale, bool balance_parameter_opt_between_cards)
+ Scope *scope, const std::vector<Scope *> &local_scopes,
+ bool use_default_grad_scale, bool balance_parameter_opt_between_cards,
+ const ExecutionStrategy &exec_strategy)
: member_(new ParallelExecutorPrivate(places)) {
member_->global_scope_ = scope;
@@ -103,8 +103,7 @@ ParallelExecutor::ParallelExecutor(
auto graph = builder.Build(main_program);
member_->executor_.reset(new details::ThreadedSSAGraphExecutor(
- num_threads, use_event, member_->local_scopes_, places, std::move(graph),
- allow_op_delay));
+ exec_strategy, member_->local_scopes_, places, std::move(graph)));
// Step 3. Create vars in each scope;
for (auto *var : main_program.Block(0).AllVars()) {
diff --git a/paddle/fluid/framework/parallel_executor.h b/paddle/fluid/framework/parallel_executor.h
index b251fc9141..ab50509124 100644
--- a/paddle/fluid/framework/parallel_executor.h
+++ b/paddle/fluid/framework/parallel_executor.h
@@ -17,53 +17,55 @@ limitations under the License. */
#include <string>
#include <unordered_set>
#include <vector>
+#include "paddle/fluid/framework/details/execution_strategy.h"
#include "paddle/fluid/framework/executor.h"
#include "paddle/fluid/framework/op_info.h"
#include "paddle/fluid/framework/program_desc.h"
#include "paddle/fluid/framework/scope.h"
#include "paddle/fluid/framework/tensor.h"
#include "paddle/fluid/platform/device_context.h"
-
namespace paddle {
namespace framework {
class ParallelExecutorPrivate;
+using details::ExecutionStrategy;
+
class ParallelExecutor {
DISABLE_COPY_AND_ASSIGN(ParallelExecutor);
public:
- explicit ParallelExecutor(size_t num_threads, bool use_event,
- const std::vector<platform::Place>& places,
- const std::unordered_set<std::string>& params,
- const std::unordered_set<std::string>& bcast_vars,
- const ProgramDesc& main_program,
- const std::string& loss_var_name, Scope* scope,
- const std::vector<Scope*>& local_scopes,
- bool allow_op_delay, bool use_default_grad_scale,
- bool balance_parameter_opt_between_cards);
+ explicit ParallelExecutor(const std::vector<platform::Place> &places,
+ const std::unordered_set<std::string> ¶ms,
+ const std::unordered_set<std::string> &bcast_vars,
+ const ProgramDesc &main_program,
+ const std::string &loss_var_name, Scope *scope,
+ const std::vector<Scope *> &local_scopes,
+ bool use_default_grad_scale,
+ bool balance_parameter_opt_between_cards,
+ const ExecutionStrategy &exec_strategy);
~ParallelExecutor();
- std::vector<Scope*>& GetLocalScopes();
+ std::vector<Scope *> &GetLocalScopes();
/**
* Feed tensors to local scopes. The size of tensors should be equal to the
* size of local scopes.
*/
void FeedTensorsIntoLocalScopes(
- const std::vector<std::unordered_map<std::string, LoDTensor>>& tensors);
+ const std::vector<std::unordered_map<std::string, LoDTensor>> &tensors);
void FeedAndSplitTensorIntoLocalScopes(
- const std::unordered_map<std::string, LoDTensor>& tensors);
+ const std::unordered_map<std::string, LoDTensor> &tensors);
- void Run(const std::vector<std::string>& fetch_tensors,
- const std::string& fetched_var_name);
+ void Run(const std::vector<std::string> &fetch_tensors,
+ const std::string &fetched_var_name);
- void BCastParamsToGPUs(const std::unordered_set<std::string>& vars) const;
+ void BCastParamsToGPUs(const std::unordered_set<std::string> &vars) const;
private:
- ParallelExecutorPrivate* member_;
+ ParallelExecutorPrivate *member_;
};
} // namespace framework
diff --git a/paddle/fluid/pybind/pybind.cc b/paddle/fluid/pybind/pybind.cc
index 3e2eed31b4..c456bc1a71 100644
--- a/paddle/fluid/pybind/pybind.cc
+++ b/paddle/fluid/pybind/pybind.cc
@@ -494,22 +494,33 @@ All parameter, weight, gradient are variables in Paddle.
m.def("disable_profiler", platform::DisableProfiler);
m.def("reset_profiler", platform::ResetProfiler);
- py::class_<ParallelExecutor>(m, "ParallelExecutor")
- .def("__init__",
- [](ParallelExecutor &self, size_t num_threads, bool use_event,
- const std::vector<platform::Place> &places,
- const std::unordered_set<std::string> ¶ms,
- const std::unordered_set<std::string> &bcast_vars,
- const ProgramDesc &main_program, const std::string &loss_var_name,
- Scope *scope, std::vector<Scope *> &local_scopes,
- bool allow_op_delay, bool use_default_grad_scale,
- bool balance_parameter_opt_between_cards) {
- new (&self) ParallelExecutor(
- num_threads, use_event, places, params, bcast_vars,
- main_program, loss_var_name, scope, local_scopes,
- allow_op_delay, use_default_grad_scale,
- balance_parameter_opt_between_cards);
- })
+ py::class_<ParallelExecutor> pe(m, "ParallelExecutor");
+ py::class_<ExecutionStrategy>(pe, "ExecutionStrategy")
+ .def(py::init())
+ .def_property(
+ "num_threads",
+ [](const ExecutionStrategy &self) { return self.num_threads_; },
+ [](ExecutionStrategy &self, size_t num_threads) {
+ self.num_threads_ = num_threads;
+ })
+ .def_property(
+ "use_event",
+ [](const ExecutionStrategy &self) { return self.use_event_; },
+ [](ExecutionStrategy &self, bool use_event) {
+ self.use_event_ = use_event;
+ })
+ .def_property(
+ "allow_op_delay",
+ [](const ExecutionStrategy &self) { return self.allow_op_delay_; },
+ [](ExecutionStrategy &self, bool allow_op_delay) {
+ self.allow_op_delay_ = allow_op_delay;
+ });
+
+ pe.def(py::init<const std::vector<platform::Place> &,
+ const std::unordered_set<std::string> &,
+ const std::unordered_set<std::string> &, const ProgramDesc &,
+ const std::string &, Scope *, std::vector<Scope *> &, bool,
+ bool, const ExecutionStrategy &>())
.def("bcast_params", &ParallelExecutor::BCastParamsToGPUs)
// NOTE: even we return a vec<Scope*>* to Python use reference policy.
// We still cannot get local_scope from this vector, since the element
diff --git a/python/paddle/fluid/__init__.py b/python/paddle/fluid/__init__.py
index c8a435748d..ef7a586475 100644
--- a/python/paddle/fluid/__init__.py
+++ b/python/paddle/fluid/__init__.py
@@ -44,42 +44,44 @@ import transpiler
from param_attr import ParamAttr, WeightNormParamAttr
from data_feeder import DataFeeder
from core import LoDTensor, CPUPlace, CUDAPlace, CUDAPinnedPlace
-from transpiler import DistributeTranspiler, SimpleDistributeTranspiler, InferenceTranspiler, memory_optimize, release_memory
+from transpiler import DistributeTranspiler, SimpleDistributeTranspiler, \
+ InferenceTranspiler, memory_optimize, release_memory
from concurrency import (Go, make_channel, channel_send, channel_recv,
channel_close, Select)
import clip
import profiler
import unique_name
import recordio_writer
-from parallel_executor import ParallelExecutor
+from parallel_executor import ParallelExecutor, ExecutionStrategy
Tensor = LoDTensor
-__all__ = framework.__all__ + executor.__all__ + concurrency.__all__ +\
+__all__ = framework.__all__ + executor.__all__ + concurrency.__all__ + \
trainer.__all__ + inferencer.__all__ + transpiler.__all__ + [
- 'io',
- 'initializer',
- 'layers',
- 'transpiler'
- 'nets',
- 'optimizer',
- 'learning_rate_decay',
- 'backward',
- 'regularizer',
- 'LoDTensor',
- 'CPUPlace',
- 'CUDAPlace',
- 'CUDAPinnedPlace',
- 'Tensor',
- 'ParamAttr',
- 'WeightNormParamAttr',
- 'DataFeeder',
- 'clip',
- 'profiler',
- 'unique_name',
- 'recordio_writer',
- 'ParallelExecutor',
-]
+ 'io',
+ 'initializer',
+ 'layers',
+ 'transpiler'
+ 'nets',
+ 'optimizer',
+ 'learning_rate_decay',
+ 'backward',
+ 'regularizer',
+ 'LoDTensor',
+ 'CPUPlace',
+ 'CUDAPlace',
+ 'CUDAPinnedPlace',
+ 'Tensor',
+ 'ParamAttr',
+ 'WeightNormParamAttr',
+ 'DataFeeder',
+ 'clip',
+ 'profiler',
+ 'unique_name',
+ 'recordio_writer',
+ 'ParallelExecutor',
+ 'ExecutionStrategy',
+ ]
def __bootstrap__():
diff --git a/python/paddle/fluid/parallel_executor.py b/python/paddle/fluid/parallel_executor.py
index 5b43f860e7..69ea9ee335 100644
--- a/python/paddle/fluid/parallel_executor.py
+++ b/python/paddle/fluid/parallel_executor.py
@@ -19,7 +19,9 @@ import executor
import warnings
import sys
-__all__ = ['ParallelExecutor']
+__all__ = ['ParallelExecutor', 'ExecutionStrategy']
+
+ExecutionStrategy = core.ParallelExecutor.ExecutionStrategy
class ParallelExecutor(object):
@@ -27,11 +29,11 @@ class ParallelExecutor(object):
use_cuda,
loss_name=None,
main_program=None,
- num_threads=None,
- allow_op_delay=False,
share_vars_from=None,
use_default_grad_scale=True,
- balance_parameter_opt_between_cards=False):
+ balance_parameter_opt_between_cards=False,
+ exec_strategy=None,
+ **kwargs):
"""
ParallelExecutor can run program in parallel.
@@ -40,11 +42,6 @@ class ParallelExecutor(object):
loss_name(str, default None): The loss name must set in training.
main_program(Program, default None): The program that need to run,
if not provided, then default_main_program will be used.
- num_threads(int, default None): How many threads are used for
- training.
- allow_op_delay(bool, default False): Whether to delay and buffer
- some operators together for scheduling or not, which may
- improve performance in some cases, default False.
share_vars_from(ParallelExecutor, default None): If provied,
it will share variables from the specified ParallelExecutor.
use_default_grad_scale(bool, default True): If set True, a default
@@ -76,6 +73,16 @@ class ParallelExecutor(object):
train_loss, = train_exe.run([loss.name], feed=feed_dict)
test_loss, = test_exe.run([loss.name], feed=feed_dict)
"""
+ if len(kwargs) != 0:
+ err_msg = ""
+ for key in kwargs:
+ if key in dir(ExecutionStrategy):
+ err_msg += \
+ "Setting {0} by constructor is deprecated. Use " \
+ "strategy=ExecutionStrategy(); strategy.{0}=xxx; " \
+ "pe=ParallelExecutor(exec_strategy=strategy) " \
+ "instead.\n "
+ raise ValueError(err_msg)
self._places = []
self._act_places = []
@@ -93,13 +100,20 @@ class ParallelExecutor(object):
self._places.append(p)
assert self._places, "no place for execution"
- if num_threads is None:
+ if exec_strategy is None:
+ exec_strategy = ExecutionStrategy()
+ if use_cuda:
+ exec_strategy.use_event = True
+ else:
+ exec_strategy.use_event = False
+
+ if exec_strategy.num_threads == 0:
if use_cuda:
# Experiments on se-resnext shows that too many threads hurt
# performance. Worth tunning for other models in the future.
- num_threads = len(self._places) * 2
+ exec_strategy.num_threads = len(self._places) * 2
else:
- num_threads = min(
+ exec_strategy.num_threads = min(
len(self._places) * 2, multiprocessing.cpu_count())
main = main_program
@@ -120,21 +134,14 @@ class ParallelExecutor(object):
]
self.executor = core.ParallelExecutor(
- num_threads,
- True if use_cuda else False, # use_event
self._places,
set([
p.name for p in main.global_block().iter_parameters()
if not p.stop_gradient
]),
- set(self.persistable_vars),
- main.desc,
- loss_name if loss_name else '',
- scope,
- local_scopes,
- allow_op_delay,
- use_default_grad_scale,
- balance_parameter_opt_between_cards)
+ set(self.persistable_vars), main.desc, loss_name
+ if loss_name else '', scope, local_scopes, use_default_grad_scale,
+ balance_parameter_opt_between_cards, exec_strategy)
self.scope = scope
diff --git a/python/paddle/fluid/tests/unittests/test_parallel_executor.py b/python/paddle/fluid/tests/unittests/test_parallel_executor.py
index a3be1a8db6..4173ad1925 100644
--- a/python/paddle/fluid/tests/unittests/test_parallel_executor.py
+++ b/python/paddle/fluid/tests/unittests/test_parallel_executor.py
@@ -232,14 +232,14 @@ class TestParallelExecutorBase(unittest.TestCase):
place = fluid.CUDAPlace(0)
startup_exe = fluid.Executor(place)
startup_exe.run(startup)
-
+ exec_strategy = fluid.ExecutionStrategy()
+ exec_strategy.allow_op_delay = allow_op_delay
if use_parallel_executor:
exe = fluid.ParallelExecutor(
True,
loss_name=loss.name,
- allow_op_delay=allow_op_delay,
- balance_parameter_opt_between_cards=balance_parameter_opt_between_cards
- )
+ balance_parameter_opt_between_cards=balance_parameter_opt_between_cards,
+ exec_strategy=exec_strategy)
else:
exe = fluid.Executor(place=place)
From b9cc896545944f17238585c3f55f14a1f6972fbd Mon Sep 17 00:00:00 2001
From: yuyang18 <reyoung@126.com>
Date: Mon, 14 May 2018 13:29:47 +0800
Subject: [PATCH 084/195] Add includes
---
paddle/fluid/framework/data_type.cc | 4 ++++
1 file changed, 4 insertions(+)
diff --git a/paddle/fluid/framework/data_type.cc b/paddle/fluid/framework/data_type.cc
index 9e5f255891..28bbf82bc8 100644
--- a/paddle/fluid/framework/data_type.cc
+++ b/paddle/fluid/framework/data_type.cc
@@ -13,6 +13,10 @@
// limitations under the License.
#include "paddle/fluid/framework/data_type.h"
+#include <stdint.h>
+#include <mutex> // NOLINT
+#include <string>
+#include <unordered_map>
namespace paddle {
namespace framework {
From 7b0c0273f4a5d0dc7a65248a1c2cb7a8ebf49909 Mon Sep 17 00:00:00 2001
From: typhoonzero <typhoonzero1986@gmail.com>
Date: Mon, 14 May 2018 14:05:30 +0800
Subject: [PATCH 085/195] update by comments
---
paddle/fluid/framework/parallel_executor.h | 2 +-
paddle/fluid/operators/gen_nccl_id_op.cc | 24 +++++++++++-----------
paddle/fluid/platform/nccl_helper.h | 4 ++--
python/paddle/fluid/parallel_executor.py | 4 ++--
4 files changed, 17 insertions(+), 17 deletions(-)
diff --git a/paddle/fluid/framework/parallel_executor.h b/paddle/fluid/framework/parallel_executor.h
index 7ab17de389..9e279876cf 100644
--- a/paddle/fluid/framework/parallel_executor.h
+++ b/paddle/fluid/framework/parallel_executor.h
@@ -42,7 +42,7 @@ class ParallelExecutor {
const std::vector<Scope*>& local_scopes,
bool allow_op_delay, bool use_default_grad_scale,
bool balance_parameter_opt_between_cards,
- size_t num_trainers = 0, size_t trainer_id = 0);
+ size_t num_trainers = 1, size_t trainer_id = 0);
~ParallelExecutor();
diff --git a/paddle/fluid/operators/gen_nccl_id_op.cc b/paddle/fluid/operators/gen_nccl_id_op.cc
index b4ff6b7598..36fc862213 100644
--- a/paddle/fluid/operators/gen_nccl_id_op.cc
+++ b/paddle/fluid/operators/gen_nccl_id_op.cc
@@ -75,29 +75,29 @@ class GenNCCLIdOp : public framework::OperatorBase {
// NOTE: Can not use unique_ptr here because the default
// deleter will call GRPC Server's base class's dtor and
// that will cause a wired crash.
- rpc_service_ = new detail::AsyncGRPCServer(endpoint, true);
+
+ detail::AsyncGRPCServer rpc_service(endpoint, true);
framework::ProgramDesc empty_program;
framework::Executor executor(dev_ctx.GetPlace());
- rpc_service_->SetScope(scope);
- rpc_service_->SetDevCtx(&dev_ctx);
- rpc_service_->SetProgram(&empty_program);
- rpc_service_->SetExecutor(&executor);
+ rpc_service.SetScope(scope);
+ rpc_service.SetDevCtx(&dev_ctx);
+ rpc_service.SetProgram(&empty_program);
+ rpc_service.SetExecutor(&executor);
std::thread server_thread(
- std::bind(&detail::AsyncGRPCServer::RunSyncUpdate, rpc_service_));
- rpc_service_->SetCond(0);
+ std::bind(&detail::AsyncGRPCServer::RunSyncUpdate, &rpc_service));
+ rpc_service.SetCond(0);
VLOG(3) << "start getting nccl id from trainer 0...";
- auto recv = rpc_service_->Get();
+ auto recv = rpc_service.Get();
VLOG(3) << "got nccl id and stop server...";
- rpc_service_->ShutDown();
+ rpc_service.ShutDown();
VLOG(3) << "rpc server stopped";
// TODO(wuyi): reinit nccl communicators
server_thread.join();
- delete rpc_service_;
}
- protected:
- mutable detail::AsyncGRPCServer* rpc_service_ = nullptr;
+ // protected:
+ // mutable detail::AsyncGRPCServer* rpc_service_ = nullptr;
};
class GenNCCLIdOpMaker : public framework::OpProtoAndCheckerMaker {
diff --git a/paddle/fluid/platform/nccl_helper.h b/paddle/fluid/platform/nccl_helper.h
index 408721be8b..e30c1a9ebf 100644
--- a/paddle/fluid/platform/nccl_helper.h
+++ b/paddle/fluid/platform/nccl_helper.h
@@ -78,7 +78,7 @@ struct NCCLContextMap {
explicit NCCLContextMap(const std::vector<platform::Place> &places,
ncclUniqueId *nccl_id = nullptr,
- size_t num_trainers = 0, size_t trainer_id = 0) {
+ size_t num_trainers = 1, size_t trainer_id = 0) {
PADDLE_ENFORCE(!places.empty());
order_.reserve(places.size());
for (auto &p : places) {
@@ -100,7 +100,7 @@ struct NCCLContextMap {
PADDLE_ENFORCE(platform::dynload::ncclCommInitAll(
comms.get(), static_cast<int>(order_.size()), order_.data()));
} else {
- PADDLE_ENFORCE_GT(num_trainers, 0);
+ PADDLE_ENFORCE_GT(num_trainers, 1);
// TODO(wuyi): need to ensure each node have same number of GPUs
{
int nranks = num_trainers * order_.size();
diff --git a/python/paddle/fluid/parallel_executor.py b/python/paddle/fluid/parallel_executor.py
index 59294d9721..7358c4b60e 100644
--- a/python/paddle/fluid/parallel_executor.py
+++ b/python/paddle/fluid/parallel_executor.py
@@ -32,7 +32,7 @@ class ParallelExecutor(object):
share_vars_from=None,
use_default_grad_scale=True,
balance_parameter_opt_between_cards=False,
- num_trainers=0,
+ num_trainers=1,
trainer_id=0):
"""
ParallelExecutor can run program in parallel.
@@ -57,7 +57,7 @@ class ParallelExecutor(object):
balance_parameter_opt_between_cards(bool, default True): Whether
updating different gradients on different cards. Currently, it
is not recommended.
- num_trainers(int, default 0): If greater than 0, NCCL will be
+ num_trainers(int, default 1): If greater than 1, NCCL will be
initialized with multpile rank of nodes, each node should have
same number of GPUs. Distributed training will be enabled then.
trainer_id(int, default 0): Must use together with num_trainers.
From 2a0205a5d9ae65a1251ecd7fc7d65cbdc9a60839 Mon Sep 17 00:00:00 2001
From: yuyang18 <reyoung@126.com>
Date: Mon, 14 May 2018 14:19:29 +0800
Subject: [PATCH 086/195] Draft for train by parallel executor
---
.../test_recognize_digits_conv.py | 7 ++-
python/paddle/fluid/trainer.py | 63 ++++++++++++++-----
2 files changed, 51 insertions(+), 19 deletions(-)
diff --git a/python/paddle/fluid/tests/book/high-level-api/recognize_digits/test_recognize_digits_conv.py b/python/paddle/fluid/tests/book/high-level-api/recognize_digits/test_recognize_digits_conv.py
index 1f91f471f2..159eec9487 100644
--- a/python/paddle/fluid/tests/book/high-level-api/recognize_digits/test_recognize_digits_conv.py
+++ b/python/paddle/fluid/tests/book/high-level-api/recognize_digits/test_recognize_digits_conv.py
@@ -66,7 +66,8 @@ def train(use_cuda, save_dirname):
train_func=train_program,
infer_func=inference_program,
place=place,
- optimizer=optimizer)
+ optimizer=optimizer,
+ parallel=True)
def event_handler(event):
if isinstance(event, fluid.EndEpochEvent):
@@ -95,6 +96,8 @@ def train(use_cuda, save_dirname):
# event.epoch + 1, float(avg_cost), float(acc)))
# if math.isnan(float(avg_cost)):
# sys.exit("got NaN loss, training failed.")
+ elif isinstance(event, fluid.EndStepEvent):
+ print("Step {0}, Epoch {1}".format(event.step, event.epoch))
train_reader = paddle.batch(
paddle.reader.shuffle(
@@ -132,4 +135,4 @@ def main(use_cuda):
if __name__ == '__main__':
# for use_cuda in (False, True):
- main(use_cuda=False)
+ main(use_cuda=True)
diff --git a/python/paddle/fluid/trainer.py b/python/paddle/fluid/trainer.py
index 67d8be82d5..8dd140a92c 100644
--- a/python/paddle/fluid/trainer.py
+++ b/python/paddle/fluid/trainer.py
@@ -20,6 +20,7 @@ import data_feeder
import contextlib
import io
import unique_name
+import parallel_executor
# optimizer is same as the parameter of Trainer.__init__. Rename it to opt_module
import optimizer as opt_module
@@ -97,7 +98,9 @@ class Trainer(object):
infer_func,
optimizer,
param_path=None,
- place=None):
+ place=None,
+ parallel=False):
+ self.parallel = parallel
# 1. we need to generate a framework.Program by calling
# program_func. Reference: fluid.program_guard in
# test_word2vec.py
@@ -112,14 +115,14 @@ class Trainer(object):
with framework.program_guard(self.train_program, self.startup_program):
program_func_outs = train_func()
- self.test_outputs = program_func_outs if isinstance(
+ self.train_func_outputs = program_func_outs if isinstance(
program_func_outs, list) else [program_func_outs]
self.test_program = self.train_program.clone()
if not isinstance(optimizer, opt_module.Optimizer):
raise TypeError(
"The optimizer should be an instance of Optimizer")
# The fisrt element of program_func_outs is loss.
- loss = self.test_outputs[0]
+ loss = self.train_func_outputs[0]
optimize_ops, params_grads = optimizer.minimize(loss)
self.place = check_and_get_place(place)
@@ -175,12 +178,7 @@ class Trainer(object):
'TRAINING_ROLE environment variable must be either TRAINER or PSERVER'
)
- def train(self,
- num_epochs,
- event_handler,
- reader=None,
- parallel=False,
- feed_order=None):
+ def train(self, num_epochs, event_handler, reader=None, feed_order=None):
"""
Train the model.
@@ -188,25 +186,24 @@ class Trainer(object):
num_epochs: The number of epoch. An epoch will process all data in reader
event_handler: The event handler. A function with type (ev:Event)->void
reader:
- parallel: True if use multi-CPUs or multi-GPUs
feed_order: Feeding order of reader. None will following the defining
order in program
Returns:
"""
- if parallel:
- raise NotImplementedError(
- "Parallel Executor version of trainer is not implemented")
-
training_role = os.getenv("PADDLE_TRAINING_ROLE", "")
if training_role == "PSERVER":
with self._prog_and_scope_guard():
exe = executor.Executor(self.place)
exe.run()
return
-
- self._train_by_executor(num_epochs, event_handler, reader, feed_order)
+ if self.parallel:
+ self._train_by_parallel_executor(num_epochs, event_handler, reader,
+ feed_order)
+ else:
+ self._train_by_executor(num_epochs, event_handler, reader,
+ feed_order)
def test(self, reader, feed_order=None):
"""
@@ -218,7 +215,8 @@ class Trainer(object):
order in program
"""
- return self._test_by_executor(reader, feed_order, self.test_outputs)
+ return self._test_by_executor(reader, feed_order,
+ self.train_func_outputs)
def save_params(self, param_path):
# reference: save_persistables in io.py
@@ -286,6 +284,37 @@ class Trainer(object):
return [x / count for x in accumulated]
+ def _train_by_parallel_executor(self, num_epochs, event_handler, reader,
+ feed_order):
+ with self._prog_and_scope_guard():
+ pe = self._get_or_create_parallel_executor()
+ feed_var_list = build_feed_var_list(self.train_program, feed_order)
+ feeder = data_feeder.DataFeeder(
+ feed_list=feed_var_list, place=self.place)
+ reader = feeder.decorate_reader(reader, multi_devices=True)
+ for epoch_id in range(num_epochs):
+ event_handler(BeginEpochEvent(epoch_id=epoch_id))
+ for step_id, data in enumerate(reader()):
+ event_handler(
+ BeginStepEvent(
+ epoch_id=epoch_id, step_id=step_id))
+ pe.run(feed=data, fetch_list=[])
+ event_handler(
+ EndStepEvent(
+ epoch_id=epoch_id, step_id=step_id))
+
+ event_handler(EndEpochEvent(epoch_id=epoch_id))
+
+ def _get_parallel_executor(self):
+ return getattr(self, 'parallel_executor', None)
+
+ def _get_or_create_parallel_executor(self):
+ if self._get_parallel_executor() is None:
+ self.parallel_executor = parallel_executor.ParallelExecutor(
+ use_cuda=isinstance(self.place, core.CUDAPlace),
+ loss_name=self.train_func_outputs[0].name)
+ return self._get_parallel_executor()
+
def build_feed_var_list(program, feed_order):
if not isinstance(program, framework.Program):
From 715c933d887e7c16e66e76ecc884433fff2921a4 Mon Sep 17 00:00:00 2001
From: yuyang18 <reyoung@126.com>
Date: Mon, 14 May 2018 15:23:14 +0800
Subject: [PATCH 087/195] Change deps
---
paddle/fluid/framework/CMakeLists.txt | 6 +++---
1 file changed, 3 insertions(+), 3 deletions(-)
diff --git a/paddle/fluid/framework/CMakeLists.txt b/paddle/fluid/framework/CMakeLists.txt
index 384f084dde..ed1e70c646 100644
--- a/paddle/fluid/framework/CMakeLists.txt
+++ b/paddle/fluid/framework/CMakeLists.txt
@@ -5,11 +5,11 @@ proto_library(framework_proto SRCS framework.proto)
cc_library(ddim SRCS ddim.cc DEPS eigen3 boost)
cc_test(ddim_test SRCS ddim_test.cc DEPS ddim)
nv_test(dim_test SRCS dim_test.cu DEPS ddim)
-cc_library(data_type SRCS data_type.cc DEPS framework_proto ddim)
+cc_library(data_type SRCS data_type.cc DEPS framework_proto ddim device_context)
if(WITH_GPU)
- nv_library(tensor SRCS tensor.cc tensor_util.cu DEPS place memory device_context data_type)
+ nv_library(tensor SRCS tensor.cc tensor_util.cu DEPS place memory data_type)
else()
- cc_library(tensor SRCS tensor.cc tensor_util.cc DEPS place memory device_context data_type)
+ cc_library(tensor SRCS tensor.cc tensor_util.cc DEPS place memory data_type)
endif()
cc_test(tensor_test SRCS tensor_test.cc DEPS tensor)
From c4ad0dd08400d89f2a86adfb2fc0218bc129a997 Mon Sep 17 00:00:00 2001
From: yuyang18 <reyoung@126.com>
Date: Mon, 14 May 2018 15:37:10 +0800
Subject: [PATCH 088/195] Add fetch metrics
---
.../test_recognize_digits_conv.py | 3 +-
python/paddle/fluid/trainer.py | 43 +++++++++++--------
2 files changed, 26 insertions(+), 20 deletions(-)
diff --git a/python/paddle/fluid/tests/book/high-level-api/recognize_digits/test_recognize_digits_conv.py b/python/paddle/fluid/tests/book/high-level-api/recognize_digits/test_recognize_digits_conv.py
index 159eec9487..b86f5eee7b 100644
--- a/python/paddle/fluid/tests/book/high-level-api/recognize_digits/test_recognize_digits_conv.py
+++ b/python/paddle/fluid/tests/book/high-level-api/recognize_digits/test_recognize_digits_conv.py
@@ -97,7 +97,8 @@ def train(use_cuda, save_dirname):
# if math.isnan(float(avg_cost)):
# sys.exit("got NaN loss, training failed.")
elif isinstance(event, fluid.EndStepEvent):
- print("Step {0}, Epoch {1}".format(event.step, event.epoch))
+ print("Step {0}, Epoch {1} Metrics {2}".format(
+ event.step, event.epoch, map(numpy.array, event.metrics)))
train_reader = paddle.batch(
paddle.reader.shuffle(
diff --git a/python/paddle/fluid/trainer.py b/python/paddle/fluid/trainer.py
index 8dd140a92c..544856794b 100644
--- a/python/paddle/fluid/trainer.py
+++ b/python/paddle/fluid/trainer.py
@@ -49,12 +49,14 @@ class BeginStepEvent(object):
def __init__(self, epoch_id, step_id):
self.epoch = epoch_id
self.step = step_id
+ self.fetch_metrics = True
class EndStepEvent(object):
- def __init__(self, epoch_id, step_id):
+ def __init__(self, epoch_id, step_id, metrics):
self.epoch = epoch_id
self.step = step_id
+ self.metrics = metrics
def check_and_get_place(place):
@@ -259,13 +261,25 @@ class Trainer(object):
feeder = data_feeder.DataFeeder(
feed_list=feed_var_list, place=self.place)
exe = executor.Executor(self.place)
- for epoch_id in range(num_epochs):
- event_handler(BeginEpochEvent(epoch_id))
- for step_id, data in enumerate(reader()):
- event_handler(BeginStepEvent(epoch_id, step_id))
- exe.run(feed=feeder.feed(data), fetch_list=[])
- event_handler(EndStepEvent(epoch_id, step_id))
- event_handler(EndEpochEvent(epoch_id))
+ reader = feeder.decorate_reader(reader, multi_devices=False)
+ self._train_by_any_executor(event_handler, exe, num_epochs, reader)
+
+ def _train_by_any_executor(self, event_handler, exe, num_epochs, reader):
+ for epoch_id in range(num_epochs):
+ event_handler(BeginEpochEvent(epoch_id))
+ for step_id, data in enumerate(reader()):
+ begin_event = BeginStepEvent(epoch_id, step_id)
+ event_handler(begin_event)
+ if begin_event.fetch_metrics:
+ metrics = exe.run(feed=data,
+ fetch_list=[
+ var.name
+ for var in self.train_func_outputs
+ ])
+ else:
+ metrics = exe.run(feed=data, fetch_list=[])
+ event_handler(EndStepEvent(epoch_id, step_id, metrics))
+ event_handler(EndEpochEvent(epoch_id))
def _test_by_executor(self, reader, feed_order, fetch_list):
with executor.scope_guard(self.scope):
@@ -293,17 +307,8 @@ class Trainer(object):
feed_list=feed_var_list, place=self.place)
reader = feeder.decorate_reader(reader, multi_devices=True)
for epoch_id in range(num_epochs):
- event_handler(BeginEpochEvent(epoch_id=epoch_id))
- for step_id, data in enumerate(reader()):
- event_handler(
- BeginStepEvent(
- epoch_id=epoch_id, step_id=step_id))
- pe.run(feed=data, fetch_list=[])
- event_handler(
- EndStepEvent(
- epoch_id=epoch_id, step_id=step_id))
-
- event_handler(EndEpochEvent(epoch_id=epoch_id))
+ self._train_by_any_executor(event_handler, pe, num_epochs,
+ reader)
def _get_parallel_executor(self):
return getattr(self, 'parallel_executor', None)
From c0a6237d1a4c3b73be6ac39db3f4755747805ec6 Mon Sep 17 00:00:00 2001
From: dzhwinter <dzhwinter@gmail.com>
Date: Mon, 14 May 2018 00:45:09 -0700
Subject: [PATCH 089/195] "fix ci"
---
.../tests/unittests/test_network_with_dtype.py | 17 ++++++++++-------
1 file changed, 10 insertions(+), 7 deletions(-)
diff --git a/python/paddle/fluid/tests/unittests/test_network_with_dtype.py b/python/paddle/fluid/tests/unittests/test_network_with_dtype.py
index af487919a9..fe8aceb3ae 100644
--- a/python/paddle/fluid/tests/unittests/test_network_with_dtype.py
+++ b/python/paddle/fluid/tests/unittests/test_network_with_dtype.py
@@ -27,12 +27,15 @@ class TestNetWithDtype(unittest.TestCase):
def set_network(self):
self.dtype = "float64"
self.init_dtype()
- self.x = fluid.layers.data(name='x', shape=[13], dtype=self.dtype)
- self.y = fluid.layers.data(name='y', shape=[1], dtype=self.dtype)
- y_predict = fluid.layers.fc(input=self.x, size=1, act=None)
+ main = fluid.Program()
+ with fluid.program_guard(main):
+ self.x = fluid.layers.data(name='x', shape=[13], dtype=self.dtype)
+ self.y = fluid.layers.data(name='y', shape=[1], dtype=self.dtype)
+ y_predict = fluid.layers.fc(input=self.x, size=1, act=None)
- cost = fluid.layers.square_error_cost(input=y_predict, label=self.y)
- avg_cost = fluid.layers.mean(cost)
+ cost = fluid.layers.square_error_cost(input=y_predict, label=self.y)
+ avg_cost = fluid.layers.mean(cost)
+ self.program = main
self.fetch_list = [avg_cost]
sgd_optimizer = fluid.optimizer.SGD(learning_rate=0.001)
@@ -45,7 +48,7 @@ class TestNetWithDtype(unittest.TestCase):
exe = fluid.Executor(place)
exe.run(fluid.default_startup_program())
for data in train_reader():
- exe.run(fluid.default_main_program(),
+ exe.run(self.program,
feed=feeder.feed(data),
fetch_list=self.fetch_list)
# the main program is runable, the datatype is fully supported
@@ -68,7 +71,7 @@ class TestNetWithDtype(unittest.TestCase):
# TODO(dzhwinter): make sure the fp16 is runable
-# class TestFloat16(SimpleNet):
+# class TestFloat16(TestNetWithDtype):
# def init_dtype(self):
# self.dtype = "float16"
From 373a2e66eb339f7b6d1bd9ef292ce1b693126ff5 Mon Sep 17 00:00:00 2001
From: typhoonzero <typhoonzero1986@gmail.com>
Date: Mon, 14 May 2018 15:47:11 +0800
Subject: [PATCH 090/195] remove comments
---
paddle/fluid/operators/gen_nccl_id_op.cc | 4 ----
1 file changed, 4 deletions(-)
diff --git a/paddle/fluid/operators/gen_nccl_id_op.cc b/paddle/fluid/operators/gen_nccl_id_op.cc
index 36fc862213..804d43e4cd 100644
--- a/paddle/fluid/operators/gen_nccl_id_op.cc
+++ b/paddle/fluid/operators/gen_nccl_id_op.cc
@@ -92,12 +92,8 @@ class GenNCCLIdOp : public framework::OperatorBase {
VLOG(3) << "got nccl id and stop server...";
rpc_service.ShutDown();
VLOG(3) << "rpc server stopped";
- // TODO(wuyi): reinit nccl communicators
server_thread.join();
}
-
- // protected:
- // mutable detail::AsyncGRPCServer* rpc_service_ = nullptr;
};
class GenNCCLIdOpMaker : public framework::OpProtoAndCheckerMaker {
From 872e55bce5e51e466844367dc1f552d9031eef38 Mon Sep 17 00:00:00 2001
From: typhoonzero <typhoonzero1986@gmail.com>
Date: Mon, 14 May 2018 15:47:39 +0800
Subject: [PATCH 091/195] remove comments
---
paddle/fluid/operators/gen_nccl_id_op.cc | 1 -
1 file changed, 1 deletion(-)
diff --git a/paddle/fluid/operators/gen_nccl_id_op.cc b/paddle/fluid/operators/gen_nccl_id_op.cc
index 804d43e4cd..a5678f6346 100644
--- a/paddle/fluid/operators/gen_nccl_id_op.cc
+++ b/paddle/fluid/operators/gen_nccl_id_op.cc
@@ -75,7 +75,6 @@ class GenNCCLIdOp : public framework::OperatorBase {
// NOTE: Can not use unique_ptr here because the default
// deleter will call GRPC Server's base class's dtor and
// that will cause a wired crash.
-
detail::AsyncGRPCServer rpc_service(endpoint, true);
framework::ProgramDesc empty_program;
framework::Executor executor(dev_ctx.GetPlace());
From b3e5a88450e37880ed8a56b602ab4cf63d8c1b37 Mon Sep 17 00:00:00 2001
From: Wu Yi <typhoonzero1986@gmail.com>
Date: Mon, 14 May 2018 16:15:31 +0800
Subject: [PATCH 092/195] Patch mkldnn for build on gcc 4.8.2 (#10616)
* test_patch_mkldnn
* use patch file
* follow comments
* fix patch
---
cmake/external/mkldnn.cmake | 2 +
patches/mkldnn.hpp | 4252 +++++++++++++++++++++++++++++++++++
2 files changed, 4254 insertions(+)
create mode 100644 patches/mkldnn.hpp
diff --git a/cmake/external/mkldnn.cmake b/cmake/external/mkldnn.cmake
index 966c0bafd3..0332e39d14 100644
--- a/cmake/external/mkldnn.cmake
+++ b/cmake/external/mkldnn.cmake
@@ -56,6 +56,8 @@ ExternalProject_Add(
GIT_TAG "v0.14"
PREFIX ${MKLDNN_SOURCES_DIR}
UPDATE_COMMAND ""
+ # Patch MKLDNN to compile with gcc 4.8, the related issue is in intel/mkl-dnn#237.
+ PATCH_COMMAND ${CMAKE_COMMAND} -E copy_if_different ${CMAKE_CURRENT_SOURCE_DIR}/patches/mkldnn.hpp ${MKLDNN_SOURCES_DIR}/src/extern_mkldnn/include/mkldnn.hpp
CMAKE_ARGS -DCMAKE_INSTALL_PREFIX=${MKLDNN_INSTALL_DIR}
CMAKE_ARGS -DCMAKE_BUILD_TYPE=${CMAKE_BUILD_TYPE}
CMAKE_ARGS -DMKLROOT=${MKLML_ROOT}
diff --git a/patches/mkldnn.hpp b/patches/mkldnn.hpp
new file mode 100644
index 0000000000..fe01ad8a10
--- /dev/null
+++ b/patches/mkldnn.hpp
@@ -0,0 +1,4252 @@
+// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+// http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+/*******************************************************************************
+* Copyright 2016-2018 Intel Corporation
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+* http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*******************************************************************************/
+
+#ifndef MKLDNN_HPP
+#define MKLDNN_HPP
+
+#ifndef DOXYGEN_SHOULD_SKIP_THIS
+#include <stdlib.h>
+#include <algorithm>
+#include <iterator>
+#include <memory>
+#include <string>
+#include <vector>
+
+#include "mkldnn.h"
+#endif
+
+namespace mkldnn {
+
+/// @addtogroup cpp_api C++ API
+/// @{
+
+/// @addtogroup cpp_api_utils Utils
+/// @{
+
+/// A class that provides the destructor for an Intel(R) MKL-DNN C handle
+template <typename T>
+class handle_traits {};
+
+/// A class for wrapping an Intel(R) MKL-DNN handle. It is used as the base
+/// class for primitive (#mkldnn_primitive_t), engine (#mkldnn_engine_t), and
+/// stream (#mkldnn_stream_t) handles. An object of the #mkldnn::handle class
+/// can be passed by value. This class enables wrapping:
+/// - Newly constructed handles.
+/// @n In this case, the constructed handle uses reference counting provided
+/// by @p std::shared_ptr with a proper deleter function specified through
+/// the @p handle_traits class.
+/// - Pre-existing handles returned by the Intel(R) MKL-DNN C API (for
+/// example, through #mkldnn_primitive_get_output()).
+/// @n In this case, an Intel(R) MKL-DNN C API handle is wrapped without a
+/// deleter because it is assumed that the handle wrapper for the original
+/// object deletes the handle (this model is similar to @p std::weak_ptr).
+template <typename T, typename traits = handle_traits<T>>
+class handle {
+private:
+ std::shared_ptr<typename std::remove_pointer<T>::type> _data;
+ handle(const handle &&) = delete;
+ handle &operator=(const handle &&other) = delete;
+
+protected:
+ /// Constructs a C handle wrapper.
+ /// @param t The C handle to wrap.
+ /// @param weak A flag to specify whether to construct a weak wrapper.
+ handle(T t = 0, bool weak = false) : _data(0) { reset(t, weak); }
+
+ bool operator==(const T other) const { return other == _data.get(); }
+ bool operator!=(const T other) const { return !(*this == other); }
+
+public:
+ handle(const handle &other) : _data(other._data) {}
+ handle &operator=(const handle &other) {
+ _data = other._data;
+ return *this;
+ }
+ /// Resets the value of a C handle.
+ /// @param t The new value of the C handle.
+ /// @param weak A flag to specify whether the wrapper should be weak.
+ void reset(T t, bool weak = false) {
+ auto dummy_destructor = [](T) {
+ return decltype(traits::destructor(0))(0);
+ };
+ _data.reset(t, weak ? dummy_destructor : traits::destructor);
+ }
+
+ /// Returns the value of the underlying C handle.
+ T get() const { return _data.get(); }
+
+ bool operator==(const handle &other) const {
+ return other._data.get() == _data.get();
+ }
+ bool operator!=(const handle &other) const { return !(*this == other); }
+};
+
+#ifndef DOXYGEN_SHOULD_SKIP_THIS
+template <>
+struct handle_traits<mkldnn_primitive_desc_t> {
+ static constexpr auto destructor = &mkldnn_primitive_desc_destroy;
+};
+
+template <>
+struct handle_traits<mkldnn_primitive_t> {
+ static constexpr auto destructor = &mkldnn_primitive_destroy;
+};
+#endif
+
+/// Base class for all computational primitives.
+class primitive : public handle<mkldnn_primitive_t> {
+ friend struct error;
+ friend struct stream;
+ friend class primitive_at;
+ using handle::handle;
+
+public:
+ /// A proxy to C primitive kind enum
+ enum class kind {
+ undefined_primitive = mkldnn_undefined_primitive,
+ memory = mkldnn_memory,
+ view = mkldnn_view,
+ reorder = mkldnn_reorder,
+ concat = mkldnn_concat,
+ concat_inplace = mkldnn_concat_inplace,
+ sum = mkldnn_sum,
+ convolution = mkldnn_convolution,
+ deconvolution = mkldnn_deconvolution,
+ eltwise = mkldnn_eltwise,
+ relu = mkldnn_relu,
+ softmax = mkldnn_softmax,
+ pooling = mkldnn_pooling,
+ lrn = mkldnn_lrn,
+ batch_normalization = mkldnn_batch_normalization,
+ inner_product = mkldnn_inner_product,
+ convolution_relu = mkldnn_convolution_relu,
+ rnn = mkldnn_rnn,
+ };
+
+ /// A wrapper structure to specify a particular output of a primitive.
+ struct at {
+ /// The underlying C API structure.
+ mkldnn_primitive_at_t data;
+ /// Constructs a wrapper specifying @p aprimitive output with index @p
+ /// at.
+ ///
+ /// @param aprimitive The target primitive.
+ /// @param at The output index.
+
+ at(const primitive &aprimitive, size_t at = 0)
+ : data(mkldnn_primitive_at(aprimitive.get(), at)) {}
+ /// Returns the specified output.
+ inline operator primitive() const;
+ };
+
+ /// Returns the descriptor of the underlying C API primitive
+ inline const_mkldnn_primitive_desc_t get_primitive_desc() const;
+ // TODO: use the C++ API wrapper structure.
+};
+
+inline mkldnn_primitive_kind_t convert_to_c(primitive::kind akind) {
+ return static_cast<mkldnn_primitive_kind_t>(akind);
+}
+
+/// Intel(R) MKL-DNN exception class.
+///
+/// This class captures the status returned by the failed C API function, error
+/// message, and, optionally, handle of the primitive that caused the error.
+struct error : public std::exception {
+ mkldnn_status_t status;
+ std::string message;
+ primitive error_primitive;
+
+ /// Constructs an error instance.
+ ///
+ /// @param astatus The error status returned by the C API.
+ /// @param amessage The error message.
+ /// @param aerror_primitive (optional) A C handle of the primitive that
+ /// caused the error.
+
+ error(mkldnn_status_t astatus,
+ std::string amessage,
+ mkldnn_primitive_t aerror_primitive = 0)
+ : status(astatus),
+ message(amessage),
+ error_primitive(aerror_primitive, true) {}
+
+ /// A convenience function for wrapping calls to the C API. Checks the
+ /// return status and throws an #error in case of failure.
+ ///
+ /// @param status The error status returned by the C API.
+ /// @param message The error message.
+ /// @param error_primitive (optional) A C handle of the primitive that
+ /// caused the error.
+
+ static void wrap_c_api(mkldnn_status_t status,
+ std::string message,
+ mkldnn_primitive_t *error_primitive = 0) {
+ if (status != mkldnn_success) {
+ if (nullptr != error_primitive)
+ throw error(status, message, *error_primitive);
+ else
+ throw error(status, message, nullptr);
+ }
+ }
+};
+
+inline primitive::at::operator primitive() const {
+ const_mkldnn_primitive_t output;
+ error::wrap_c_api(
+ mkldnn_primitive_get_output(data.primitive, data.output_index, &output),
+ "could not get an output primitive");
+ return primitive(const_cast<mkldnn_primitive_t>(output), true);
+}
+
+const_mkldnn_primitive_desc_t primitive::get_primitive_desc() const {
+ const_mkldnn_primitive_desc_t pd;
+ error::wrap_c_api(mkldnn_primitive_get_primitive_desc(get(), &pd),
+ "could not get primitive descriptor by primitive");
+ return pd;
+}
+/// @}
+
+/// @addtogroup cpp_api_enums Common data types and enumerations
+/// @{
+
+enum round_mode {
+ round_nearest = mkldnn_round_nearest,
+ round_down = mkldnn_round_down,
+};
+
+inline mkldnn_round_mode_t convert_to_c(round_mode mode) {
+ return static_cast<mkldnn_round_mode_t>(mode);
+}
+
+enum padding_kind { zero = mkldnn_padding_zero };
+
+inline mkldnn_padding_kind_t convert_to_c(padding_kind kind) {
+ return static_cast<mkldnn_padding_kind_t>(kind);
+}
+
+enum prop_kind {
+ forward_training = mkldnn_forward_training,
+ forward_scoring = mkldnn_forward_scoring,
+ forward_inference = mkldnn_forward_inference,
+ forward = mkldnn_forward,
+ backward = mkldnn_backward,
+ backward_data = mkldnn_backward_data,
+ backward_weights = mkldnn_backward_weights,
+ backward_bias = mkldnn_backward_bias
+};
+
+inline mkldnn_prop_kind_t convert_to_c(prop_kind kind) {
+ return static_cast<mkldnn_prop_kind_t>(kind);
+}
+
+enum algorithm {
+ algorithm_undef = mkldnn_alg_kind_undef,
+ convolution_direct = mkldnn_convolution_direct,
+ convolution_winograd = mkldnn_convolution_winograd,
+ deconvolution_direct = mkldnn_deconvolution_direct,
+ deconvolution_winograd = mkldnn_deconvolution_winograd,
+ eltwise_relu = mkldnn_eltwise_relu,
+ eltwise_tanh = mkldnn_eltwise_tanh,
+ eltwise_elu = mkldnn_eltwise_elu,
+ eltwise_square = mkldnn_eltwise_square,
+ eltwise_abs = mkldnn_eltwise_abs,
+ eltwise_sqrt = mkldnn_eltwise_sqrt,
+ eltwise_linear = mkldnn_eltwise_linear,
+ eltwise_bounded_relu = mkldnn_eltwise_bounded_relu,
+ eltwise_soft_relu = mkldnn_eltwise_soft_relu,
+ eltwise_logistic = mkldnn_eltwise_logistic,
+ lrn_across_channels = mkldnn_lrn_across_channels,
+ lrn_within_channel = mkldnn_lrn_within_channel,
+ pooling_max = mkldnn_pooling_max,
+ pooling_avg = mkldnn_pooling_avg,
+ pooling_avg_include_padding = mkldnn_pooling_avg_include_padding,
+ pooling_avg_exclude_padding = mkldnn_pooling_avg_exclude_padding,
+ vanilla_rnn = mkldnn_vanilla_rnn,
+ vanilla_lstm = mkldnn_vanilla_lstm,
+ vanilla_gru = mkldnn_vanilla_gru,
+};
+
+inline mkldnn_alg_kind_t convert_to_c(algorithm aalgorithm) {
+ return static_cast<mkldnn_alg_kind_t>(aalgorithm);
+}
+
+enum batch_normalization_flag {
+ use_global_stats = mkldnn_use_global_stats,
+ use_scale_shift = mkldnn_use_scaleshift,
+ omit_stats = mkldnn_omit_stats,
+ fuse_bn_relu = mkldnn_fuse_bn_relu
+};
+
+inline mkldnn_batch_normalization_flag_t convert_to_c(
+ batch_normalization_flag aflag) {
+ return static_cast<mkldnn_batch_normalization_flag_t>(aflag);
+}
+
+enum rnn_direction {
+ unidirectional_left2right = mkldnn_unidirectional_left2right,
+ unidirectional_right2left = mkldnn_unidirectional_right2left,
+ unidirectional = mkldnn_unidirectional,
+ bidirectional_concat = mkldnn_bidirectional_concat,
+ bidirectional_sum = mkldnn_bidirectional_sum,
+};
+
+inline mkldnn_rnn_direction_t convert_to_c(rnn_direction adir) {
+ return static_cast<mkldnn_rnn_direction_t>(adir);
+}
+
+enum query {
+ undef = mkldnn_query_undef,
+
+ eengine = mkldnn_query_engine,
+ primitive_kind = mkldnn_query_primitive_kind,
+
+ num_of_inputs_s32 = mkldnn_query_num_of_inputs_s32,
+ num_of_outputs_s32 = mkldnn_query_num_of_outputs_s32,
+
+ time_estimate_f64 = mkldnn_query_time_estimate_f64,
+ memory_consumption_s64 = mkldnn_query_memory_consumption_s64,
+
+ impl_info_str = mkldnn_query_impl_info_str,
+
+ memory_d = mkldnn_query_memory_d,
+ convolution_d = mkldnn_query_convolution_d,
+ deconvolution_d = mkldnn_query_deconvolution_d,
+ eltwise_d = mkldnn_query_eltwise_d,
+ relu_d = mkldnn_query_relu_d,
+ softmax_d = mkldnn_query_softmax_d,
+ pooling_d = mkldnn_query_pooling_d,
+ lrn_d = mkldnn_query_lrn_d,
+ batch_normalization_d = mkldnn_query_batch_normalization_d,
+ inner_product_d = mkldnn_query_inner_product_d,
+ convolution_relu_d = mkldnn_query_convolution_relu_d,
+ rnn_d = mkldnn_query_rnn_d,
+
+ input_pd = mkldnn_query_input_pd,
+ output_pd = mkldnn_query_output_pd,
+ src_pd = mkldnn_query_src_pd,
+ diff_src_pd = mkldnn_query_diff_src_pd,
+ weights_pd = mkldnn_query_weights_pd,
+ diff_weights_pd = mkldnn_query_diff_weights_pd,
+ dst_pd = mkldnn_query_dst_pd,
+ diff_dst_pd = mkldnn_query_diff_dst_pd,
+ workspace_pd = mkldnn_query_workspace_pd,
+};
+
+inline mkldnn_query_t convert_to_c(query aquery) {
+ return static_cast<mkldnn_query_t>(aquery);
+}
+
+/// @}
+
+/// @addtogroup cpp_api_attr Attributes
+/// @{
+
+#ifndef DOXYGEN_SHOULD_SKIP_THIS
+template <>
+struct handle_traits<mkldnn_post_ops_t> {
+ static constexpr auto destructor = &mkldnn_post_ops_destroy;
+};
+#endif
+
+struct post_ops : public handle<mkldnn_post_ops_t> {
+ post_ops() {
+ mkldnn_post_ops_t result;
+ error::wrap_c_api(mkldnn_post_ops_create(&result),
+ "could not create post operation sequence");
+ reset(result);
+ }
+
+ int len() const { return mkldnn_post_ops_len(get()); }
+
+ primitive::kind kind(int index) const {
+ error::wrap_c_api(index < len() ? mkldnn_success : mkldnn_invalid_arguments,
+ "post_ops index is out of range");
+ return static_cast<primitive::kind>(mkldnn_post_ops_get_kind(get(), index));
+ }
+
+ void append_sum(float scale = 1.) {
+ error::wrap_c_api(mkldnn_post_ops_append_sum(get(), scale),
+ "could not append sum");
+ }
+
+ void get_params_sum(int index, float &scale) const {
+ error::wrap_c_api(mkldnn_post_ops_get_params_sum(get(), index, &scale),
+ "could not get sum params");
+ }
+
+ void append_eltwise(float scale, algorithm alg, float alpha, float beta) {
+ error::wrap_c_api(mkldnn_post_ops_append_eltwise(
+ get(), scale, convert_to_c(alg), alpha, beta),
+ "could not append eltwise");
+ }
+
+ void get_params_eltwise(int index,
+ float &scale,
+ algorithm &alg,
+ float &alpha,
+ float &beta) const {
+ mkldnn_alg_kind_t c_alg;
+ error::wrap_c_api(mkldnn_post_ops_get_params_eltwise(
+ get(), index, &scale, &c_alg, &alpha, &beta),
+ "could not get eltwise params");
+ alg = static_cast<algorithm>(c_alg);
+ }
+};
+
+#ifndef DOXYGEN_SHOULD_SKIP_THIS
+template <>
+struct handle_traits<mkldnn_primitive_attr_t> {
+ static constexpr auto destructor = &mkldnn_primitive_attr_destroy;
+};
+#endif
+
+struct primitive_attr : public handle<mkldnn_primitive_attr_t> {
+ primitive_attr() {
+ mkldnn_primitive_attr_t result;
+ error::wrap_c_api(mkldnn_primitive_attr_create(&result),
+ "could not create a primitive attr");
+ reset(result);
+ }
+
+ round_mode get_int_output_round_mode() const {
+ mkldnn_round_mode_t result;
+ error::wrap_c_api(
+ mkldnn_primitive_attr_get_int_output_round_mode(get(), &result),
+ "could not get int output round mode");
+ return round_mode(result);
+ }
+
+ void set_int_output_round_mode(round_mode mode) {
+ error::wrap_c_api(mkldnn_primitive_attr_set_int_output_round_mode(
+ get(), mkldnn::convert_to_c(mode)),
+ "could not set int output round mode");
+ }
+
+ void get_output_scales(int &mask, std::vector<float> &scales) const {
+ int count, c_mask;
+ const float *c_scales;
+ error::wrap_c_api(mkldnn_primitive_attr_get_output_scales(
+ get(), &count, &c_mask, &c_scales),
+ "could not get int output scales");
+ scales.resize(count);
+
+ mask = c_mask;
+ for (int c = 0; c < count; ++c) scales[c] = c_scales[c];
+ }
+
+ void set_output_scales(int mask, const std::vector<float> &scales) {
+ error::wrap_c_api(mkldnn_primitive_attr_set_output_scales(
+ get(), (int)scales.size(), mask, &scales[0]),
+ "could not set int output scales");
+ }
+
+ const post_ops get_post_ops() const {
+ post_ops result;
+ const_mkldnn_post_ops_t c_result;
+ error::wrap_c_api(mkldnn_primitive_attr_get_post_ops(get(), &c_result),
+ "could not get post operation sequence");
+ result.reset(const_cast<mkldnn_post_ops_t>(c_result), true);
+ return result;
+ }
+
+ void set_post_ops(post_ops ops) {
+ error::wrap_c_api(mkldnn_primitive_attr_set_post_ops(get(), ops.get()),
+ "could not set post operation sequence");
+ }
+};
+
+/// @}
+
+/// @addtogroup cpp_api_engine Engine
+/// @{
+
+#ifndef DOXYGEN_SHOULD_SKIP_THIS
+template <>
+struct handle_traits<mkldnn_engine_t> {
+ static constexpr auto destructor = &mkldnn_engine_destroy;
+};
+#endif
+
+/// An execution engine.
+struct engine : public handle<mkldnn_engine_t> {
+ friend class primitive;
+ // gcc bug??? using handle::handle;
+
+ /// Kinds of engines
+ enum kind {
+ /// An unspecified engine
+ any = mkldnn_any_engine,
+ /// CPU engine
+ cpu = mkldnn_cpu,
+ };
+
+ /// Returns the number of engines of a certain kind.
+ ///
+ /// @param akind The kind of engines to count.
+
+ static size_t get_count(kind akind) {
+ return mkldnn_engine_get_count(convert_to_c(akind));
+ }
+
+ /// Constructs an engine.
+ ///
+ /// @param akind The kind of engine to construct.
+ /// @param index The index of the engine. Must be less than the value
+ /// returned by #get_count() for this particular kind of engine.
+
+ engine(kind akind, size_t index) {
+ mkldnn_engine_t aengine;
+ error::wrap_c_api(
+ mkldnn_engine_create(&aengine, convert_to_c(akind), index),
+ "could not create an engine");
+ reset(aengine);
+ }
+
+ explicit engine(const mkldnn_engine_t &aengine) : handle(aengine, true) {}
+
+ engine(const handle<mkldnn_primitive_desc_t> &pd) {
+ mkldnn_engine_t engine_q;
+ error::wrap_c_api(
+ mkldnn_primitive_desc_query(
+ pd.get(), mkldnn::convert_to_c(eengine), 0, &engine_q),
+ "could not get engine from primitive_desc");
+ reset(engine_q, true);
+ }
+
+ template <class primitive_desc>
+ static engine query(const primitive_desc &pd) {
+ mkldnn_engine_t engine_q;
+ error::wrap_c_api(
+ mkldnn_primitive_desc_query(
+ pd.get(), mkldnn::convert_to_c(eengine), 0, &engine_q),
+ "could not get engine from primitive_desc");
+
+ return engine(engine_q);
+ }
+
+private:
+ static mkldnn_engine_kind_t convert_to_c(kind akind) {
+ return static_cast<mkldnn_engine_kind_t>(akind);
+ }
+};
+
+/// @}
+
+/// @addtogroup cpp_api_primitives Primitives
+/// @{
+
+/// @addtogroup cpp_api_memory Memory
+/// @{
+
+/// Memory primitive that describes the data.
+struct memory : public primitive {
+private:
+ std::shared_ptr<char> _handle;
+
+public:
+ typedef std::vector<std::remove_extent<mkldnn_dims_t>::type> dims;
+
+ template <typename T>
+ static void validate_dims(std::vector<T> v) {
+ if (v.size() > TENSOR_MAX_DIMS)
+ throw error(mkldnn_invalid_arguments, "invalid dimensions");
+ }
+
+ /// Data type specification. See #mkldnn_data_type_t for a detailed
+ /// description.
+ enum data_type {
+ data_undef = mkldnn_data_type_undef,
+ f32 = mkldnn_f32,
+ s32 = mkldnn_s32,
+ s16 = mkldnn_s16,
+ s8 = mkldnn_s8,
+ u8 = mkldnn_u8,
+ };
+
+ /// Memory format specification. See #mkldnn_memory_format_t
+ /// for a detailed description.
+ enum format {
+ format_undef = mkldnn_format_undef,
+ any = mkldnn_any,
+ blocked = mkldnn_blocked,
+ x = mkldnn_x,
+ nc = mkldnn_nc,
+ nchw = mkldnn_nchw,
+ nhwc = mkldnn_nhwc,
+ chwn = mkldnn_chwn,
+ nChw8c = mkldnn_nChw8c,
+ nChw16c = mkldnn_nChw16c,
+ ncdhw = mkldnn_ncdhw,
+ ndhwc = mkldnn_ndhwc,
+ nCdhw16c = mkldnn_nCdhw16c,
+ oi = mkldnn_oi,
+ io = mkldnn_io,
+ oihw = mkldnn_oihw,
+ ihwo = mkldnn_ihwo,
+ hwio = mkldnn_hwio,
+ oidhw = mkldnn_oidhw,
+ OIdhw16i16o = mkldnn_OIdhw16i16o,
+ OIdhw16o16i = mkldnn_OIdhw16o16i,
+ Oidhw16o = mkldnn_Oidhw16o,
+ Odhwi16o = mkldnn_Odhwi16o,
+ oIhw8i = mkldnn_oIhw8i,
+ oIhw16i = mkldnn_oIhw16i,
+ OIhw8i8o = mkldnn_OIhw8i8o,
+ OIhw16i16o = mkldnn_OIhw16i16o,
+ OIhw8o8i = mkldnn_OIhw8o8i,
+ OIhw16o16i = mkldnn_OIhw16o16i,
+ IOhw16o16i = mkldnn_IOhw16o16i,
+ OIhw8i16o2i = mkldnn_OIhw8i16o2i,
+ OIhw8o16i2o = mkldnn_OIhw8o16i2o,
+ OIhw4i16o4i = mkldnn_OIhw4i16o4i,
+ Oihw8o = mkldnn_Oihw8o,
+ Oihw16o = mkldnn_Oihw16o,
+ Ohwi8o = mkldnn_Ohwi8o,
+ Ohwi16o = mkldnn_Ohwi16o,
+ OhIw16o4i = mkldnn_OhIw16o4i,
+ goihw = mkldnn_goihw,
+ hwigo = mkldnn_hwigo,
+ gOIhw8i8o = mkldnn_gOIhw8i8o,
+ gOIhw16i16o = mkldnn_gOIhw16i16o,
+ gOIhw8i16o2i = mkldnn_gOIhw8i16o2i,
+ gOIhw8o16i2o = mkldnn_gOIhw8o16i2o,
+ gOIhw4i16o4i = mkldnn_gOIhw4i16o4i,
+ gOihw8o = mkldnn_gOihw8o,
+ gOihw16o = mkldnn_gOihw16o,
+ gOhwi8o = mkldnn_gOhwi8o,
+ gOhwi16o = mkldnn_gOhwi16o,
+ Goihw8g = mkldnn_Goihw8g,
+ Goihw16g = mkldnn_Goihw16g,
+ gOIhw8o8i = mkldnn_gOIhw8o8i,
+ gOIhw16o16i = mkldnn_gOIhw16o16i,
+ gIOhw16o16i = mkldnn_gIOhw16o16i,
+ gOhIw16o4i = mkldnn_gOhIw16o4i,
+ goidhw = mkldnn_goidhw,
+ gOIdhw16i16o = mkldnn_gOIdhw16i16o,
+ gOIdhw16o16i = mkldnn_gOIdhw16o16i,
+ gOidhw16o = mkldnn_gOidhw16o,
+ gOdhwi16o = mkldnn_gOdhwi16o,
+ ntc = mkldnn_ntc,
+ tnc = mkldnn_tnc,
+ ldsnc = mkldnn_ldsnc,
+ ldigo = mkldnn_ldigo,
+ ldigo_p = mkldnn_ldigo_p,
+ ldgoi = mkldnn_ldgoi,
+ ldgoi_p = mkldnn_ldgoi_p,
+ ldgo = mkldnn_ldgo,
+ wino_fmt = mkldnn_wino_fmt,
+ format_last = mkldnn_format_last,
+ };
+
+ /// A memory descriptor.
+ struct desc {
+ friend struct memory;
+ /// The underlying C API data structure.
+ mkldnn_memory_desc_t data;
+
+ /// Constructs a memory descriptor.
+ ///
+ /// @param adims Data dimensions
+ /// @param adata_type Data precision/type.
+ /// @param aformat Data layout format.
+ desc(dims adims, data_type adata_type, format aformat) {
+ validate_dims(adims);
+ error::wrap_c_api(
+ mkldnn_memory_desc_init(&data,
+ (int)adims.size(),
+ adims.size() == 0 ? nullptr : &adims[0],
+ convert_to_c(adata_type),
+ convert_to_c(aformat)),
+ "could not initialize a memory descriptor");
+ }
+
+ /// Constructs a memory descriptor from a C API data structure.
+ ///
+ /// @param adata A C API #mkldnn_memory_desc_t structure.
+ desc(const mkldnn_memory_desc_t &adata) : data(adata) {}
+ };
+
+ /// A memory primitive descriptor.
+ struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
+ friend struct memory;
+
+ // TODO: make private
+ primitive_desc() {}
+
+ /// Constructs a memory primitive descriptor.
+ primitive_desc(const desc &adesc, const engine &aengine) {
+ mkldnn_primitive_desc_t result;
+ error::wrap_c_api(mkldnn_memory_primitive_desc_create(
+ &result, &adesc.data, aengine.get()),
+ "could not initialize a memory primitive descriptor");
+ reset(result);
+ }
+
+ /// Returns the memory primitive descriptor.
+ memory::desc desc() {
+ auto memory_d = mkldnn_primitive_desc_query_memory_d(get());
+ return memory::desc(*memory_d);
+ }
+
+ /// Returns the number of bytes required to allocate the memory described
+ /// including the padding area.
+ size_t get_size() const {
+ return mkldnn_memory_primitive_desc_get_size(get());
+ }
+
+ bool operator==(const primitive_desc &other) const {
+ return mkldnn_memory_primitive_desc_equal(get(), other.get());
+ }
+
+ bool operator!=(const primitive_desc &other) const {
+ return !operator==(other);
+ }
+
+ engine get_engine() { return engine::query(*this); }
+ };
+
+ /// Constructs a memory primitive from a generic primitive.
+ ///
+ /// @param aprimitive The primitive to treat as memory.
+ memory(const primitive &aprimitive) : primitive(aprimitive) {}
+ /// Constructs a memory primitive.
+ ///
+ /// @param adesc Memory primitive descriptor.
+ memory(const primitive_desc &adesc) {
+ mkldnn_primitive_t result;
+ error::wrap_c_api(
+ mkldnn_primitive_create(&result, adesc.get(), nullptr, nullptr),
+ "could not create a memory primitive");
+ reset(result);
+ auto _malloc = [](size_t size, int alignment) {
+ void *ptr;
+#ifdef _WIN32
+ ptr = _aligned_malloc(size, alignment);
+ int rc = ((ptr) ? 0 : errno);
+#else
+ int rc = ::posix_memalign(&ptr, alignment, size);
+#endif /* _WIN32 */
+ return (rc == 0) ? (char *)ptr : nullptr;
+ };
+ auto _free = [](char *p) {
+#ifdef _WIN32
+ _aligned_free((void *)p);
+#else
+ ::free((void *)p);
+#endif /* _WIN32 */
+ };
+ _handle.reset(_malloc(adesc.get_size(), 4096), _free);
+ set_data_handle(_handle.get());
+ }
+
+ memory(const primitive_desc &adesc, void *ahandle) {
+ mkldnn_primitive_t result;
+ error::wrap_c_api(
+ mkldnn_primitive_create(&result, adesc.get(), nullptr, nullptr),
+ "could not create a memory primitive");
+ reset(result);
+ set_data_handle(ahandle);
+ }
+
+ /// Returns the descriptor of the memory primitive.
+ primitive_desc get_primitive_desc() const {
+ primitive_desc adesc;
+ const_mkldnn_primitive_desc_t cdesc;
+ error::wrap_c_api(
+ mkldnn_primitive_get_primitive_desc(get(), &cdesc),
+ "could not get primitive descriptor from a memory primitive");
+ /* FIXME: no const_cast should be here */
+ adesc.reset(const_cast<mkldnn_primitive_desc_t>(cdesc), true);
+ return adesc;
+ }
+
+ /// Returns a handle of the data contained in the memory primitive. On
+ /// the CPU engine, this is a pointer to the allocated memory.
+ inline void *get_data_handle() const {
+ void *handle;
+ error::wrap_c_api(mkldnn_memory_get_data_handle(get(), &handle),
+ "could not get native handle");
+ return handle;
+ }
+
+ inline void set_data_handle(void *handle) const {
+ error::wrap_c_api(mkldnn_memory_set_data_handle(get(), handle),
+ "could not set native handle");
+ }
+
+ // Must go away or be private:
+ static mkldnn_data_type_t convert_to_c(data_type adata_type) {
+ return static_cast<mkldnn_data_type_t>(adata_type);
+ }
+ static mkldnn_memory_format_t convert_to_c(format aformat) {
+ return static_cast<mkldnn_memory_format_t>(aformat);
+ }
+};
+
+inline memory::desc zero_md() {
+ mkldnn_memory_desc_t zero;
+ zero.primitive_kind = mkldnn_memory;
+ return memory::desc(zero);
+}
+
+inline memory null_memory(engine eng) {
+ mkldnn::memory::desc zero = zero_md();
+ return memory({zero, eng}, nullptr);
+}
+
+inline bool is_null_memory(const const_mkldnn_primitive_t &aprimitive) {
+ const_mkldnn_primitive_desc_t aprimitive_pd;
+ mkldnn_primitive_get_primitive_desc(aprimitive, &aprimitive_pd);
+ const mkldnn_memory_desc_t *aprimitive_md =
+ mkldnn_primitive_desc_query_memory_d(aprimitive_pd);
+
+ return ((aprimitive_md != nullptr) && (aprimitive_md->ndims == 0));
+}
+
+inline bool operator==(mkldnn_data_type_t a, memory::data_type b) {
+ return a == memory::convert_to_c(b);
+}
+inline bool operator!=(mkldnn_data_type_t a, memory::data_type b) {
+ return !(a == b);
+}
+inline bool operator==(memory::data_type a, mkldnn_data_type_t b) {
+ return b == a;
+}
+inline bool operator!=(memory::data_type a, mkldnn_data_type_t b) {
+ return !(a == b);
+}
+
+inline bool operator==(mkldnn_memory_format_t a, memory::format b) {
+ return a == memory::convert_to_c(b);
+}
+inline bool operator!=(mkldnn_memory_format_t a, memory::format b) {
+ return !(a == b);
+}
+inline bool operator==(memory::format a, mkldnn_memory_format_t b) {
+ return b == a;
+}
+inline bool operator!=(memory::format a, mkldnn_memory_format_t b) {
+ return !(a == b);
+}
+
+/// @}
+
+/// @addtogroup cpp_api_reorder Reorder
+/// @{
+
+struct reorder : public primitive {
+ struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
+ primitive_desc(const memory::primitive_desc &input,
+ const memory::primitive_desc &output) {
+ mkldnn_primitive_desc_t result;
+ error::wrap_c_api(mkldnn_reorder_primitive_desc_create(
+ &result, input.get(), output.get()),
+ "could not create a reorder primitive descriptor");
+ reset(result);
+ }
+
+ primitive_desc(const memory::primitive_desc &input,
+ const memory::primitive_desc &output,
+ const primitive_attr &aattr) {
+ mkldnn_primitive_desc_t result;
+ error::wrap_c_api(mkldnn_reorder_primitive_desc_create_v2(
+ &result, input.get(), output.get(), aattr.get()),
+ "could not create a reorder primitive descriptor");
+ reset(result);
+ }
+
+ engine get_engine() { return engine::query(*this); }
+ };
+
+ reorder(const primitive_desc &aprimitive_desc,
+ const primitive::at &input,
+ const memory &output) {
+ mkldnn_primitive_t result;
+ mkldnn_primitive_at_t inputs[] = {input.data};
+ const_mkldnn_primitive_t outputs[] = {output.get()};
+ error::wrap_c_api(mkldnn_primitive_create(
+ &result, aprimitive_desc.get(), inputs, outputs),
+ "could not create a reorder primitive");
+ reset(result);
+ }
+
+ reorder(const primitive::at &input, const memory &output) {
+ auto input_mpd = memory(input).get_primitive_desc();
+ auto output_mpd = output.get_primitive_desc();
+
+ auto reorder_d = primitive_desc(input_mpd, output_mpd);
+
+ mkldnn_primitive_t result;
+ mkldnn_primitive_at_t inputs[] = {input.data};
+ const_mkldnn_primitive_t outputs[] = {output.get()};
+ error::wrap_c_api(
+ mkldnn_primitive_create(&result, reorder_d.get(), inputs, outputs),
+ "could not create a reorder primitive");
+ reset(result);
+ }
+};
+
+/// @}
+
+/// @addtogroup cpp_api_view View
+/// @{
+
+struct view : public primitive {
+ struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
+ primitive_desc(const memory::primitive_desc &input,
+ memory::dims dims,
+ memory::dims offsets) {
+ mkldnn_primitive_desc_t result;
+
+ error::wrap_c_api(mkldnn_view_primitive_desc_create(
+ &result, input.get(), &dims[0], &offsets[0]),
+ "could not create a view primitive descriptor");
+ reset(result);
+ }
+
+ memory::primitive_desc dst_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t cdesc;
+ const_mkldnn_primitive_desc_t const_cdesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(dst_pd), 0);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
+ "could not clone a dst primitive descriptor");
+ adesc.reset(cdesc);
+ return adesc;
+ }
+
+ engine get_engine() { return engine::query(*this); }
+ };
+
+ view(const primitive_desc &view_pd, primitive::at input) {
+ mkldnn_primitive_t result;
+ mkldnn_primitive_at_t inputs[] = {input.data};
+ error::wrap_c_api(
+ mkldnn_primitive_create(&result, view_pd.get(), inputs, nullptr),
+ "could not create a view primitive");
+ reset(result);
+ }
+
+ view(memory input, memory::dims dims, memory::dims offsets) {
+ mkldnn_primitive_t result;
+ primitive_desc view_pd(input.get_primitive_desc(), dims, offsets);
+ mkldnn_primitive_at_t inputs[] = {primitive::at(input).data};
+ error::wrap_c_api(
+ mkldnn_primitive_create(&result, view_pd.get(), inputs, nullptr),
+ "could not create a view primitive");
+ reset(result);
+ }
+};
+
+/// @}
+
+/// @addtogroup cpp_api_concat Concat
+/// @{
+
+struct concat : public primitive {
+ struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
+ std::vector<const_mkldnn_primitive_desc_t> cpp_to_c(
+ std::vector<memory::primitive_desc> inputs) {
+ std::vector<const_mkldnn_primitive_desc_t> c_api_inputs;
+ c_api_inputs.reserve(inputs.size());
+ auto convert_to_c = [](memory::primitive_desc d) { return d.get(); };
+ std::transform(inputs.begin(),
+ inputs.end(),
+ std::back_inserter(c_api_inputs),
+ convert_to_c);
+ return c_api_inputs;
+ }
+
+ primitive_desc(const memory::desc &output,
+ int concat_dimension,
+ std::vector<memory::primitive_desc> inputs) {
+ mkldnn_primitive_desc_t result;
+
+ auto c_api_inputs = cpp_to_c(inputs);
+
+ error::wrap_c_api(
+ mkldnn_concat_primitive_desc_create(&result,
+ &output.data,
+ (int)c_api_inputs.size(),
+ concat_dimension,
+ &c_api_inputs[0]),
+ "could not create a concat primitive descriptor");
+ reset(result);
+ }
+
+ primitive_desc(int concat_dimension,
+ std::vector<memory::primitive_desc> inputs) {
+ mkldnn_primitive_desc_t result;
+
+ auto c_api_inputs = cpp_to_c(inputs);
+
+ error::wrap_c_api(
+ mkldnn_concat_primitive_desc_create(&result,
+ nullptr,
+ (int)c_api_inputs.size(),
+ concat_dimension,
+ &c_api_inputs[0]),
+ "could not create a concat primitive descriptor");
+ reset(result);
+ }
+
+ memory::primitive_desc dst_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t cdesc;
+ const_mkldnn_primitive_desc_t const_cdesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(dst_pd), 0);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
+ "could not clone a dst primitive descriptor");
+ adesc.reset(cdesc);
+ return adesc;
+ }
+
+ engine get_engine() { return engine::query(*this); }
+ };
+
+ concat(const primitive_desc &concat_pd,
+ std::vector<primitive::at> &inputs,
+ const memory &output) {
+ mkldnn_primitive_t result;
+
+ std::vector<mkldnn_primitive_at_t> p_inputs;
+ for (size_t i = 0; i < inputs.size(); i++)
+ p_inputs.push_back(inputs[i].data);
+ const_mkldnn_primitive_t outputs[] = {output.get()};
+
+ error::wrap_c_api(mkldnn_primitive_create(
+ &result, concat_pd.get(), &p_inputs[0], outputs),
+ "could not create a concat primitive");
+ reset(result);
+ }
+};
+
+/// @}
+
+/// @addtogroup cpp_api_sum Sum
+/// @{
+
+struct sum : public primitive {
+ struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
+ std::vector<const_mkldnn_primitive_desc_t> cpp_to_c(
+ std::vector<memory::primitive_desc> inputs) {
+ std::vector<const_mkldnn_primitive_desc_t> c_api_inputs;
+ c_api_inputs.reserve(inputs.size());
+ auto convert_to_c = [](memory::primitive_desc d) { return d.get(); };
+ std::transform(inputs.begin(),
+ inputs.end(),
+ std::back_inserter(c_api_inputs),
+ convert_to_c);
+ return c_api_inputs;
+ }
+
+ primitive_desc(const memory::desc &output,
+ const std::vector<float> &scales,
+ std::vector<memory::primitive_desc> inputs) {
+ mkldnn_primitive_desc_t result;
+
+ auto c_api_inputs = cpp_to_c(inputs);
+
+ error::wrap_c_api(
+ mkldnn_sum_primitive_desc_create(&result,
+ &output.data,
+ (int)c_api_inputs.size(),
+ &scales[0],
+ &c_api_inputs[0]),
+ "could not create a sum primitive descriptor");
+ reset(result);
+ }
+
+ primitive_desc(const std::vector<float> &scales,
+ std::vector<memory::primitive_desc> inputs) {
+ mkldnn_primitive_desc_t result;
+
+ auto c_api_inputs = cpp_to_c(inputs);
+
+ error::wrap_c_api(
+ mkldnn_sum_primitive_desc_create(&result,
+ nullptr,
+ (int)c_api_inputs.size(),
+ &scales[0],
+ &c_api_inputs[0]),
+ "could not create a sum primitive descriptor");
+ reset(result);
+ }
+
+ /** @deprecated: api backwards compatibility for double scales type */
+ MKLDNN_DEPRECATED
+ primitive_desc(const memory::desc &output,
+ std::vector<double> scale,
+ std::vector<memory::primitive_desc> inputs) {
+ mkldnn_primitive_desc_t result;
+
+ auto c_api_inputs = cpp_to_c(inputs);
+ auto scale_f = scale_to_float(scale);
+
+ error::wrap_c_api(
+ mkldnn_sum_primitive_desc_create(&result,
+ &output.data,
+ (int)c_api_inputs.size(),
+ &scale_f[0],
+ &c_api_inputs[0]),
+ "could not create a sum primitive descriptor");
+ reset(result);
+ }
+
+ /** @deprecated: api backwards compatibility for double scales type */
+ MKLDNN_DEPRECATED
+ primitive_desc(std::vector<double> scale,
+ std::vector<memory::primitive_desc> inputs) {
+ mkldnn_primitive_desc_t result;
+
+ auto c_api_inputs = cpp_to_c(inputs);
+ auto scale_f = scale_to_float(scale);
+
+ error::wrap_c_api(
+ mkldnn_sum_primitive_desc_create(&result,
+ nullptr,
+ (int)c_api_inputs.size(),
+ &scale_f[0],
+ &c_api_inputs[0]),
+ "could not create a sum primitive descriptor");
+ reset(result);
+ }
+
+ memory::primitive_desc dst_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t cdesc;
+ const_mkldnn_primitive_desc_t const_cdesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(dst_pd), 0);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
+ "could not clone a dst primitive descriptor");
+ adesc.reset(cdesc);
+ return adesc;
+ }
+
+ engine get_engine() { return engine::query(*this); }
+ };
+
+ sum(const primitive_desc &sum_pd,
+ std::vector<primitive::at> &inputs,
+ const memory &output) {
+ mkldnn_primitive_t result;
+
+ std::vector<mkldnn_primitive_at_t> p_inputs;
+ for (size_t i = 0; i < inputs.size(); i++)
+ p_inputs.push_back(inputs[i].data);
+ const_mkldnn_primitive_t outputs[] = {output.get()};
+
+ error::wrap_c_api(
+ mkldnn_primitive_create(&result, sum_pd.get(), &p_inputs[0], outputs),
+ "could not create a sum primitive");
+ reset(result);
+ }
+
+private:
+ static std::vector<float> scale_to_float(const std::vector<double> &vd) {
+ std::vector<float> vf(vd.size());
+ std::transform(
+ vd.begin(), vd.end(), vf.begin(), [=](double x) { return (float)x; });
+ return vf;
+ }
+};
+
+/// @}
+
+/// @addtogroup cpp_api_convolution Convolution
+/// @{
+
+struct convolution_forward : public primitive {
+ struct desc {
+ mkldnn_convolution_desc_t data;
+ desc(prop_kind aprop_kind,
+ algorithm aalgorithm,
+ const memory::desc &src_desc,
+ const memory::desc &weights_desc,
+ const memory::desc &bias_desc,
+ const memory::desc &dst_desc,
+ const memory::dims strides,
+ const memory::dims padding_l,
+ const memory::dims padding_r,
+ const padding_kind apadding_kind) {
+ memory::validate_dims(strides);
+ memory::validate_dims(padding_l);
+ memory::validate_dims(padding_r);
+ error::wrap_c_api(mkldnn_convolution_forward_desc_init(
+ &data,
+ mkldnn::convert_to_c(aprop_kind),
+ convert_to_c(aalgorithm),
+ &src_desc.data,
+ &weights_desc.data,
+ &bias_desc.data,
+ &dst_desc.data,
+ &strides[0],
+ &padding_l[0],
+ &padding_r[0],
+ mkldnn::convert_to_c(apadding_kind)),
+ "could not create a convolution forward descriptor");
+ }
+ desc(prop_kind aprop_kind,
+ algorithm aalgorithm,
+ const memory::desc &src_desc,
+ const memory::desc &weights_desc,
+ const memory::desc &dst_desc,
+ const memory::dims strides,
+ const memory::dims padding_l,
+ const memory::dims padding_r,
+ const padding_kind apadding_kind) {
+ memory::validate_dims(strides);
+ memory::validate_dims(padding_l);
+ memory::validate_dims(padding_r);
+ error::wrap_c_api(mkldnn_convolution_forward_desc_init(
+ &data,
+ mkldnn::convert_to_c(aprop_kind),
+ convert_to_c(aalgorithm),
+ &src_desc.data,
+ &weights_desc.data,
+ nullptr,
+ &dst_desc.data,
+ &strides[0],
+ &padding_l[0],
+ &padding_r[0],
+ mkldnn::convert_to_c(apadding_kind)),
+ "could not create a convolution forward descriptor");
+ }
+ desc(prop_kind aprop_kind,
+ algorithm aalgorithm,
+ const memory::desc &src_desc,
+ const memory::desc &weights_desc,
+ const memory::desc &bias_desc,
+ const memory::desc &dst_desc,
+ const memory::dims strides,
+ const memory::dims dilates,
+ const memory::dims padding_l,
+ const memory::dims padding_r,
+ const padding_kind apadding_kind) {
+ memory::validate_dims(strides);
+ memory::validate_dims(dilates);
+ memory::validate_dims(padding_l);
+ memory::validate_dims(padding_r);
+ error::wrap_c_api(
+ mkldnn_dilated_convolution_forward_desc_init(
+ &data,
+ mkldnn::convert_to_c(aprop_kind),
+ convert_to_c(aalgorithm),
+ &src_desc.data,
+ &weights_desc.data,
+ &bias_desc.data,
+ &dst_desc.data,
+ &strides[0],
+ &dilates[0],
+ &padding_l[0],
+ &padding_r[0],
+ mkldnn::convert_to_c(apadding_kind)),
+ "could not create a dilated convolution forward descriptor");
+ }
+ desc(prop_kind aprop_kind,
+ algorithm aalgorithm,
+ const memory::desc &src_desc,
+ const memory::desc &weights_desc,
+ const memory::desc &dst_desc,
+ const memory::dims strides,
+ const memory::dims dilates,
+ const memory::dims padding_l,
+ const memory::dims padding_r,
+ const padding_kind apadding_kind) {
+ memory::validate_dims(strides);
+ memory::validate_dims(dilates);
+ memory::validate_dims(padding_l);
+ memory::validate_dims(padding_r);
+ error::wrap_c_api(
+ mkldnn_dilated_convolution_forward_desc_init(
+ &data,
+ mkldnn::convert_to_c(aprop_kind),
+ convert_to_c(aalgorithm),
+ &src_desc.data,
+ &weights_desc.data,
+ nullptr,
+ &dst_desc.data,
+ &strides[0],
+ &dilates[0],
+ &padding_l[0],
+ &padding_r[0],
+ mkldnn::convert_to_c(apadding_kind)),
+ "could not create a dilated convolution forward descriptor");
+ }
+ };
+ struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
+ primitive_desc(const desc &adesc, const engine &aengine) {
+ mkldnn_primitive_desc_t result;
+ error::wrap_c_api(
+ mkldnn_primitive_desc_create(
+ &result, &adesc.data, aengine.get(), nullptr),
+ "could not create a convolution forward primitive descriptor");
+ reset(result);
+ }
+
+ primitive_desc(const desc &adesc,
+ const primitive_attr &aattr,
+ const engine &aengine) {
+ mkldnn_primitive_desc_t result;
+ error::wrap_c_api(
+ mkldnn_primitive_desc_create_v2(
+ &result, &adesc.data, aattr.get(), aengine.get(), nullptr),
+ "could not create a convolution forward primitive descriptor");
+ reset(result);
+ }
+
+ memory::primitive_desc src_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t cdesc;
+ const_mkldnn_primitive_desc_t const_cdesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(src_pd), 0);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
+ "could not clone a src primititve descriptor");
+ adesc.reset(cdesc);
+ return adesc;
+ }
+
+ memory::primitive_desc weights_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t cdesc;
+ const_mkldnn_primitive_desc_t const_cdesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(weights_pd), 0);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
+ "could not clone a weights primitive descriptor");
+ adesc.reset(cdesc);
+ return adesc;
+ }
+
+ memory::primitive_desc bias_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t cdesc;
+ const_mkldnn_primitive_desc_t const_cdesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(weights_pd), 1);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
+ "could not clone a bias primitive descriptor");
+ adesc.reset(cdesc);
+ return adesc;
+ }
+
+ memory::primitive_desc dst_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t cdesc;
+ const_mkldnn_primitive_desc_t const_cdesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(dst_pd), 0);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
+ "could not clone a dst primitive descriptor");
+ adesc.reset(cdesc);
+ return adesc;
+ }
+
+ engine get_engine() { return engine::query(*this); }
+ };
+
+ convolution_forward(const primitive_desc &aprimitive_desc,
+ const primitive::at &src,
+ const primitive::at &weights,
+ const primitive::at &bias,
+ const memory &dst) {
+ mkldnn_primitive_t result;
+ mkldnn_primitive_at_t inputs[] = {src.data, weights.data, bias.data};
+ const_mkldnn_primitive_t outputs[] = {dst.get()};
+ error::wrap_c_api(mkldnn_primitive_create(
+ &result, aprimitive_desc.get(), inputs, outputs),
+ "could not create a convolution forward bias primitive");
+ reset(result);
+ }
+
+ convolution_forward(const primitive_desc &aprimitive_desc,
+ const primitive::at &src,
+ const primitive::at &weights,
+ const memory &dst) {
+ mkldnn_primitive_t result;
+ mkldnn_primitive_at_t inputs[] = {src.data, weights.data};
+ const_mkldnn_primitive_t outputs[] = {dst.get()};
+ error::wrap_c_api(mkldnn_primitive_create(
+ &result, aprimitive_desc.get(), inputs, outputs),
+ "could not create a convolution forward primitive");
+ reset(result);
+ }
+};
+
+struct convolution_backward_data : public primitive {
+ struct desc {
+ mkldnn_convolution_desc_t data;
+ desc(algorithm aalgorithm,
+ const memory::desc &diff_src_desc,
+ const memory::desc &weights_desc,
+ const memory::desc &diff_dst_desc,
+ const memory::dims strides,
+ const memory::dims padding_l,
+ const memory::dims padding_r,
+ const padding_kind apadding_kind) {
+ memory::validate_dims(strides);
+ memory::validate_dims(padding_l);
+ memory::validate_dims(padding_r);
+ error::wrap_c_api(
+ mkldnn_convolution_backward_data_desc_init(
+ &data,
+ convert_to_c(aalgorithm),
+ &diff_src_desc.data,
+ &weights_desc.data,
+ &diff_dst_desc.data,
+ &strides[0],
+ &padding_l[0],
+ &padding_r[0],
+ mkldnn::convert_to_c(apadding_kind)),
+ "could not create a convolution backward data descriptor");
+ }
+ desc(algorithm aalgorithm,
+ const memory::desc &diff_src_desc,
+ const memory::desc &weights_desc,
+ const memory::desc &diff_dst_desc,
+ const memory::dims strides,
+ const memory::dims dilates,
+ const memory::dims padding_l,
+ const memory::dims padding_r,
+ const padding_kind apadding_kind) {
+ memory::validate_dims(strides);
+ memory::validate_dims(dilates);
+ memory::validate_dims(padding_l);
+ memory::validate_dims(padding_r);
+ error::wrap_c_api(
+ mkldnn_dilated_convolution_backward_data_desc_init(
+ &data,
+ convert_to_c(aalgorithm),
+ &diff_src_desc.data,
+ &weights_desc.data,
+ &diff_dst_desc.data,
+ &strides[0],
+ &dilates[0],
+ &padding_l[0],
+ &padding_r[0],
+ mkldnn::convert_to_c(apadding_kind)),
+ "could not create a convolution backward data descriptor");
+ }
+ };
+ struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
+ primitive_desc(
+ const desc &adesc,
+ const engine &aengine,
+ const convolution_forward::primitive_desc &hint_fwd_primitive_desc) {
+ mkldnn_primitive_desc_t result;
+ error::wrap_c_api(
+ mkldnn_primitive_desc_create(&result,
+ &adesc.data,
+ aengine.get(),
+ hint_fwd_primitive_desc.get()),
+ "could not create a convolution backward data primitive descriptor");
+ reset(result);
+ }
+ memory::primitive_desc diff_src_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t cdesc;
+ const_mkldnn_primitive_desc_t const_cdesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(diff_src_pd), 0);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
+ "could not clone a diff_src primititve descriptor");
+ adesc.reset(cdesc);
+ return adesc;
+ }
+
+ memory::primitive_desc weights_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t cdesc;
+ const_mkldnn_primitive_desc_t const_cdesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(weights_pd), 0);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
+ "could not clone a weights primitive descriptor");
+ adesc.reset(cdesc);
+ return adesc;
+ }
+
+ memory::primitive_desc diff_dst_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t cdesc;
+ const_mkldnn_primitive_desc_t const_cdesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(diff_dst_pd), 0);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
+ "could not clone a diff_dst primitive descriptor");
+ adesc.reset(cdesc);
+ return adesc;
+ }
+
+ engine get_engine() { return engine::query(*this); }
+ };
+
+ convolution_backward_data(const primitive_desc &aprimitive_desc,
+ const primitive::at &diff_dst,
+ const primitive::at &weights,
+ const memory &diff_src) {
+ mkldnn_primitive_t result;
+ mkldnn_primitive_at_t inputs[] = {diff_dst.data, weights.data};
+ const_mkldnn_primitive_t outputs[] = {diff_src.get()};
+ error::wrap_c_api(mkldnn_primitive_create(
+ &result, aprimitive_desc.get(), inputs, outputs),
+ "could not create a convolution backward data primitive");
+ reset(result);
+ }
+};
+
+struct convolution_backward_weights : public primitive {
+ struct desc {
+ mkldnn_convolution_desc_t data;
+ desc(algorithm aalgorithm,
+ const memory::desc &src_desc,
+ const memory::desc &diff_weights_desc,
+ const memory::desc &diff_bias_desc,
+ const memory::desc &diff_dst_desc,
+ const memory::dims strides,
+ const memory::dims padding_l,
+ const memory::dims padding_r,
+ const padding_kind apadding_kind) {
+ memory::validate_dims(strides);
+ memory::validate_dims(padding_l);
+ memory::validate_dims(padding_r);
+ error::wrap_c_api(
+ mkldnn_convolution_backward_weights_desc_init(
+ &data,
+ convert_to_c(aalgorithm),
+ &src_desc.data,
+ &diff_weights_desc.data,
+ &diff_bias_desc.data,
+ &diff_dst_desc.data,
+ &strides[0],
+ &padding_l[0],
+ &padding_r[0],
+ mkldnn::convert_to_c(apadding_kind)),
+ "could not create a convolution backward weights descriptor");
+ }
+ desc(algorithm aalgorithm,
+ const memory::desc &src_desc,
+ const memory::desc &diff_weights_desc,
+ const memory::desc &diff_dst_desc,
+ const memory::dims strides,
+ const memory::dims padding_l,
+ const memory::dims padding_r,
+ const padding_kind apadding_kind) {
+ memory::validate_dims(strides);
+ memory::validate_dims(padding_l);
+ memory::validate_dims(padding_r);
+ error::wrap_c_api(
+ mkldnn_convolution_backward_weights_desc_init(
+ &data,
+ convert_to_c(aalgorithm),
+ &src_desc.data,
+ &diff_weights_desc.data,
+ nullptr,
+ &diff_dst_desc.data,
+ &strides[0],
+ &padding_l[0],
+ &padding_r[0],
+ mkldnn::convert_to_c(apadding_kind)),
+ "could not create a convolution backward weights descriptor");
+ }
+ desc(algorithm aalgorithm,
+ const memory::desc &src_desc,
+ const memory::desc &diff_weights_desc,
+ const memory::desc &diff_bias_desc,
+ const memory::desc &diff_dst_desc,
+ const memory::dims strides,
+ const memory::dims dilates,
+ const memory::dims padding_l,
+ const memory::dims padding_r,
+ const padding_kind apadding_kind) {
+ memory::validate_dims(strides);
+ memory::validate_dims(dilates);
+ memory::validate_dims(padding_l);
+ memory::validate_dims(padding_r);
+ error::wrap_c_api(
+ mkldnn_dilated_convolution_backward_weights_desc_init(
+ &data,
+ convert_to_c(aalgorithm),
+ &src_desc.data,
+ &diff_weights_desc.data,
+ &diff_bias_desc.data,
+ &diff_dst_desc.data,
+ &strides[0],
+ &dilates[0],
+ &padding_l[0],
+ &padding_r[0],
+ mkldnn::convert_to_c(apadding_kind)),
+ "could not create a convolution backward weights descriptor");
+ }
+ desc(algorithm aalgorithm,
+ const memory::desc &src_desc,
+ const memory::desc &diff_weights_desc,
+ const memory::desc &diff_dst_desc,
+ const memory::dims strides,
+ const memory::dims dilates,
+ const memory::dims padding_l,
+ const memory::dims padding_r,
+ const padding_kind apadding_kind) {
+ memory::validate_dims(strides);
+ memory::validate_dims(dilates);
+ memory::validate_dims(padding_l);
+ memory::validate_dims(padding_r);
+ error::wrap_c_api(
+ mkldnn_dilated_convolution_backward_weights_desc_init(
+ &data,
+ convert_to_c(aalgorithm),
+ &src_desc.data,
+ &diff_weights_desc.data,
+ nullptr,
+ &diff_dst_desc.data,
+ &strides[0],
+ &dilates[0],
+ &padding_l[0],
+ &padding_r[0],
+ mkldnn::convert_to_c(apadding_kind)),
+ "could not create a convolution backward weights descriptor");
+ }
+ };
+
+ struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
+ primitive_desc(
+ const desc &adesc,
+ const engine &aengine,
+ const convolution_forward::primitive_desc &hint_fwd_primitive_desc) {
+ mkldnn_primitive_desc_t result;
+ error::wrap_c_api(
+ mkldnn_primitive_desc_create(&result,
+ &adesc.data,
+ aengine.get(),
+ hint_fwd_primitive_desc.get()),
+ "could not create a convolution backward weights primitive "
+ "descriptor");
+ reset(result);
+ }
+ memory::primitive_desc src_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t cdesc;
+ const_mkldnn_primitive_desc_t const_cdesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(src_pd), 0);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
+ "could not clone a src primititve descriptor");
+ adesc.reset(cdesc);
+ return adesc;
+ }
+
+ memory::primitive_desc diff_weights_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t cdesc;
+ const_mkldnn_primitive_desc_t const_cdesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(diff_weights_pd), 0);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
+ "could not clone a diff_weights primitive descriptor");
+ adesc.reset(cdesc);
+ return adesc;
+ }
+
+ memory::primitive_desc diff_bias_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t cdesc;
+ const_mkldnn_primitive_desc_t const_cdesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(diff_weights_pd), 1);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
+ "could not clone a diff_bias primitive descriptor");
+ adesc.reset(cdesc);
+ return adesc;
+ }
+
+ memory::primitive_desc diff_dst_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t cdesc;
+ const_mkldnn_primitive_desc_t const_cdesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(diff_dst_pd), 0);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
+ "could not clone a diff_dst primitive descriptor");
+ adesc.reset(cdesc);
+ return adesc;
+ }
+
+ engine get_engine() { return engine::query(*this); }
+ };
+
+ convolution_backward_weights(const primitive_desc &aprimitive_desc,
+ const primitive::at &src,
+ const primitive::at &diff_dst,
+ const memory &diff_weights,
+ const memory &diff_bias) {
+ mkldnn_primitive_t result;
+ mkldnn_primitive_at_t inputs[] = {src.data, diff_dst.data};
+ const_mkldnn_primitive_t outputs[] = {diff_weights.get(), diff_bias.get()};
+ error::wrap_c_api(
+ mkldnn_primitive_create(
+ &result, aprimitive_desc.get(), inputs, outputs),
+ "could not create a convolution backward weights primitive");
+ reset(result);
+ }
+ convolution_backward_weights(const primitive_desc &aprimitive_desc,
+ const primitive::at &src,
+ const primitive::at &diff_dst,
+ const memory &diff_weights) {
+ mkldnn_primitive_t result;
+ mkldnn_primitive_at_t inputs[] = {src.data, diff_dst.data};
+ const_mkldnn_primitive_t outputs[] = {diff_weights.get()};
+ error::wrap_c_api(
+ mkldnn_primitive_create(
+ &result, aprimitive_desc.get(), inputs, outputs),
+ "could not create a convolution backward weights primitive");
+ reset(result);
+ }
+};
+
+struct convolution_relu_forward : public primitive {
+ struct desc {
+ mkldnn_convolution_relu_desc_t data;
+ desc(const convolution_forward::desc conv_desc,
+ const float negative_slope) {
+ error::wrap_c_api(
+ mkldnn_convolution_relu_desc_init(
+ &data, &conv_desc.data, negative_slope),
+ "could not create a convolution_relu_forward descriptor");
+ }
+ };
+
+ struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
+ primitive_desc(const desc &adesc, const engine &aengine) {
+ mkldnn_primitive_desc_t result;
+ error::wrap_c_api(
+ mkldnn_primitive_desc_create(
+ &result, &adesc.data, aengine.get(), nullptr),
+ "could not create a convolution relu forward descriptor");
+ reset(result);
+ }
+
+ engine get_engine() { return engine::query(*this); }
+ };
+
+ convolution_relu_forward(const primitive_desc &aprimitive_desc,
+ const primitive::at &src,
+ const primitive::at &weights,
+ const primitive::at &bias,
+ const memory &dst) {
+ mkldnn_primitive_t result;
+ mkldnn_primitive_at_t inputs[] = {src.data, weights.data, bias.data};
+ const_mkldnn_primitive_t outputs[] = {dst.get()};
+ error::wrap_c_api(mkldnn_primitive_create(
+ &result, aprimitive_desc.get(), inputs, outputs),
+ "could not create a convolution relu forward primitive");
+ reset(result);
+ }
+
+ convolution_relu_forward(const primitive_desc &aprimitive_desc,
+ const primitive::at &src,
+ const primitive::at &weights,
+ const memory &dst) {
+ mkldnn_primitive_t result;
+ mkldnn_primitive_at_t inputs[] = {src.data, weights.data};
+ const_mkldnn_primitive_t outputs[] = {dst.get()};
+ error::wrap_c_api(mkldnn_primitive_create(
+ &result, aprimitive_desc.get(), inputs, outputs),
+ "could not create a convolution relu forward primitive");
+ reset(result);
+ }
+};
+
+/// @}
+//
+/// @addtogroup cpp_api_deconvolution Deconvolution
+/// @{
+
+struct deconvolution_forward : public primitive {
+ struct desc {
+ mkldnn_deconvolution_desc_t data;
+ desc(prop_kind aprop_kind,
+ algorithm aalgorithm,
+ const memory::desc &src_desc,
+ const memory::desc &weights_desc,
+ const memory::desc &bias_desc,
+ const memory::desc &dst_desc,
+ const memory::dims strides,
+ const memory::dims padding_l,
+ const memory::dims padding_r,
+ const padding_kind apadding_kind) {
+ memory::validate_dims(strides);
+ memory::validate_dims(padding_l);
+ memory::validate_dims(padding_r);
+ error::wrap_c_api(mkldnn_deconvolution_forward_desc_init(
+ &data,
+ mkldnn::convert_to_c(aprop_kind),
+ convert_to_c(aalgorithm),
+ &src_desc.data,
+ &weights_desc.data,
+ &bias_desc.data,
+ &dst_desc.data,
+ &strides[0],
+ &padding_l[0],
+ &padding_r[0],
+ mkldnn::convert_to_c(apadding_kind)),
+ "could not create a deconvolution forward descriptor");
+ }
+ desc(prop_kind aprop_kind,
+ algorithm aalgorithm,
+ const memory::desc &src_desc,
+ const memory::desc &weights_desc,
+ const memory::desc &dst_desc,
+ const memory::dims strides,
+ const memory::dims padding_l,
+ const memory::dims padding_r,
+ const padding_kind apadding_kind) {
+ memory::validate_dims(strides);
+ memory::validate_dims(padding_l);
+ memory::validate_dims(padding_r);
+ error::wrap_c_api(mkldnn_deconvolution_forward_desc_init(
+ &data,
+ mkldnn::convert_to_c(aprop_kind),
+ convert_to_c(aalgorithm),
+ &src_desc.data,
+ &weights_desc.data,
+ nullptr,
+ &dst_desc.data,
+ &strides[0],
+ &padding_l[0],
+ &padding_r[0],
+ mkldnn::convert_to_c(apadding_kind)),
+ "could not create a deconvolution forward descriptor");
+ }
+ };
+ struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
+ primitive_desc(const desc &adesc, const engine &aengine) {
+ mkldnn_primitive_desc_t result;
+ error::wrap_c_api(
+ mkldnn_primitive_desc_create(
+ &result, &adesc.data, aengine.get(), nullptr),
+ "could not create a deconvolution forward primitive descriptor");
+ reset(result);
+ }
+
+ primitive_desc(const desc &adesc,
+ const primitive_attr &aattr,
+ const engine &aengine) {
+ mkldnn_primitive_desc_t result;
+ error::wrap_c_api(
+ mkldnn_primitive_desc_create_v2(
+ &result, &adesc.data, aattr.get(), aengine.get(), nullptr),
+ "could not create a deconvolution forward primitive descriptor");
+ reset(result);
+ }
+
+ memory::primitive_desc src_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t cdesc;
+ const_mkldnn_primitive_desc_t const_cdesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(src_pd), 0);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
+ "could not clone a src primititve descriptor");
+ adesc.reset(cdesc);
+ return adesc;
+ }
+
+ memory::primitive_desc weights_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t cdesc;
+ const_mkldnn_primitive_desc_t const_cdesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(weights_pd), 0);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
+ "could not clone a weights primitive descriptor");
+ adesc.reset(cdesc);
+ return adesc;
+ }
+
+ memory::primitive_desc bias_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t cdesc;
+ const_mkldnn_primitive_desc_t const_cdesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(weights_pd), 1);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
+ "could not clone a bias primitive descriptor");
+ adesc.reset(cdesc);
+ return adesc;
+ }
+
+ memory::primitive_desc dst_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t cdesc;
+ const_mkldnn_primitive_desc_t const_cdesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(dst_pd), 0);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
+ "could not clone a dst primitive descriptor");
+ adesc.reset(cdesc);
+ return adesc;
+ }
+
+ engine get_engine() { return engine::query(*this); }
+ };
+
+ deconvolution_forward(const primitive_desc &aprimitive_desc,
+ const primitive::at &src,
+ const primitive::at &weights,
+ const primitive::at &bias,
+ const memory &dst) {
+ mkldnn_primitive_t result;
+ mkldnn_primitive_at_t inputs[] = {src.data, weights.data, bias.data};
+ const_mkldnn_primitive_t outputs[] = {dst.get()};
+ error::wrap_c_api(
+ mkldnn_primitive_create(
+ &result, aprimitive_desc.get(), inputs, outputs),
+ "could not create a deconvolution forward bias primitive");
+ reset(result);
+ }
+
+ deconvolution_forward(const primitive_desc &aprimitive_desc,
+ const primitive::at &src,
+ const primitive::at &weights,
+ const memory &dst) {
+ mkldnn_primitive_t result;
+ mkldnn_primitive_at_t inputs[] = {src.data, weights.data};
+ const_mkldnn_primitive_t outputs[] = {dst.get()};
+ error::wrap_c_api(mkldnn_primitive_create(
+ &result, aprimitive_desc.get(), inputs, outputs),
+ "could not create a deconvolution forward primitive");
+ reset(result);
+ }
+};
+
+struct deconvolution_backward_data : public primitive {
+ struct desc {
+ mkldnn_deconvolution_desc_t data;
+ desc(algorithm aalgorithm,
+ const memory::desc &diff_src_desc,
+ const memory::desc &weights_desc,
+ const memory::desc &diff_dst_desc,
+ const memory::dims strides,
+ const memory::dims padding_l,
+ const memory::dims padding_r,
+ const padding_kind apadding_kind) {
+ memory::validate_dims(strides);
+ memory::validate_dims(padding_l);
+ memory::validate_dims(padding_r);
+ error::wrap_c_api(
+ mkldnn_deconvolution_backward_data_desc_init(
+ &data,
+ convert_to_c(aalgorithm),
+ &diff_src_desc.data,
+ &weights_desc.data,
+ &diff_dst_desc.data,
+ &strides[0],
+ &padding_l[0],
+ &padding_r[0],
+ mkldnn::convert_to_c(apadding_kind)),
+ "could not create a deconvolution backward data descriptor");
+ }
+ };
+ struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
+ primitive_desc(
+ const desc &adesc,
+ const engine &aengine,
+ const deconvolution_forward::primitive_desc &hint_fwd_primitive_desc) {
+ mkldnn_primitive_desc_t result;
+ error::wrap_c_api(
+ mkldnn_primitive_desc_create(&result,
+ &adesc.data,
+ aengine.get(),
+ hint_fwd_primitive_desc.get()),
+ "could not create a deconvolution backward data primitive "
+ "descriptor");
+ reset(result);
+ }
+ memory::primitive_desc diff_src_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t cdesc;
+ const_mkldnn_primitive_desc_t const_cdesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(diff_src_pd), 0);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
+ "could not clone a diff_src primititve descriptor");
+ adesc.reset(cdesc);
+ return adesc;
+ }
+
+ memory::primitive_desc weights_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t cdesc;
+ const_mkldnn_primitive_desc_t const_cdesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(weights_pd), 0);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
+ "could not clone a weights primitive descriptor");
+ adesc.reset(cdesc);
+ return adesc;
+ }
+
+ memory::primitive_desc diff_dst_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t cdesc;
+ const_mkldnn_primitive_desc_t const_cdesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(diff_dst_pd), 0);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
+ "could not clone a diff_dst primitive descriptor");
+ adesc.reset(cdesc);
+ return adesc;
+ }
+
+ engine get_engine() { return engine::query(*this); }
+ };
+
+ deconvolution_backward_data(const primitive_desc &aprimitive_desc,
+ const primitive::at &diff_dst,
+ const primitive::at &weights,
+ const memory &diff_src) {
+ mkldnn_primitive_t result;
+ mkldnn_primitive_at_t inputs[] = {diff_dst.data, weights.data};
+ const_mkldnn_primitive_t outputs[] = {diff_src.get()};
+ error::wrap_c_api(
+ mkldnn_primitive_create(
+ &result, aprimitive_desc.get(), inputs, outputs),
+ "could not create a deconvolution backward data primitive");
+ reset(result);
+ }
+};
+
+struct deconvolution_backward_weights : public primitive {
+ struct desc {
+ mkldnn_deconvolution_desc_t data;
+ desc(algorithm aalgorithm,
+ const memory::desc &src_desc,
+ const memory::desc &diff_weights_desc,
+ const memory::desc &diff_bias_desc,
+ const memory::desc &diff_dst_desc,
+ const memory::dims strides,
+ const memory::dims padding_l,
+ const memory::dims padding_r,
+ const padding_kind apadding_kind) {
+ memory::validate_dims(strides);
+ memory::validate_dims(padding_l);
+ memory::validate_dims(padding_r);
+ error::wrap_c_api(
+ mkldnn_deconvolution_backward_weights_desc_init(
+ &data,
+ convert_to_c(aalgorithm),
+ &src_desc.data,
+ &diff_weights_desc.data,
+ &diff_bias_desc.data,
+ &diff_dst_desc.data,
+ &strides[0],
+ &padding_l[0],
+ &padding_r[0],
+ mkldnn::convert_to_c(apadding_kind)),
+ "could not create a deconvolution backward weights descriptor");
+ }
+ desc(algorithm aalgorithm,
+ const memory::desc &src_desc,
+ const memory::desc &diff_weights_desc,
+ const memory::desc &diff_dst_desc,
+ const memory::dims strides,
+ const memory::dims padding_l,
+ const memory::dims padding_r,
+ const padding_kind apadding_kind) {
+ memory::validate_dims(strides);
+ memory::validate_dims(padding_l);
+ memory::validate_dims(padding_r);
+ error::wrap_c_api(
+ mkldnn_deconvolution_backward_weights_desc_init(
+ &data,
+ convert_to_c(aalgorithm),
+ &src_desc.data,
+ &diff_weights_desc.data,
+ nullptr,
+ &diff_dst_desc.data,
+ &strides[0],
+ &padding_l[0],
+ &padding_r[0],
+ mkldnn::convert_to_c(apadding_kind)),
+ "could not create a deconvolution backward weights descriptor");
+ }
+ };
+
+ struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
+ primitive_desc(
+ const desc &adesc,
+ const engine &aengine,
+ const deconvolution_forward::primitive_desc &hint_fwd_primitive_desc) {
+ mkldnn_primitive_desc_t result;
+ error::wrap_c_api(
+ mkldnn_primitive_desc_create(&result,
+ &adesc.data,
+ aengine.get(),
+ hint_fwd_primitive_desc.get()),
+ "could not create a deconvolution backward weights primitive "
+ "descriptor");
+ reset(result);
+ }
+ memory::primitive_desc src_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t cdesc;
+ const_mkldnn_primitive_desc_t const_cdesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(src_pd), 0);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
+ "could not clone a src primititve descriptor");
+ adesc.reset(cdesc);
+ return adesc;
+ }
+
+ memory::primitive_desc diff_weights_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t cdesc;
+ const_mkldnn_primitive_desc_t const_cdesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(diff_weights_pd), 0);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
+ "could not clone a diff_weights primitive descriptor");
+ adesc.reset(cdesc);
+ return adesc;
+ }
+
+ memory::primitive_desc diff_bias_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t cdesc;
+ const_mkldnn_primitive_desc_t const_cdesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(diff_weights_pd), 1);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
+ "could not clone a diff_bias primitive descriptor");
+ adesc.reset(cdesc);
+ return adesc;
+ }
+
+ memory::primitive_desc diff_dst_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t cdesc;
+ const_mkldnn_primitive_desc_t const_cdesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(diff_dst_pd), 0);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
+ "could not clone a diff_dst primitive descriptor");
+ adesc.reset(cdesc);
+ return adesc;
+ }
+
+ engine get_engine() { return engine::query(*this); }
+ };
+
+ deconvolution_backward_weights(const primitive_desc &aprimitive_desc,
+ const primitive::at &src,
+ const primitive::at &diff_dst,
+ const memory &diff_weights,
+ const memory &diff_bias) {
+ mkldnn_primitive_t result;
+ mkldnn_primitive_at_t inputs[] = {src.data, diff_dst.data};
+ const_mkldnn_primitive_t outputs[] = {diff_weights.get(), diff_bias.get()};
+ error::wrap_c_api(
+ mkldnn_primitive_create(
+ &result, aprimitive_desc.get(), inputs, outputs),
+ "could not create a deconvolution backward weights primitive");
+ reset(result);
+ }
+ deconvolution_backward_weights(const primitive_desc &aprimitive_desc,
+ const primitive::at &src,
+ const primitive::at &diff_dst,
+ const memory &diff_weights) {
+ mkldnn_primitive_t result;
+ mkldnn_primitive_at_t inputs[] = {src.data, diff_dst.data};
+ const_mkldnn_primitive_t outputs[] = {diff_weights.get()};
+ error::wrap_c_api(
+ mkldnn_primitive_create(
+ &result, aprimitive_desc.get(), inputs, outputs),
+ "could not create a deconvolution backward weights primitive");
+ reset(result);
+ }
+};
+
+/// @}
+
+/// @addtogroup cpp_api_lrn LRN
+/// @{
+
+struct lrn_forward : public primitive {
+ struct desc {
+ mkldnn_lrn_desc_t data;
+ desc(prop_kind aprop_kind,
+ algorithm aalgorithm,
+ const memory::desc &src_desc,
+ int local_size,
+ float alpha,
+ float beta,
+ float k) {
+ error::wrap_c_api(
+ mkldnn_lrn_forward_desc_init(&data,
+ mkldnn::convert_to_c(aprop_kind),
+ convert_to_c(aalgorithm),
+ &src_desc.data,
+ local_size,
+ alpha,
+ beta,
+ k),
+ "could not create a lrn forward descriptor");
+ }
+ desc(prop_kind aprop_kind,
+ algorithm aalgorithm,
+ const memory::desc &src_desc,
+ int local_size,
+ float alpha,
+ float beta) {
+ error::wrap_c_api(
+ mkldnn_lrn_forward_desc_init(&data,
+ mkldnn::convert_to_c(aprop_kind),
+ convert_to_c(aalgorithm),
+ &src_desc.data,
+ local_size,
+ alpha,
+ beta,
+ float(1.0)),
+ "could not create a lrn forward descriptor");
+ }
+ };
+
+ struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
+ primitive_desc(const desc &adesc, const engine &aengine) {
+ mkldnn_primitive_desc_t result;
+ error::wrap_c_api(mkldnn_primitive_desc_create(
+ &result, &adesc.data, aengine.get(), nullptr),
+ "could not create a lrn forward primitive descriptor");
+ reset(result);
+ }
+
+ memory::primitive_desc src_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t cdesc;
+ const_mkldnn_primitive_desc_t const_cdesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(src_pd), 0);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
+ "could not clone a src primitive descriptor");
+ adesc.reset(cdesc);
+ return adesc;
+ }
+
+ memory::primitive_desc workspace_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t ldesc;
+ const_mkldnn_primitive_desc_t const_ldesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(workspace_pd), 0);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&ldesc, const_ldesc),
+ "could not clone a workspace primitive descriptor");
+ adesc.reset(ldesc);
+ return adesc;
+ }
+
+ memory::primitive_desc dst_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t cdesc;
+ const_mkldnn_primitive_desc_t const_cdesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(dst_pd), 0);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
+ "could not clone a dst primitive descriptor");
+ adesc.reset(cdesc);
+ return adesc;
+ }
+
+ engine get_engine() { return engine::query(*this); }
+ };
+
+ lrn_forward(const primitive_desc &aprimitive_desc,
+ const primitive::at &src,
+ const memory &workspace,
+ const memory &dst) {
+ mkldnn_primitive_t result;
+ mkldnn_primitive_at_t inputs[] = {src.data};
+ const_mkldnn_primitive_t outputs[] = {dst.get(), workspace.get()};
+ error::wrap_c_api(mkldnn_primitive_create(
+ &result, aprimitive_desc.get(), inputs, outputs),
+ "could not create a lrn forward primitive");
+ reset(result);
+ }
+
+ lrn_forward(const primitive_desc &aprimitive_desc,
+ const primitive::at &src,
+ const memory &dst) {
+ mkldnn_primitive_t result;
+ mkldnn_primitive_at_t inputs[] = {src.data};
+ const_mkldnn_primitive_t outputs[] = {dst.get()};
+ error::wrap_c_api(mkldnn_primitive_create(
+ &result, aprimitive_desc.get(), inputs, outputs),
+ "could not create a lrn forward primitive");
+ reset(result);
+ }
+};
+
+struct lrn_backward : public primitive {
+ struct desc {
+ mkldnn_lrn_desc_t data;
+ desc(algorithm aalgorithm,
+ const memory::desc &data_desc,
+ const memory::desc &diff_data_desc,
+ int local_size,
+ float alpha,
+ float beta,
+ float k) {
+ error::wrap_c_api(mkldnn_lrn_backward_desc_init(&data,
+ convert_to_c(aalgorithm),
+ &diff_data_desc.data,
+ &data_desc.data,
+ local_size,
+ alpha,
+ beta,
+ k),
+ "could not create a lrn backward descriptor");
+ }
+ desc(algorithm aalgorithm,
+ const memory::desc &data_desc,
+ const memory::desc &diff_data_desc,
+ int local_size,
+ float alpha,
+ float beta) {
+ error::wrap_c_api(mkldnn_lrn_backward_desc_init(&data,
+ convert_to_c(aalgorithm),
+ &diff_data_desc.data,
+ &data_desc.data,
+ local_size,
+ alpha,
+ beta,
+ float(1.0)),
+ "could not create a lrn backward descriptor");
+ }
+ };
+
+ struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
+ primitive_desc(const desc &adesc,
+ const engine &aengine,
+ const lrn_forward::primitive_desc &hint_fwd_primitive_desc) {
+ mkldnn_primitive_desc_t result;
+ error::wrap_c_api(
+ mkldnn_primitive_desc_create(&result,
+ &adesc.data,
+ aengine.get(),
+ hint_fwd_primitive_desc.get()),
+ "could not create a backward lrn primitive descriptor");
+ reset(result);
+ }
+
+ memory::primitive_desc diff_src_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t cdesc;
+ const_mkldnn_primitive_desc_t const_cdesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(diff_src_pd), 0);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
+ "could not clone a diff_src primitive descriptor");
+ adesc.reset(cdesc);
+ return adesc;
+ }
+
+ memory::primitive_desc workspace_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t ldesc;
+ const_mkldnn_primitive_desc_t const_ldesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(workspace_pd), 0);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&ldesc, const_ldesc),
+ "could not clone a workspace primitive descriptor");
+ adesc.reset(ldesc);
+ return adesc;
+ }
+
+ memory::primitive_desc diff_dst_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t cdesc;
+ const_mkldnn_primitive_desc_t const_cdesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(diff_dst_pd), 0);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
+ "could not clone a diff_dst primitive descriptor");
+ adesc.reset(cdesc);
+ return adesc;
+ }
+
+ engine get_engine() { return engine::query(*this); }
+ };
+
+ lrn_backward(const primitive_desc &aprimitive_desc,
+ const primitive::at &src,
+ const primitive::at &diff_dst,
+ const primitive::at &workspace,
+ const memory &diff_src) {
+ mkldnn_primitive_t result;
+ mkldnn_primitive_at_t inputs[] = {src.data, diff_dst.data, workspace.data};
+ const_mkldnn_primitive_t outputs[] = {diff_src.get()};
+ error::wrap_c_api(mkldnn_primitive_create(
+ &result, aprimitive_desc.get(), inputs, outputs),
+ "could not create a lrn backward primitive");
+ reset(result);
+ }
+
+ lrn_backward(const primitive_desc &aprimitive_desc,
+ const primitive::at &src,
+ const primitive::at &diff_dst,
+ const memory &diff_src) {
+ mkldnn_primitive_t result;
+ mkldnn_primitive_at_t inputs[] = {src.data, diff_dst.data};
+ const_mkldnn_primitive_t outputs[] = {diff_src.get()};
+ error::wrap_c_api(mkldnn_primitive_create(
+ &result, aprimitive_desc.get(), inputs, outputs),
+ "could not create a lrn backward primitive");
+ reset(result);
+ }
+};
+
+/// @}
+
+/// @addtogroup cpp_api_pooling Pooling
+/// @{
+
+struct pooling_forward : public primitive {
+ struct desc {
+ mkldnn_pooling_desc_t data;
+ desc(prop_kind aprop_kind,
+ algorithm aalgorithm,
+ const memory::desc &src_desc,
+ const memory::desc &dst_desc,
+ const memory::dims strides,
+ const memory::dims kernel,
+ const memory::dims padding_l,
+ const memory::dims padding_r,
+ const padding_kind apadding_kind) {
+ memory::validate_dims(strides);
+ memory::validate_dims(kernel);
+ memory::validate_dims(padding_l);
+ memory::validate_dims(padding_r);
+ error::wrap_c_api(
+ mkldnn_pooling_forward_desc_init(&data,
+ mkldnn::convert_to_c(aprop_kind),
+ convert_to_c(aalgorithm),
+ &src_desc.data,
+ &dst_desc.data,
+ &strides[0],
+ &kernel[0],
+ &padding_l[0],
+ &padding_r[0],
+ mkldnn::convert_to_c(apadding_kind)),
+ "could not init a forward pooling descriptor");
+ }
+ };
+
+ struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
+ primitive_desc(const desc &adesc, const engine &aengine) {
+ mkldnn_primitive_desc_t result;
+ error::wrap_c_api(
+ mkldnn_primitive_desc_create(
+ &result, &adesc.data, aengine.get(), nullptr),
+ "could not create a forward pooling primitive descriptor");
+ reset(result);
+ }
+
+ memory::primitive_desc workspace_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t cdesc;
+ const_mkldnn_primitive_desc_t const_cdesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(workspace_pd), 0);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
+ "could not clone a workspace primititve descriptor");
+ adesc.reset(cdesc);
+ return adesc;
+ }
+
+ memory::primitive_desc dst_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t cdesc;
+ const_mkldnn_primitive_desc_t const_cdesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(dst_pd), 0);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
+ "could not clone a dst primitive descriptor");
+ adesc.reset(cdesc);
+ return adesc;
+ }
+
+ engine get_engine() { return engine::query(*this); }
+ };
+
+ pooling_forward(const primitive_desc &aprimitive_desc,
+ const primitive::at &src,
+ const memory &dst) {
+ mkldnn_primitive_t result;
+ mkldnn_primitive_at_t inputs[] = {src.data};
+ const_mkldnn_primitive_t outputs[] = {dst.get(), nullptr};
+ error::wrap_c_api(mkldnn_primitive_create(
+ &result, aprimitive_desc.get(), inputs, outputs),
+ "could not create a pooling forward primitive");
+ reset(result);
+ }
+
+ pooling_forward(const primitive_desc &aprimitive_desc,
+ const primitive::at &src,
+ const memory &dst,
+ const memory &workspace) {
+ mkldnn_primitive_t result;
+ mkldnn_primitive_at_t inputs[] = {src.data};
+ const_mkldnn_primitive_t outputs[] = {dst.get(), workspace.get()};
+ error::wrap_c_api(mkldnn_primitive_create(
+ &result, aprimitive_desc.get(), inputs, outputs),
+ "could not create a pooling forward primitive");
+ reset(result);
+ }
+};
+
+struct pooling_backward : public primitive {
+ struct desc {
+ mkldnn_pooling_desc_t data;
+ desc(algorithm aalgorithm,
+ const memory::desc &diff_src_desc,
+ const memory::desc &diff_dst_desc,
+ const memory::dims &strides,
+ const memory::dims &kernel,
+ const memory::dims &padding_l,
+ const memory::dims &padding_r,
+ const padding_kind apadding_kind) {
+ memory::validate_dims(strides);
+ memory::validate_dims(kernel);
+ memory::validate_dims(padding_l);
+ memory::validate_dims(padding_r);
+ error::wrap_c_api(mkldnn_pooling_backward_desc_init(
+ &data,
+ convert_to_c(aalgorithm),
+ &diff_src_desc.data,
+ &diff_dst_desc.data,
+ &strides[0],
+ &kernel[0],
+ &padding_l[0],
+ &padding_r[0],
+ mkldnn::convert_to_c(apadding_kind)),
+ "could not init a backward pooling descriptor");
+ }
+ };
+
+ struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
+ primitive_desc(
+ const desc &adesc,
+ const engine &aengine,
+ const pooling_forward::primitive_desc &hint_fwd_primitive_desc) {
+ mkldnn_primitive_desc_t result;
+ error::wrap_c_api(
+ mkldnn_primitive_desc_create(&result,
+ &adesc.data,
+ aengine.get(),
+ hint_fwd_primitive_desc.get()),
+ "could not create a backward pooling primitive descriptor");
+ reset(result);
+ }
+
+ memory::primitive_desc diff_src_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t cdesc;
+ const_mkldnn_primitive_desc_t const_cdesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(diff_src_pd), 0);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
+ "could not clone a diff src primitive descriptor");
+ adesc.reset(cdesc);
+ return adesc;
+ }
+
+ engine get_engine() { return engine::query(*this); }
+ };
+
+ pooling_backward(const primitive_desc &aprimitive_desc,
+ const primitive::at &diff_dst,
+ const memory &diff_src) {
+ mkldnn_primitive_t result;
+ mkldnn_primitive_at_t inputs[] = {diff_dst.data};
+ const_mkldnn_primitive_t outputs[] = {diff_src.get()};
+ error::wrap_c_api(mkldnn_primitive_create(
+ &result, aprimitive_desc.get(), inputs, outputs),
+ "could not create a pooling backward primitive");
+ reset(result);
+ }
+
+ pooling_backward(const primitive_desc &aprimitive_desc,
+ const primitive::at &diff_dst,
+ const primitive::at &workspace,
+ const memory &diff_src) {
+ mkldnn_primitive_t result;
+ mkldnn_primitive_at_t inputs[] = {diff_dst.data, workspace.data};
+ const_mkldnn_primitive_t outputs[] = {diff_src.get()};
+ error::wrap_c_api(mkldnn_primitive_create(
+ &result, aprimitive_desc.get(), inputs, outputs),
+ "could not create a pooling backward primitive");
+ reset(result);
+ }
+};
+
+/// @}
+
+/// @addtogroup cpp_api_eltwise Eltwise
+/// @{
+
+struct eltwise_forward : public primitive {
+ struct desc {
+ mkldnn_eltwise_desc_t data;
+ template <typename T>
+ desc(prop_kind aprop_kind,
+ algorithm alg_kind,
+ const memory::desc &src_desc,
+ T alpha = 0,
+ T beta = 0) {
+ error::wrap_c_api(
+ mkldnn_eltwise_forward_desc_init(&data,
+ mkldnn::convert_to_c(aprop_kind),
+ mkldnn::convert_to_c(alg_kind),
+ &src_desc.data,
+ static_cast<float>(alpha),
+ static_cast<float>(beta)),
+ "could not create a eltwise forward descriptor");
+ }
+
+ /** @deprecated: api backward compatibility for relu */
+ template <typename T>
+ MKLDNN_DEPRECATED desc(prop_kind aprop_kind,
+ const memory::desc &src_desc,
+ T negative_slope)
+ : desc(aprop_kind, eltwise_relu, src_desc, negative_slope) {}
+ };
+
+ struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
+ primitive_desc(const desc &adesc, const engine &aengine) {
+ mkldnn_primitive_desc_t result;
+ error::wrap_c_api(
+ mkldnn_primitive_desc_create(
+ &result, &adesc.data, aengine.get(), nullptr),
+ "could not create a eltwise forward primitive descriptor");
+ reset(result);
+ }
+
+ memory::primitive_desc dst_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t cdesc;
+ const_mkldnn_primitive_desc_t const_cdesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(dst_pd), 0);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
+ "could not clone a dst primitive descriptor");
+ adesc.reset(cdesc);
+ return adesc;
+ }
+
+ engine get_engine() { return engine::query(*this); }
+ };
+
+ eltwise_forward(const primitive_desc &aprimitive_desc,
+ const primitive::at &src,
+ const memory &dst) {
+ mkldnn_primitive_t result;
+ mkldnn_primitive_at_t inputs[] = {src.data};
+ const_mkldnn_primitive_t outputs[] = {dst.get()};
+ error::wrap_c_api(mkldnn_primitive_create(
+ &result, aprimitive_desc.get(), inputs, outputs),
+ "could not create a eltwise forward primitive");
+ reset(result);
+ }
+};
+
+typedef eltwise_forward relu_forward;
+
+struct eltwise_backward : public primitive {
+ struct desc {
+ mkldnn_eltwise_desc_t data;
+
+ template <typename T>
+ desc(algorithm alg_kind,
+ const memory::desc &diff_data_desc,
+ const memory::desc &data_desc,
+ T alpha = 0,
+ T beta = 0) {
+ error::wrap_c_api(
+ mkldnn_eltwise_backward_desc_init(&data,
+ mkldnn::convert_to_c(alg_kind),
+ &diff_data_desc.data,
+ &data_desc.data,
+ static_cast<float>(alpha),
+ static_cast<float>(beta)),
+ "could not create a eltwise backward descriptor");
+ }
+
+ /** @deprecated: api backward compatibility for relu */
+ template <typename T>
+ MKLDNN_DEPRECATED desc(const memory::desc &diff_data_desc,
+ const memory::desc &data_desc,
+ T negative_slope)
+ : desc(eltwise_relu, diff_data_desc, data_desc, negative_slope) {}
+ };
+
+ struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
+ primitive_desc(
+ const desc &adesc,
+ const engine &aengine,
+ const eltwise_forward::primitive_desc &hint_fwd_primitive_desc) {
+ mkldnn_primitive_desc_t result;
+ error::wrap_c_api(
+ mkldnn_primitive_desc_create(&result,
+ &adesc.data,
+ aengine.get(),
+ hint_fwd_primitive_desc.get()),
+ "could not create a eltwise backward primitive descriptor");
+ reset(result);
+ }
+
+ memory::primitive_desc diff_src_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t cdesc;
+ const_mkldnn_primitive_desc_t const_cdesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(diff_src_pd), 0);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
+ "could not clone a diff src primitive descriptor");
+ adesc.reset(cdesc);
+ return adesc;
+ }
+
+ engine get_engine() { return engine::query(*this); }
+ };
+
+ eltwise_backward(const primitive_desc &aprimitive_desc,
+ const primitive::at &src,
+ const primitive::at &diff_dst,
+ const memory &diff_src) {
+ mkldnn_primitive_t result;
+ mkldnn_primitive_at_t inputs[] = {src.data, diff_dst.data};
+ const_mkldnn_primitive_t outputs[] = {diff_src.get()};
+ error::wrap_c_api(mkldnn_primitive_create(
+ &result, aprimitive_desc.get(), inputs, outputs),
+ "could not create a eltwise backward primitive");
+ reset(result);
+ }
+};
+
+typedef eltwise_backward relu_backward;
+
+/// @}
+
+/// @addtogroup cpp_api_softmax Softmax
+/// @{
+
+struct softmax_forward : public primitive {
+ struct desc {
+ mkldnn_softmax_desc_t data;
+ desc(prop_kind aprop_kind,
+ const memory::desc &data_desc,
+ int softmax_axis) {
+ error::wrap_c_api(
+ mkldnn_softmax_forward_desc_init(&data,
+ mkldnn::convert_to_c(aprop_kind),
+ &data_desc.data,
+ softmax_axis),
+ "could not create a softmax forward descriptor");
+ }
+ };
+
+ struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
+ primitive_desc(const desc &adesc, const engine &aengine) {
+ mkldnn_primitive_desc_t result;
+ error::wrap_c_api(
+ mkldnn_primitive_desc_create(
+ &result, &adesc.data, aengine.get(), nullptr),
+ "could not create a softmax forward primitive descriptor");
+ reset(result);
+ }
+
+ engine get_engine() { return engine::query(*this); }
+ };
+
+ softmax_forward(const primitive_desc &aprimitive_desc,
+ const primitive::at &src,
+ const memory &dst) {
+ mkldnn_primitive_t result;
+ mkldnn_primitive_at_t inputs[] = {src.data};
+ const_mkldnn_primitive_t outputs[] = {dst.get()};
+ error::wrap_c_api(mkldnn_primitive_create(
+ &result, aprimitive_desc.get(), inputs, outputs),
+ "could not create a softmax forward primitive");
+ reset(result);
+ }
+};
+
+/// @}
+
+/// @addtogroup cpp_api_batch_norm Batch normalization
+/// @{
+
+struct batch_normalization_forward : public primitive {
+ struct desc {
+ mkldnn_batch_normalization_desc_t data;
+ template <typename T>
+ desc(prop_kind aprop_kind,
+ const memory::desc &src_desc,
+ T epsilon,
+ unsigned flags) {
+ error::wrap_c_api(
+ mkldnn_batch_normalization_forward_desc_init(
+ &data,
+ mkldnn::convert_to_c(aprop_kind),
+ &src_desc.data,
+ static_cast<float>(epsilon),
+ flags),
+ "could not create a batch normalization forward descriptor");
+ }
+ };
+
+ struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
+ primitive_desc(const desc &adesc, const engine &aengine) {
+ mkldnn_primitive_desc_t result;
+ error::wrap_c_api(mkldnn_primitive_desc_create(
+ &result, &adesc.data, aengine.get(), nullptr),
+ "could not create a batch normalization forward "
+ "primitive descriptor");
+ reset(result);
+ }
+
+ primitive_desc(const desc &adesc,
+ const primitive_attr &aattr,
+ const engine &aengine) {
+ mkldnn_primitive_desc_t result;
+ error::wrap_c_api(
+ mkldnn_primitive_desc_create_v2(
+ &result, &adesc.data, aattr.get(), aengine.get(), nullptr),
+ "could not create a batch normalization forward "
+ "primitive descriptor");
+ reset(result);
+ }
+
+ memory::primitive_desc weights_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t bndesc;
+ const_mkldnn_primitive_desc_t const_bndesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(weights_pd), 0);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&bndesc, const_bndesc),
+ "could not clone a weights primitive descriptor");
+ adesc.reset(bndesc);
+ return adesc;
+ }
+
+ memory::primitive_desc mean_primitive_desc() const {
+ memory::primitive_desc aprimitive_desc;
+ mkldnn_primitive_desc_t bndesc;
+ mkldnn_batch_normalization_desc_t *p;
+ error::wrap_c_api(
+ mkldnn_primitive_desc_query(
+ get(), mkldnn::convert_to_c(batch_normalization_d), 0, &p),
+ "could not get a batch-normalization descriptor");
+ const_mkldnn_primitive_desc_t const_bndesc =
+ (p->flags & use_global_stats)
+ ? mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(src_pd), 1)
+ : mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(dst_pd), 1);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&bndesc, const_bndesc),
+ "could not clone a mean primitive descriptor");
+ aprimitive_desc.reset(bndesc);
+ return aprimitive_desc;
+ }
+
+ memory::primitive_desc variance_primitive_desc() const {
+ memory::primitive_desc aprimitive_desc;
+ mkldnn_primitive_desc_t bndesc;
+ mkldnn_batch_normalization_desc_t *p;
+ error::wrap_c_api(
+ mkldnn_primitive_desc_query(
+ get(), mkldnn::convert_to_c(batch_normalization_d), 0, &p),
+ "could not get a batch-normalization descriptor");
+ const_mkldnn_primitive_desc_t const_bndesc =
+ (p->flags & use_global_stats)
+ ? mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(src_pd), 2)
+ : mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(dst_pd), 2);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&bndesc, const_bndesc),
+ "could not clone a variance primitive descriptor");
+ aprimitive_desc.reset(bndesc);
+ return aprimitive_desc;
+ }
+
+ memory::primitive_desc workspace_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t cdesc;
+ const_mkldnn_primitive_desc_t const_cdesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(workspace_pd), 0);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
+ "could not clone a workspace primitive descriptor");
+ adesc.reset(cdesc);
+ return adesc;
+ }
+
+ memory::primitive_desc dst_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t cdesc;
+ const_mkldnn_primitive_desc_t const_cdesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(dst_pd), 0);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
+ "could not clone a dst primitive descriptor");
+ adesc.reset(cdesc);
+ return adesc;
+ }
+
+ engine get_engine() { return engine::query(*this); }
+ };
+
+ batch_normalization_forward(const primitive_desc &aprimitive_desc,
+ const primitive::at &src,
+ const primitive::at &mean,
+ const primitive::at &variance,
+ const primitive::at &weights,
+ const memory &dst) {
+ mkldnn_primitive_t result;
+ mkldnn_primitive_at_t inputs[] = {
+ src.data, mean.data, variance.data, weights.data};
+ const_mkldnn_primitive_t outputs[] = {dst.get()};
+ error::wrap_c_api(
+ mkldnn_primitive_create(
+ &result, aprimitive_desc.get(), inputs, outputs),
+ "could not create a batch normalization forward primitive");
+ reset(result);
+ }
+
+ batch_normalization_forward(const primitive_desc &aprimitive_desc,
+ const primitive::at &src,
+ const primitive::at &mean,
+ const primitive::at &variance,
+ const memory &dst) {
+ mkldnn_primitive_t result;
+ mkldnn_primitive_at_t inputs[] = {src.data, mean.data, variance.data};
+ const_mkldnn_primitive_t outputs[] = {dst.get()};
+ error::wrap_c_api(
+ mkldnn_primitive_create(
+ &result, aprimitive_desc.get(), inputs, outputs),
+ "could not create a batch normalization forward primitive");
+ reset(result);
+ }
+
+ /// @warning batch_normalization_forward has 2 constructors with very
+ /// similar signatures:
+ /// - (pd, src, weights, dst, mean, variance) // 2 in, 3 out
+ /// - (pd, src, dst, mean, variance, workspace) // 1 in, 4 out
+ /// The only way to distinguish between those is to explicitly
+ /// cast all input parameters to their type, i.e. to
+ /// const primitive:at &.
+ batch_normalization_forward(const primitive_desc &aprimitive_desc,
+ const primitive::at &src,
+ const primitive::at &weights,
+ const memory &dst,
+ const memory &mean,
+ const memory &variance) {
+ mkldnn_primitive_t result;
+ mkldnn_primitive_at_t inputs[] = {src.data, weights.data};
+ const_mkldnn_primitive_t outputs[] = {
+ dst.get(), mean.get(), variance.get()};
+ error::wrap_c_api(
+ mkldnn_primitive_create(
+ &result, aprimitive_desc.get(), inputs, outputs),
+ "could not create a batch normalization forward primitive");
+ reset(result);
+ }
+
+ batch_normalization_forward(const primitive_desc &aprimitive_desc,
+ const primitive::at &src,
+ const primitive::at &weights,
+ const memory &dst,
+ const memory &mean,
+ const memory &variance,
+ const memory &workspace) {
+ mkldnn_primitive_t result;
+ mkldnn_primitive_at_t inputs[] = {src.data, weights.data};
+ const_mkldnn_primitive_t outputs[] = {
+ dst.get(), mean.get(), variance.get(), workspace.get()};
+ error::wrap_c_api(
+ mkldnn_primitive_create(
+ &result, aprimitive_desc.get(), inputs, outputs),
+ "could not create a batch normalization forward primitive");
+ reset(result);
+ }
+
+ batch_normalization_forward(const primitive_desc &aprimitive_desc,
+ const primitive::at &src,
+ const memory &dst,
+ const memory &mean,
+ const memory &variance) {
+ mkldnn_primitive_t result;
+ mkldnn_primitive_at_t inputs[] = {src.data};
+ const_mkldnn_primitive_t outputs[] = {
+ dst.get(), mean.get(), variance.get()};
+ error::wrap_c_api(
+ mkldnn_primitive_create(
+ &result, aprimitive_desc.get(), inputs, outputs),
+ "could not create a batch normalization forward primitive");
+ reset(result);
+ }
+
+ /// @warning batch_normalization_forward has 2 constructors with very
+ /// similar signatures:
+ /// - (pd, src, weights, dst, mean, variance) // 2 in, 3 out
+ /// - (pd, src, dst, mean, variance, workspace) // 1 in, 4 out
+ /// The only way to distinguish between those is to explicitly
+ /// cast all input parameters to their type, i.e. to
+ /// const primitive:at &.
+ /// @note to make users' experience a little bit better this constructor
+ /// checks if whether parameters match corresponding primitive
+ /// descriptor, and if they are not -- call the other (proper)
+ /// constructor. Yeah, this is still very ugly...
+ batch_normalization_forward(const primitive_desc &aprimitive_desc,
+ const primitive::at &src,
+ const memory &dst,
+ const memory &mean,
+ const memory &variance,
+ const memory &workspace) {
+ mkldnn_primitive_t result;
+ mkldnn_primitive_at_t inputs[2] = {src.data};
+ const_mkldnn_primitive_t outputs[4] = {
+ dst.get(), mean.get(), variance.get(), workspace.get()};
+
+ if (1) { // check whether this is the `wrong` constructor
+ const int n_inputs_expected = mkldnn_primitive_desc_query_s32(
+ aprimitive_desc.get(), mkldnn_query_num_of_inputs_s32, 0);
+ const int n_outputs_expected = mkldnn_primitive_desc_query_s32(
+ aprimitive_desc.get(), mkldnn_query_num_of_outputs_s32, 0);
+ if (n_inputs_expected == 2 && n_outputs_expected == 3) {
+ // shift parameters, get rid of workspace, and add weights...
+ auto _weights = dst;
+ inputs[1] = {_weights.get(), 0};
+
+ auto _dst = mean, _mean = variance, _variance = workspace;
+ outputs[0] = _dst.get();
+ outputs[1] = _mean.get();
+ outputs[2] = _variance.get();
+ outputs[3] = nullptr;
+ }
+ }
+ error::wrap_c_api(
+ mkldnn_primitive_create(
+ &result, aprimitive_desc.get(), inputs, outputs),
+ "could not create a batch normalization forward primitive");
+ reset(result);
+ }
+
+ batch_normalization_forward(const primitive_desc &aprimitive_desc,
+ const primitive::at &src,
+ const primitive::at &weights,
+ const memory &dst) {
+ mkldnn_primitive_t result;
+ mkldnn_primitive_at_t inputs[] = {src.data, weights.data};
+ const_mkldnn_primitive_t outputs[] = {dst.get()};
+ error::wrap_c_api(
+ mkldnn_primitive_create(
+ &result, aprimitive_desc.get(), inputs, outputs),
+ "could not create a batch normalization forward primitive");
+ reset(result);
+ }
+
+ batch_normalization_forward(const primitive_desc &aprimitive_desc,
+ const primitive::at &src,
+ const memory &dst) {
+ mkldnn_primitive_t result;
+ mkldnn_primitive_at_t inputs[] = {src.data};
+ const_mkldnn_primitive_t outputs[] = {dst.get()};
+ error::wrap_c_api(
+ mkldnn_primitive_create(
+ &result, aprimitive_desc.get(), inputs, outputs),
+ "could not create a batch normalization forward primitive");
+ reset(result);
+ }
+};
+
+struct batch_normalization_backward : public primitive {
+ struct desc {
+ mkldnn_batch_normalization_desc_t data;
+ template <typename T>
+ desc(prop_kind aprop_kind,
+ const memory::desc &diff_data_desc,
+ const memory::desc &data_desc,
+ T epsilon,
+ unsigned flags) {
+ error::wrap_c_api(
+ mkldnn_batch_normalization_backward_desc_init(
+ &data,
+ mkldnn::convert_to_c(aprop_kind),
+ &diff_data_desc.data,
+ &data_desc.data,
+ static_cast<float>(epsilon),
+ flags),
+ "could not create a batch normalization backward descriptor");
+ }
+ };
+
+ struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
+ primitive_desc(const desc &adesc,
+ const engine &aengine,
+ const batch_normalization_forward::primitive_desc
+ &hint_fwd_primitive_desc) {
+ mkldnn_primitive_desc_t result;
+ error::wrap_c_api(
+ mkldnn_primitive_desc_create(&result,
+ &adesc.data,
+ aengine.get(),
+ hint_fwd_primitive_desc.get()),
+ "could not create a batch normalization backward primitive "
+ "descriptor");
+ reset(result);
+ }
+
+ memory::primitive_desc weights_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t bndesc;
+ const_mkldnn_primitive_desc_t const_bndesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(weights_pd), 0);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&bndesc, const_bndesc),
+ "could not clone a weights primitive descriptor");
+ adesc.reset(bndesc);
+ return adesc;
+ }
+
+ memory::primitive_desc diff_weights_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t bndesc;
+ const_mkldnn_primitive_desc_t const_bndesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(diff_weights_pd), 0);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&bndesc, const_bndesc),
+ "could not clone a diff_weights primitive descriptor");
+ adesc.reset(bndesc);
+ return adesc;
+ }
+
+ memory::primitive_desc mean_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t bndesc;
+ const_mkldnn_primitive_desc_t const_bndesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(src_pd), 1);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&bndesc, const_bndesc),
+ "could not clone a mean primitive descriptor");
+ adesc.reset(bndesc);
+ return adesc;
+ }
+
+ memory::primitive_desc variance_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t bndesc;
+ const_mkldnn_primitive_desc_t const_bndesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(src_pd), 2);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&bndesc, const_bndesc),
+ "could not clone a variance primitive descriptor");
+ adesc.reset(bndesc);
+ return adesc;
+ }
+
+ memory::primitive_desc workspace_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t cdesc;
+ const_mkldnn_primitive_desc_t const_cdesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(workspace_pd), 0);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
+ "could not clone a workspace primitive descriptor");
+ adesc.reset(cdesc);
+ return adesc;
+ }
+
+ memory::primitive_desc dst_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t cdesc;
+ const_mkldnn_primitive_desc_t const_cdesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(dst_pd), 0);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
+ "could not clone a dst primitive descriptor");
+ adesc.reset(cdesc);
+ return adesc;
+ }
+
+ engine get_engine() { return engine::query(*this); }
+ };
+
+ // Prop_kind == backward
+ batch_normalization_backward(const primitive_desc &aprimitive_desc,
+ const primitive::at &src,
+ const primitive::at &mean,
+ const primitive::at &variance,
+ const primitive::at &diff_dst,
+ const primitive::at &weights,
+ const memory &diff_src,
+ const memory &diff_weights) {
+ mkldnn_primitive_t result;
+ mkldnn_primitive_at_t inputs[] = {
+ src.data, mean.data, variance.data, diff_dst.data, weights.data};
+ const_mkldnn_primitive_t outputs[] = {diff_src.get(), diff_weights.get()};
+ error::wrap_c_api(
+ mkldnn_primitive_create(
+ &result, aprimitive_desc.get(), inputs, outputs),
+ "could not create a batch normalization backward primitive");
+ reset(result);
+ }
+
+ // Prop_kind == backward (+ws)
+ batch_normalization_backward(const primitive_desc &aprimitive_desc,
+ const primitive::at &src,
+ const primitive::at &mean,
+ const primitive::at &variance,
+ const primitive::at &diff_dst,
+ const primitive::at &weights,
+ const primitive::at &workspace,
+ const memory &diff_src,
+ const memory &diff_weights) {
+ mkldnn_primitive_t result;
+ mkldnn_primitive_at_t inputs[] = {src.data,
+ mean.data,
+ variance.data,
+ diff_dst.data,
+ weights.data,
+ workspace.data};
+ const_mkldnn_primitive_t outputs[] = {diff_src.get(), diff_weights.get()};
+ error::wrap_c_api(
+ mkldnn_primitive_create(
+ &result, aprimitive_desc.get(), inputs, outputs),
+ "could not create a batch normalization backward primitive");
+ reset(result);
+ }
+
+ // Prop_kind == backward_data (+ws or +weights)
+ /// @warning This constructor works for backward_data propagation
+ /// - w/ weights but w/o workspace, or
+ /// - w/ workspace but w/o weights
+ batch_normalization_backward(const primitive_desc &aprimitive_desc,
+ const primitive::at &src,
+ const primitive::at &mean,
+ const primitive::at &variance,
+ const primitive::at &diff_dst,
+ const primitive::at &weights_or_workspace,
+ const memory &diff_src) {
+ mkldnn_primitive_t result;
+ mkldnn_primitive_at_t inputs[] = {src.data,
+ mean.data,
+ variance.data,
+ diff_dst.data,
+ weights_or_workspace.data};
+ const_mkldnn_primitive_t outputs[] = {diff_src.get()};
+ error::wrap_c_api(
+ mkldnn_primitive_create(
+ &result, aprimitive_desc.get(), inputs, outputs),
+ "could not create a batch normalization backward primitive");
+ reset(result);
+ }
+
+ // Prop_kind == backward_data
+ batch_normalization_backward(const primitive_desc &aprimitive_desc,
+ const primitive::at &src,
+ const primitive::at &mean,
+ const primitive::at &variance,
+ const primitive::at &diff_dst,
+ const memory &diff_src) {
+ mkldnn_primitive_t result;
+ mkldnn_primitive_at_t inputs[] = {
+ src.data, mean.data, variance.data, diff_dst.data};
+ const_mkldnn_primitive_t outputs[] = {diff_src.get()};
+ error::wrap_c_api(
+ mkldnn_primitive_create(
+ &result, aprimitive_desc.get(), inputs, outputs),
+ "could not create a batch normalization backward primitive");
+ reset(result);
+ }
+};
+
+/// @}
+
+/// @addtogroup cpp_api_inner_product Inner Product
+/// @{
+
+struct inner_product_forward : public primitive {
+ struct desc {
+ mkldnn_inner_product_desc_t data;
+ desc(prop_kind aprop_kind,
+ const memory::desc &src_desc,
+ const memory::desc &weights_desc,
+ const memory::desc &bias_desc,
+ const memory::desc &dst_desc) {
+ error::wrap_c_api(mkldnn_inner_product_forward_desc_init(
+ &data,
+ mkldnn::convert_to_c(aprop_kind),
+ &src_desc.data,
+ &weights_desc.data,
+ &bias_desc.data,
+ &dst_desc.data),
+ "could not create a inner product forward descriptor");
+ }
+
+ desc(prop_kind aprop_kind,
+ const memory::desc &src_desc,
+ const memory::desc &weights_desc,
+ const memory::desc &dst_desc) {
+ error::wrap_c_api(mkldnn_inner_product_forward_desc_init(
+ &data,
+ mkldnn::convert_to_c(aprop_kind),
+ &src_desc.data,
+ &weights_desc.data,
+ nullptr,
+ &dst_desc.data),
+ "could not create a inner product forward descriptor");
+ }
+ };
+
+ struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
+ primitive_desc(const desc &adesc, const engine &aengine) {
+ mkldnn_primitive_desc_t result;
+ error::wrap_c_api(
+ mkldnn_primitive_desc_create(
+ &result, &adesc.data, aengine.get(), nullptr),
+ "could not create a inner product forward primitive descriptor");
+ reset(result);
+ }
+
+ primitive_desc(const desc &adesc,
+ const primitive_attr &aattr,
+ const engine &aengine) {
+ mkldnn_primitive_desc_t result;
+ error::wrap_c_api(
+ mkldnn_primitive_desc_create_v2(
+ &result, &adesc.data, aattr.get(), aengine.get(), nullptr),
+ "could not create a inner product "
+ "forward primitive descriptor");
+ reset(result);
+ }
+
+ memory::primitive_desc src_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t cdesc;
+ const_mkldnn_primitive_desc_t const_cdesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(src_pd), 0);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
+ "could not clone a src primitive descriptor");
+ adesc.reset(cdesc);
+ return adesc;
+ }
+
+ memory::primitive_desc weights_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t cdesc;
+ const_mkldnn_primitive_desc_t const_cdesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(weights_pd), 0);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
+ "could not clone a weights primitive descriptor");
+ adesc.reset(cdesc);
+ return adesc;
+ }
+
+ memory::primitive_desc bias_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t cdesc;
+ const_mkldnn_primitive_desc_t const_cdesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(weights_pd), 1);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
+ "could not clone a bias primitive descriptor");
+ adesc.reset(cdesc);
+ return adesc;
+ }
+
+ memory::primitive_desc dst_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t cdesc;
+ const_mkldnn_primitive_desc_t const_cdesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(dst_pd), 0);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
+ "could not clone a dst primitive descriptor");
+ adesc.reset(cdesc);
+ return adesc;
+ }
+
+ engine get_engine() { return engine::query(*this); }
+ };
+
+ inner_product_forward(const primitive_desc &aprimitive_desc,
+ const primitive::at &src,
+ const primitive::at weights,
+ const primitive::at &bias,
+ const memory &dst) {
+ mkldnn_primitive_t result;
+ mkldnn_primitive_at_t inputs[] = {src.data, weights.data, bias.data};
+ const_mkldnn_primitive_t outputs[] = {dst.get()};
+ error::wrap_c_api(mkldnn_primitive_create(
+ &result, aprimitive_desc.get(), inputs, outputs),
+ "could not create a inner product forward primitive");
+ reset(result);
+ }
+
+ inner_product_forward(const primitive_desc &aprimitive_desc,
+ const primitive::at &src,
+ const primitive::at weights,
+ const memory &dst) {
+ mkldnn_primitive_t result;
+ mkldnn_primitive_at_t inputs[] = {src.data, weights.data};
+ const_mkldnn_primitive_t outputs[] = {dst.get()};
+ error::wrap_c_api(mkldnn_primitive_create(
+ &result, aprimitive_desc.get(), inputs, outputs),
+ "could not create a inner product forward primitive");
+ reset(result);
+ }
+};
+
+struct inner_product_backward_data : public primitive {
+ struct desc {
+ mkldnn_inner_product_desc_t data;
+ desc(const memory::desc &diff_src_desc,
+ const memory::desc &weights_desc,
+ const memory::desc &diff_dst_desc) {
+ error::wrap_c_api(
+ mkldnn_inner_product_backward_data_desc_init(&data,
+ &diff_src_desc.data,
+ &weights_desc.data,
+ &diff_dst_desc.data),
+ "could not create a inner product backward data descriptor");
+ }
+ };
+
+ struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
+ primitive_desc(
+ const desc &adesc,
+ const engine &aengine,
+ const inner_product_forward::primitive_desc &hint_fwd_primitive_desc) {
+ mkldnn_primitive_desc_t result;
+ error::wrap_c_api(
+ mkldnn_primitive_desc_create(&result,
+ &adesc.data,
+ aengine.get(),
+ hint_fwd_primitive_desc.get()),
+ "could not create a inner product backward data primitive "
+ "descriptor");
+ reset(result);
+ }
+
+ memory::primitive_desc diff_dst_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t cdesc;
+ const_mkldnn_primitive_desc_t const_cdesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(diff_dst_pd), 0);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
+ "could not clone a diff dst primititve descriptor");
+ adesc.reset(cdesc);
+ return adesc;
+ }
+
+ memory::primitive_desc weights_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t cdesc;
+ const_mkldnn_primitive_desc_t const_cdesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(weights_pd), 0);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
+ "could not clone a weights primitive descriptor");
+ adesc.reset(cdesc);
+ return adesc;
+ }
+
+ memory::primitive_desc diff_src_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t cdesc;
+ const_mkldnn_primitive_desc_t const_cdesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(diff_src_pd), 0);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
+ "could not clone a diff src primitive descriptor");
+ adesc.reset(cdesc);
+ return adesc;
+ }
+
+ engine get_engine() { return engine::query(*this); }
+ };
+
+ inner_product_backward_data(const primitive_desc &aprimitive_desc,
+ const primitive::at &diff_dst,
+ const primitive::at weights,
+ const memory &diff_src) {
+ mkldnn_primitive_t result;
+ mkldnn_primitive_at_t inputs[] = {diff_dst.data, weights.data};
+ const_mkldnn_primitive_t outputs[] = {diff_src.get()};
+ error::wrap_c_api(
+ mkldnn_primitive_create(
+ &result, aprimitive_desc.get(), inputs, outputs),
+ "could not create a inner product backward data primitive");
+ reset(result);
+ }
+};
+
+struct inner_product_backward_weights : public primitive {
+ struct desc {
+ mkldnn_inner_product_desc_t data;
+ desc(const memory::desc &src_desc,
+ const memory::desc &diff_weights_desc,
+ const memory::desc &diff_bias_desc,
+ const memory::desc &diff_dst_desc) {
+ error::wrap_c_api(
+ mkldnn_inner_product_backward_weights_desc_init(
+ &data,
+ &src_desc.data,
+ &diff_weights_desc.data,
+ &diff_bias_desc.data,
+ &diff_dst_desc.data),
+ "could not create a inner product backward weights descriptor");
+ }
+ desc(const memory::desc &src_desc,
+ const memory::desc &diff_weights_desc,
+ const memory::desc &diff_dst_desc) {
+ error::wrap_c_api(
+ mkldnn_inner_product_backward_weights_desc_init(
+ &data,
+ &src_desc.data,
+ &diff_weights_desc.data,
+ nullptr,
+ &diff_dst_desc.data),
+ "could not create a inner product backward weights descriptor");
+ }
+ };
+
+ struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
+ primitive_desc(
+ const desc &adesc,
+ const engine &aengine,
+ const inner_product_forward::primitive_desc &hint_fwd_primitive_desc) {
+ mkldnn_primitive_desc_t result;
+ error::wrap_c_api(
+ mkldnn_primitive_desc_create(&result,
+ &adesc.data,
+ aengine.get(),
+ hint_fwd_primitive_desc.get()),
+ "could not create a inner product backward weights primitive "
+ "descriptor");
+ reset(result);
+ }
+
+ memory::primitive_desc diff_dst_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t cdesc;
+ const_mkldnn_primitive_desc_t const_cdesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(diff_dst_pd), 0);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
+ "could not clone a diff dst primititve descriptor");
+ adesc.reset(cdesc);
+ return adesc;
+ }
+
+ memory::primitive_desc diff_weights_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t cdesc;
+ const_mkldnn_primitive_desc_t const_cdesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(diff_weights_pd), 0);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
+ "could not clone a diff weights primitive descriptor");
+ adesc.reset(cdesc);
+ return adesc;
+ }
+
+ memory::primitive_desc diff_bias_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t cdesc;
+ const_mkldnn_primitive_desc_t const_cdesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(diff_weights_pd), 1);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
+ "could not clone a diff bias primitive descriptor");
+ adesc.reset(cdesc);
+ return adesc;
+ }
+
+ memory::primitive_desc src_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t cdesc;
+ const_mkldnn_primitive_desc_t const_cdesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(src_pd), 0);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
+ "could not clone a src primitive descriptor");
+ adesc.reset(cdesc);
+ return adesc;
+ }
+
+ engine get_engine() { return engine::query(*this); }
+ };
+
+ inner_product_backward_weights(const primitive_desc &aprimitive_desc,
+ const primitive::at &src,
+ const primitive::at diff_dst,
+ const memory &diff_weights) {
+ mkldnn_primitive_t result;
+ mkldnn_primitive_at_t inputs[] = {src.data, diff_dst.data};
+ const_mkldnn_primitive_t outputs[] = {diff_weights.get()};
+ error::wrap_c_api(
+ mkldnn_primitive_create(
+ &result, aprimitive_desc.get(), inputs, outputs),
+ "could not create a inner product backward weights primitive");
+ reset(result);
+ }
+
+ inner_product_backward_weights(const primitive_desc &aprimitive_desc,
+ const primitive::at &src,
+ const primitive::at diff_dst,
+ const memory &diff_weights,
+ const memory &diff_bias) {
+ mkldnn_primitive_t result;
+ mkldnn_primitive_at_t inputs[] = {src.data, diff_dst.data};
+ const_mkldnn_primitive_t outputs[] = {diff_weights.get(), diff_bias.get()};
+ error::wrap_c_api(
+ mkldnn_primitive_create(
+ &result, aprimitive_desc.get(), inputs, outputs),
+ "could not create a inner product backward weights primitive");
+ reset(result);
+ }
+};
+
+/// @}
+
+/// @addtogroup cpp_api_rnn RNN
+/// @{
+
+struct rnn_cell {
+ struct desc {
+ mkldnn_rnn_cell_desc_t c_rnn_cell_;
+
+ desc(algorithm kind, algorithm activation_f) {
+ error::wrap_c_api(
+ mkldnn_rnn_cell_desc_init(&c_rnn_cell_,
+ mkldnn::convert_to_c(kind),
+ mkldnn::convert_to_c(activation_f),
+ 0U,
+ 0,
+ 0),
+ "could not init an rnn cell descriptor");
+ }
+ desc(algorithm kind) : desc(kind, algorithm::algorithm_undef) {}
+
+ operator const mkldnn_rnn_cell_desc_t *() const { return &c_rnn_cell_; }
+
+ algorithm get_cell_kind() const { return algorithm(c_rnn_cell_.cell_kind); }
+ algorithm get_activation() const {
+ return algorithm(c_rnn_cell_.activation_kind);
+ }
+
+ float get_alpha() const { return c_rnn_cell_.alpha; }
+ void set_alpha(float alpha) {
+ c_rnn_cell_.flags |= mkldnn_rnn_cell_with_relu;
+ c_rnn_cell_.alpha = alpha;
+ }
+
+ float get_clipping() const { return c_rnn_cell_.clipping; }
+ void set_clipping(float clipping) {
+ c_rnn_cell_.flags |= mkldnn_rnn_cell_with_clipping;
+ c_rnn_cell_.clipping = clipping;
+ }
+
+ int get_gates_count() const {
+ return mkldnn_rnn_cell_get_gates_count(&c_rnn_cell_);
+ }
+ int get_state_count() const {
+ return mkldnn_rnn_cell_get_states_count(&c_rnn_cell_);
+ }
+ };
+};
+
+struct rnn_forward : public primitive {
+ struct desc {
+ mkldnn_rnn_desc_t data;
+ desc(prop_kind aprop_kind,
+ rnn_cell::desc cell,
+ const rnn_direction direction,
+ const memory::desc &src_layer_desc,
+ const memory::desc &src_iter_desc,
+ const memory::desc &weights_layer_desc,
+ const memory::desc &weights_iter_desc,
+ const memory::desc &bias_desc,
+ const memory::desc &dst_layer_desc,
+ const memory::desc &dst_iter_desc) {
+ error::wrap_c_api(
+ mkldnn_rnn_forward_desc_init(&data,
+ mkldnn::convert_to_c(aprop_kind),
+ cell,
+ mkldnn::convert_to_c(direction),
+ &src_layer_desc.data,
+ &src_iter_desc.data,
+ &weights_layer_desc.data,
+ &weights_iter_desc.data,
+ &bias_desc.data,
+ &dst_layer_desc.data,
+ &dst_iter_desc.data),
+ "could not create an RNN forward descriptor");
+ }
+ };
+ struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
+ primitive_desc(const desc &adesc, const engine &aengine) {
+ mkldnn_primitive_desc_t result;
+ error::wrap_c_api(mkldnn_primitive_desc_create(
+ &result, &adesc.data, aengine.get(), nullptr),
+ "could not create an RNN forward primitive descriptor");
+ reset(result);
+ }
+
+ memory::primitive_desc src_layer_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t cdesc;
+ const_mkldnn_primitive_desc_t const_cdesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(src_pd), 0);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
+ "could not clone an src layer primitive descriptor");
+ adesc.reset(cdesc);
+ return adesc;
+ }
+
+ memory::primitive_desc src_iter_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t cdesc;
+ const_mkldnn_primitive_desc_t const_cdesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(src_pd), 1);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
+ "could not clone a src iter primitive descriptor");
+ adesc.reset(cdesc);
+ return adesc;
+ }
+
+ memory::primitive_desc weights_layer_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t cdesc;
+ const_mkldnn_primitive_desc_t const_cdesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(weights_pd), 0);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
+ "could not clone a weights primitive descriptor");
+ adesc.reset(cdesc);
+ return adesc;
+ }
+
+ memory::primitive_desc weights_src_iter_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t cdesc;
+ const_mkldnn_primitive_desc_t const_cdesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(weights_pd), 1);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
+ "could not clone a weights primitive descriptor");
+ adesc.reset(cdesc);
+ return adesc;
+ }
+
+ memory::primitive_desc bias_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t cdesc;
+ const_mkldnn_primitive_desc_t const_cdesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(weights_pd), 2);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
+ "could not clone a bias primitive descriptor");
+ adesc.reset(cdesc);
+ return adesc;
+ }
+
+ memory::primitive_desc workspace_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t ldesc;
+ const_mkldnn_primitive_desc_t const_ldesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(workspace_pd), 0);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&ldesc, const_ldesc),
+ "could not clone a workspace primitive descriptor");
+ adesc.reset(ldesc);
+ return adesc;
+ }
+
+ memory::primitive_desc dst_layer_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t cdesc;
+ const_mkldnn_primitive_desc_t const_cdesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(dst_pd), 0);
+ error::wrap_c_api(
+ mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
+ "could not clone a dst last layer primitive descriptor");
+ adesc.reset(cdesc);
+ return adesc;
+ }
+
+ memory::primitive_desc dst_iter_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t cdesc;
+ const_mkldnn_primitive_desc_t const_cdesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(dst_pd), 1);
+ error::wrap_c_api(
+ mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
+ "could not clone a dst last iteration primitive descriptor");
+ adesc.reset(cdesc);
+ return adesc;
+ }
+
+ engine get_engine() { return engine::query(*this); }
+ };
+
+ rnn_forward(const primitive_desc &aprimitive_desc,
+ const primitive::at &src_layer,
+ const primitive::at &src_iter,
+ const primitive::at &weights_layer,
+ const primitive::at &weights_iter,
+ const primitive::at &bias,
+ const memory &dst_layer,
+ const memory &dst_iter,
+ const memory &workspace) {
+ mkldnn_primitive_t result;
+ mkldnn_primitive_at_t inputs[5];
+ const_mkldnn_primitive_t outputs[3];
+ int idx = 0;
+ inputs[idx++] = src_layer.data;
+ if (!is_null_memory(src_iter.data.primitive)) inputs[idx++] = src_iter.data;
+ inputs[idx++] = weights_layer.data;
+ inputs[idx++] = weights_iter.data;
+ if (!is_null_memory(bias.data.primitive)) inputs[idx++] = bias.data;
+
+ idx = 0;
+ outputs[idx++] = dst_layer.get();
+ if (!is_null_memory(dst_iter.get())) outputs[idx++] = dst_iter.get();
+ if (!is_null_memory(workspace.get())) outputs[idx++] = workspace.get();
+
+ error::wrap_c_api(mkldnn_primitive_create(
+ &result, aprimitive_desc.get(), inputs, outputs),
+ "could not create an RNN forward primitive");
+ reset(result);
+ }
+};
+
+struct rnn_backward : public primitive {
+ struct desc {
+ mkldnn_rnn_desc_t data;
+ desc(prop_kind aprop_kind,
+ rnn_cell::desc cell,
+ const rnn_direction direction,
+ const memory::desc &src_layer_desc,
+ const memory::desc &src_iter_desc,
+ const memory::desc &weights_layer_desc,
+ const memory::desc &weights_iter_desc,
+ const memory::desc &bias_desc,
+ const memory::desc &dst_layer_desc,
+ const memory::desc &dst_iter_desc,
+ const memory::desc &diff_src_layer_desc,
+ const memory::desc &diff_src_iter_desc,
+ const memory::desc &diff_weights_layer_desc,
+ const memory::desc &diff_weights_iter_desc,
+ const memory::desc &diff_bias_desc,
+ const memory::desc &diff_dst_layer_desc,
+ const memory::desc &diff_dst_iter_desc) {
+ error::wrap_c_api(
+ mkldnn_rnn_backward_desc_init(&data,
+ mkldnn::convert_to_c(aprop_kind),
+ cell,
+ mkldnn::convert_to_c(direction),
+ &src_layer_desc.data,
+ &src_iter_desc.data,
+ &weights_layer_desc.data,
+ &weights_iter_desc.data,
+ &bias_desc.data,
+ &dst_layer_desc.data,
+ &dst_iter_desc.data,
+ &diff_src_layer_desc.data,
+ &diff_src_iter_desc.data,
+ &diff_weights_layer_desc.data,
+ &diff_weights_iter_desc.data,
+ &diff_bias_desc.data,
+ &diff_dst_layer_desc.data,
+ &diff_dst_iter_desc.data),
+ "could not create an RNN backward descriptor");
+ }
+ };
+ struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
+ primitive_desc(const desc &adesc, const engine &aengine) {
+ mkldnn_primitive_desc_t result;
+ error::wrap_c_api(
+ mkldnn_primitive_desc_create(
+ &result, &adesc.data, aengine.get(), nullptr),
+ "could not create an RNN backward primitive descriptor");
+ reset(result);
+ }
+
+ memory::primitive_desc src_layer_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t cdesc;
+ const_mkldnn_primitive_desc_t const_cdesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(src_pd), 0);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
+ "could not clone an src layer primitive descriptor");
+ adesc.reset(cdesc);
+ return adesc;
+ }
+
+ memory::primitive_desc src_iter_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t cdesc;
+ const_mkldnn_primitive_desc_t const_cdesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(src_pd), 1);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
+ "could not clone a src iter primitive descriptor");
+ adesc.reset(cdesc);
+ return adesc;
+ }
+
+ memory::primitive_desc weights_layer_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t cdesc;
+ const_mkldnn_primitive_desc_t const_cdesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(weights_pd), 0);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
+ "could not clone a weights primitive descriptor");
+ adesc.reset(cdesc);
+ return adesc;
+ }
+
+ memory::primitive_desc weights_iter_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t cdesc;
+ const_mkldnn_primitive_desc_t const_cdesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(weights_pd), 1);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
+ "could not clone a weights primitive descriptor");
+ adesc.reset(cdesc);
+ return adesc;
+ }
+
+ memory::primitive_desc bias_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t cdesc;
+ const_mkldnn_primitive_desc_t const_cdesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(weights_pd), 2);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
+ "could not clone a bias primitive descriptor");
+ adesc.reset(cdesc);
+ return adesc;
+ }
+
+ memory::primitive_desc dst_layer_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t cdesc;
+ const_mkldnn_primitive_desc_t const_cdesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(dst_pd), 0);
+ error::wrap_c_api(
+ mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
+ "could not clone a dst last layer primitive descriptor");
+ adesc.reset(cdesc);
+ return adesc;
+ }
+
+ memory::primitive_desc dst_iter_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t cdesc;
+ const_mkldnn_primitive_desc_t const_cdesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(dst_pd), 1);
+ error::wrap_c_api(
+ mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
+ "could not clone a dst last iteration primitive descriptor");
+ adesc.reset(cdesc);
+ return adesc;
+ }
+
+ memory::primitive_desc diff_src_layer_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t cdesc;
+ const_mkldnn_primitive_desc_t const_cdesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(diff_src_pd), 0);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
+ "could not clone an src_layer primitive descriptor");
+ adesc.reset(cdesc);
+ return adesc;
+ }
+
+ memory::primitive_desc diff_src_iter_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t cdesc;
+ const_mkldnn_primitive_desc_t const_cdesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(diff_src_pd), 1);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
+ "could not clone a src iter primitive descriptor");
+ adesc.reset(cdesc);
+ return adesc;
+ }
+
+ memory::primitive_desc diff_weights_layer_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t cdesc;
+ const_mkldnn_primitive_desc_t const_cdesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(diff_weights_pd), 0);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
+ "could not clone a weights primitive descriptor");
+ adesc.reset(cdesc);
+ return adesc;
+ }
+
+ memory::primitive_desc diff_weights_iter_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t cdesc;
+ const_mkldnn_primitive_desc_t const_cdesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(diff_weights_pd), 1);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
+ "could not clone a weights primitive descriptor");
+ adesc.reset(cdesc);
+ return adesc;
+ }
+
+ memory::primitive_desc diff_bias_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t cdesc;
+ const_mkldnn_primitive_desc_t const_cdesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(diff_weights_pd), 2);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
+ "could not clone a bias primitive descriptor");
+ adesc.reset(cdesc);
+ return adesc;
+ }
+
+ memory::primitive_desc diff_dst_layer_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t cdesc;
+ const_mkldnn_primitive_desc_t const_cdesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(diff_dst_pd), 0);
+ error::wrap_c_api(
+ mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
+ "could not clone a dst last layer primitive descriptor");
+ adesc.reset(cdesc);
+ return adesc;
+ }
+
+ memory::primitive_desc diff_dst_iter_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t cdesc;
+ const_mkldnn_primitive_desc_t const_cdesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(diff_dst_pd), 1);
+ error::wrap_c_api(
+ mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
+ "could not clone a dst last iteration primitive descriptor");
+ adesc.reset(cdesc);
+ return adesc;
+ }
+
+ memory::primitive_desc workspace_primitive_desc() const {
+ memory::primitive_desc adesc;
+ mkldnn_primitive_desc_t ldesc;
+ const_mkldnn_primitive_desc_t const_ldesc =
+ mkldnn_primitive_desc_query_pd(
+ get(), mkldnn::convert_to_c(workspace_pd), 0);
+ error::wrap_c_api(mkldnn_primitive_desc_clone(&ldesc, const_ldesc),
+ "could not clone a workspace primitive descriptor");
+ adesc.reset(ldesc);
+ return adesc;
+ }
+
+ engine get_engine() { return engine::query(*this); }
+ };
+ // With last iteration (with and without input src_iter)
+ rnn_backward(const primitive_desc &aprimitive_desc,
+ const primitive::at &src_layer,
+ const primitive::at &src_iter,
+ const primitive::at &weights_layer,
+ const primitive::at &weights_iter,
+ const primitive::at &bias,
+ const primitive::at &dst_layer,
+ const primitive::at &dst_iter,
+ const memory &diff_src_layer,
+ const memory &diff_src_iter,
+ const memory &diff_weights_layer,
+ const memory &diff_weights_iter,
+ const memory &diff_bias,
+ const primitive::at &diff_dst_layer,
+ const primitive::at &diff_dst_iter,
+ const primitive::at &workspace) {
+ mkldnn_primitive_t result;
+ mkldnn_primitive_at_t inputs[10];
+ const_mkldnn_primitive_t outputs[5];
+ int idx = 0;
+ inputs[idx] = src_layer.data;
+ if (!is_null_memory(src_iter.data.primitive)) inputs[idx++] = src_iter.data;
+ inputs[idx++] = weights_layer.data;
+ inputs[idx++] = weights_iter.data;
+ if (!is_null_memory(bias.data.primitive)) inputs[idx++] = bias.data;
+ inputs[idx] = dst_layer.data;
+ if (!is_null_memory(dst_iter.data.primitive)) inputs[idx++] = dst_iter.data;
+ inputs[idx] = diff_dst_layer.data;
+ if (!is_null_memory(diff_dst_iter.data.primitive))
+ inputs[idx++] = diff_dst_iter.data;
+ inputs[idx] = workspace.data;
+
+ idx = 0;
+ outputs[idx] = diff_src_layer.get();
+ if (!is_null_memory(diff_src_iter.get()))
+ outputs[idx++] = diff_src_iter.get();
+ outputs[idx] = diff_weights_layer.get();
+ outputs[idx] = diff_weights_iter.get();
+ if (!is_null_memory(diff_bias.get())) outputs[idx] = diff_bias.get();
+ error::wrap_c_api(mkldnn_primitive_create(
+ &result, aprimitive_desc.get(), inputs, outputs),
+ "could not create an RNN backward primitive");
+ reset(result);
+ }
+};
+
+/// @}
+/// @} Primitives
+
+/// @addtogroup cpp_api_stream Stream
+/// @{
+
+#ifndef DOXYGEN_SHOULD_SKIP_THIS
+template <>
+struct handle_traits<mkldnn_stream_t> {
+ static constexpr auto destructor = &mkldnn_stream_destroy;
+};
+#endif
+
+struct stream : public handle<mkldnn_stream_t> {
+ using handle::handle;
+
+ enum kind {
+ any = mkldnn_stream_kind_t::mkldnn_any_stream,
+ eager = mkldnn_stream_kind_t::mkldnn_eager,
+ lazy = mkldnn_stream_kind_t::mkldnn_lazy
+ };
+
+ static mkldnn_stream_kind_t convert_to_c(kind akind) {
+ return static_cast<mkldnn_stream_kind_t>(akind);
+ }
+ /// Constructs a stream.
+ stream(kind akind) {
+ mkldnn_stream_t astream;
+ error::wrap_c_api(mkldnn_stream_create(&astream, convert_to_c(akind)),
+ "could not create a stream");
+ reset(astream);
+ }
+
+ /// Submits a vector of primitives to a stream for computations.
+ ///
+ /// @param primitives The vector of primitives to submit.
+ /// @returns The stream.
+ stream &submit(std::vector<primitive> primitives) {
+ // TODO: find a proper way to convert vector<primitive> to
+ // vector<mkldnn_primitive_t>
+ if (primitives.size() == 0) return *this;
+ std::vector<mkldnn_primitive_t> c_api_primitives;
+ c_api_primitives.reserve(primitives.size());
+ auto convert_to_c = [](primitive p) { return p.get(); };
+ std::transform(primitives.begin(),
+ primitives.end(),
+ std::back_inserter(c_api_primitives),
+ convert_to_c);
+
+ mkldnn_primitive_t c_api_error_primitive;
+ error::wrap_c_api(mkldnn_stream_submit(get(),
+ c_api_primitives.size(),
+ &c_api_primitives[0],
+ &c_api_error_primitive),
+ "could not submit primitives to a stream",
+ &c_api_error_primitive);
+
+ return *this;
+ }
+
+ /// Waits for all computations submitted to the stream to complete.
+ ///
+ /// @param block Specifies whether the operation should wait indefinitely or
+ /// return
+ /// immediately.
+ /// @returns @c true if all computations completed.
+ /// @returns @c false if not all computations completed.
+ bool wait(bool block = true) {
+ mkldnn_primitive_t c_api_error_primitive;
+ mkldnn_status_t status =
+ mkldnn_stream_wait(get(), block, &c_api_error_primitive);
+ if (status != mkldnn_success && status != mkldnn_try_again)
+ error::wrap_c_api(
+ status, "could not wait on a stream", &c_api_error_primitive);
+ return (status == mkldnn_success);
+ }
+
+ stream &rerun() {
+ mkldnn_primitive_t c_api_error_primitive;
+ error::wrap_c_api(mkldnn_stream_rerun(get(), &c_api_error_primitive),
+ "could not rerun a stream",
+ &c_api_error_primitive);
+ return *this;
+ }
+};
+
+/// @}
+
+/// @} C++ API
+
+} // namespace mkldnn
+
+#endif
From 08295f9877606cdae2df0a0983514eac67a45dca Mon Sep 17 00:00:00 2001
From: yuyang18 <reyoung@126.com>
Date: Mon, 14 May 2018 16:40:13 +0800
Subject: [PATCH 093/195] Add build strategy
---
.../fluid/framework/details/build_strategy.h | 36 +++++++++++
.../details/multi_devices_graph_builder.cc | 47 ++++++++-------
.../details/multi_devices_graph_builder.h | 12 ++--
paddle/fluid/framework/parallel_executor.cc | 12 ++--
paddle/fluid/framework/parallel_executor.h | 7 ++-
paddle/fluid/platform/nccl_helper.h | 2 +-
paddle/fluid/pybind/pybind.cc | 31 +++++++++-
python/paddle/fluid/__init__.py | 8 +--
python/paddle/fluid/parallel_executor.py | 25 +++++---
.../tests/unittests/test_parallel_executor.py | 59 +++++++++++--------
10 files changed, 162 insertions(+), 77 deletions(-)
create mode 100644 paddle/fluid/framework/details/build_strategy.h
diff --git a/paddle/fluid/framework/details/build_strategy.h b/paddle/fluid/framework/details/build_strategy.h
new file mode 100644
index 0000000000..d6f9c547d8
--- /dev/null
+++ b/paddle/fluid/framework/details/build_strategy.h
@@ -0,0 +1,36 @@
+// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+// http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#pragma once
+
+namespace paddle {
+namespace framework {
+namespace details {
+
+struct BuildStrategy {
+ enum class ReduceStrategy { kAllReduce = 0, kReduce = 1 };
+
+ enum class GradientScaleStrategy {
+ kCoeffNumDevice = 0,
+ kOne = 1,
+ kCustomized = 2,
+ };
+
+ ReduceStrategy reduce_{ReduceStrategy::kReduce};
+ GradientScaleStrategy gradient_scale_{GradientScaleStrategy::kCoeffNumDevice};
+};
+
+} // namespace details
+} // namespace framework
+} // namespace paddle
diff --git a/paddle/fluid/framework/details/multi_devices_graph_builder.cc b/paddle/fluid/framework/details/multi_devices_graph_builder.cc
index 4755559f8d..45bad58145 100644
--- a/paddle/fluid/framework/details/multi_devices_graph_builder.cc
+++ b/paddle/fluid/framework/details/multi_devices_graph_builder.cc
@@ -37,31 +37,26 @@ MultiDevSSAGraphBuilder::MultiDevSSAGraphBuilder(
const std::string &loss_var_name,
const std::unordered_set<std::string> ¶ms,
const std::vector<Scope *> &local_scopes,
- platform::NCCLContextMap *nccl_ctxs, bool use_default_grad_scale,
- bool balance_parameter_opt_between_cards)
+ platform::NCCLContextMap *nccl_ctxs, const BuildStrategy &strategy)
: loss_var_name_(loss_var_name),
places_(places),
local_scopes_(local_scopes),
nccl_ctxs_(nccl_ctxs),
- balance_parameter_opt_between_cards_(
- balance_parameter_opt_between_cards) {
+ strategy_(strategy) {
#else
MultiDevSSAGraphBuilder::MultiDevSSAGraphBuilder(
const std::vector<platform::Place> &places,
const std::string &loss_var_name,
const std::unordered_set<std::string> ¶ms,
- const std::vector<Scope *> &local_scopes, bool use_default_grad_scale,
- bool balance_parameter_opt_between_cards)
+ const std::vector<Scope *> &local_scopes, const BuildStrategy &strategy)
: loss_var_name_(loss_var_name),
places_(places),
local_scopes_(local_scopes),
- balance_parameter_opt_between_cards_(
- balance_parameter_opt_between_cards) {
+ strategy_(strategy) {
#endif
for (auto &p : params) {
grad_names_.insert(GradVarName(p));
}
- use_default_grad_scale_ = use_default_grad_scale;
}
void MultiDevSSAGraphBuilder::CreateOpHandleIOs(SSAGraph *result,
@@ -146,7 +141,8 @@ std::unique_ptr<SSAGraph> MultiDevSSAGraphBuilder::Build(
CreateComputationalOps(&result, *op, 1);
} else if (IsScaleLossOp(*op)) {
// user can customize loss@grad if not use_default_grad_scale_
- if (use_default_grad_scale_) {
+ if (strategy_.gradient_scale_ !=
+ BuildStrategy::GradientScaleStrategy::kCustomized) {
CreateScaleLossGradOp(&result);
}
is_forwarding = false;
@@ -165,19 +161,22 @@ std::unique_ptr<SSAGraph> MultiDevSSAGraphBuilder::Build(
// broadcast, and each gradient is only broadcast once.
for (auto &og : op->OutputArgumentNames()) {
if (IsParameterGradientOnce(og, &og_has_been_broadcast)) {
- if (balance_parameter_opt_between_cards_) {
- CreateReduceOp(&result, og, cur_device_id);
- var_name_on_devices[cur_device_id].emplace(og);
- bcast_var_name_set[cur_device_id].emplace(
- og.substr(0, og.size() - strlen(kGradVarSuffix)));
- cur_device_id = (cur_device_id + 1) % places_.size();
- } else {
- if (IsSparseGradient(var_types, og)) {
- CreateReduceOp(&result, og, 0);
- CreateBroadcastOp(&result, og, 0);
- } else {
- InsertNCCLAllReduceOp(&result, og);
- }
+ switch (strategy_.reduce_) {
+ case BuildStrategy::ReduceStrategy::kReduce:
+ CreateReduceOp(&result, og, cur_device_id);
+ var_name_on_devices[cur_device_id].emplace(og);
+ bcast_var_name_set[cur_device_id].emplace(
+ og.substr(0, og.size() - strlen(kGradVarSuffix)));
+ cur_device_id = (cur_device_id + 1) % places_.size();
+ break;
+ case BuildStrategy::ReduceStrategy::kAllReduce:
+ if (IsSparseGradient(var_types, og)) {
+ CreateReduceOp(&result, og, 0);
+ CreateBroadcastOp(&result, og, 0);
+ } else {
+ InsertNCCLAllReduceOp(&result, og);
+ }
+ break;
}
}
}
@@ -303,7 +302,7 @@ bool MultiDevSSAGraphBuilder::IsParameterGradientOnce(
int MultiDevSSAGraphBuilder::GetOpDeviceID(
const std::vector<std::unordered_set<std::string>> &var_name_on_devices,
const OpDesc &op) const {
- if (!balance_parameter_opt_between_cards_) {
+ if (strategy_.reduce_ != BuildStrategy::ReduceStrategy::kReduce) {
return -1;
}
diff --git a/paddle/fluid/framework/details/multi_devices_graph_builder.h b/paddle/fluid/framework/details/multi_devices_graph_builder.h
index 3a3e9e3b85..4f70852188 100644
--- a/paddle/fluid/framework/details/multi_devices_graph_builder.h
+++ b/paddle/fluid/framework/details/multi_devices_graph_builder.h
@@ -17,6 +17,7 @@
#include <utility>
#include <vector>
+#include "paddle/fluid/framework/details/build_strategy.h"
#include "paddle/fluid/framework/details/ssa_graph_builder.h"
namespace paddle {
@@ -36,15 +37,13 @@ class MultiDevSSAGraphBuilder : public SSAGraphBuilder {
const std::unordered_set<std::string> ¶ms,
const std::vector<Scope *> &local_scopes,
platform::NCCLContextMap *nccl_ctxs,
- bool use_default_grad_scale,
- bool balance_parameter_opt_between_cards);
+ const BuildStrategy &strategy);
#else
MultiDevSSAGraphBuilder(const std::vector<platform::Place> &places,
const std::string &loss_var_name,
const std::unordered_set<std::string> ¶ms,
const std::vector<Scope *> &local_scopes,
- bool use_default_grad_scale,
- bool balance_parameter_opt_between_cards);
+ const BuildStrategy &strategy);
#endif
std::unique_ptr<SSAGraph> Build(const ProgramDesc &program) const override;
@@ -62,8 +61,6 @@ class MultiDevSSAGraphBuilder : public SSAGraphBuilder {
#ifdef PADDLE_WITH_CUDA
platform::NCCLContextMap *nccl_ctxs_;
#endif
- bool balance_parameter_opt_between_cards_;
- bool use_default_grad_scale_;
bool IsScaleLossOp(const OpDesc &op) const;
@@ -105,6 +102,9 @@ class MultiDevSSAGraphBuilder : public SSAGraphBuilder {
bool IsSparseGradient(
const std::unordered_map<std::string, proto::VarType::Type> &var_types,
const std::string &og) const;
+
+ private:
+ BuildStrategy strategy_;
};
} // namespace details
} // namespace framework
diff --git a/paddle/fluid/framework/parallel_executor.cc b/paddle/fluid/framework/parallel_executor.cc
index cdfd0a8c07..392b13d3dc 100644
--- a/paddle/fluid/framework/parallel_executor.cc
+++ b/paddle/fluid/framework/parallel_executor.cc
@@ -57,8 +57,7 @@ ParallelExecutor::ParallelExecutor(
const std::unordered_set<std::string> &bcast_vars,
const ProgramDesc &main_program, const std::string &loss_var_name,
Scope *scope, const std::vector<Scope *> &local_scopes,
- bool use_default_grad_scale, bool balance_parameter_opt_between_cards,
- const ExecutionStrategy &exec_strategy)
+ const ExecutionStrategy &exec_strategy, const BuildStrategy &build_strategy)
: member_(new ParallelExecutorPrivate(places)) {
member_->global_scope_ = scope;
@@ -93,12 +92,11 @@ ParallelExecutor::ParallelExecutor(
#ifdef PADDLE_WITH_CUDA
details::MultiDevSSAGraphBuilder builder(
member_->places_, loss_var_name, params, member_->local_scopes_,
- member_->nccl_ctxs_.get(), use_default_grad_scale,
- balance_parameter_opt_between_cards);
+ member_->nccl_ctxs_.get(), build_strategy);
#else
- details::MultiDevSSAGraphBuilder builder(
- member_->places_, loss_var_name, params, member_->local_scopes_,
- use_default_grad_scale, balance_parameter_opt_between_cards);
+ details::MultiDevSSAGraphBuilder builder(member_->places_, loss_var_name,
+ params, member_->local_scopes_,
+ build_strategy);
#endif
auto graph = builder.Build(main_program);
diff --git a/paddle/fluid/framework/parallel_executor.h b/paddle/fluid/framework/parallel_executor.h
index ab50509124..121e74293c 100644
--- a/paddle/fluid/framework/parallel_executor.h
+++ b/paddle/fluid/framework/parallel_executor.h
@@ -14,6 +14,7 @@ limitations under the License. */
#pragma once
+#include <paddle/fluid/framework/details/build_strategy.h>
#include <string>
#include <unordered_set>
#include <vector>
@@ -29,6 +30,7 @@ namespace framework {
class ParallelExecutorPrivate;
+using details::BuildStrategy;
using details::ExecutionStrategy;
class ParallelExecutor {
@@ -41,9 +43,8 @@ class ParallelExecutor {
const ProgramDesc &main_program,
const std::string &loss_var_name, Scope *scope,
const std::vector<Scope *> &local_scopes,
- bool use_default_grad_scale,
- bool balance_parameter_opt_between_cards,
- const ExecutionStrategy &exec_strategy);
+ const ExecutionStrategy &exec_strategy,
+ const BuildStrategy &build_strategy);
~ParallelExecutor();
diff --git a/paddle/fluid/platform/nccl_helper.h b/paddle/fluid/platform/nccl_helper.h
index 0013597fd5..ec1682a44e 100644
--- a/paddle/fluid/platform/nccl_helper.h
+++ b/paddle/fluid/platform/nccl_helper.h
@@ -50,7 +50,7 @@ class NCCLGroupGuard {
}
inline ~NCCLGroupGuard() {
- PADDLE_ENFORCE(dynload::ncclGroupEnd());
+ CHECK_EQ(dynload::ncclGroupEnd(), ncclSuccess);
NCCLMutex().unlock();
}
};
diff --git a/paddle/fluid/pybind/pybind.cc b/paddle/fluid/pybind/pybind.cc
index c456bc1a71..ee2c5b9044 100644
--- a/paddle/fluid/pybind/pybind.cc
+++ b/paddle/fluid/pybind/pybind.cc
@@ -494,6 +494,7 @@ All parameter, weight, gradient are variables in Paddle.
m.def("disable_profiler", platform::DisableProfiler);
m.def("reset_profiler", platform::ResetProfiler);
+ // -- python binds for parallel executor.
py::class_<ParallelExecutor> pe(m, "ParallelExecutor");
py::class_<ExecutionStrategy>(pe, "ExecutionStrategy")
.def(py::init())
@@ -515,12 +516,38 @@ All parameter, weight, gradient are variables in Paddle.
[](ExecutionStrategy &self, bool allow_op_delay) {
self.allow_op_delay_ = allow_op_delay;
});
+ py::class_<BuildStrategy> build_strategy(pe, "BuildStrategy");
+
+ py::enum_<BuildStrategy::ReduceStrategy>(build_strategy, "ReduceStrategy")
+ .value("Reduce", BuildStrategy::ReduceStrategy::kReduce)
+ .value("AllReduce", BuildStrategy::ReduceStrategy::kAllReduce);
+ py::enum_<BuildStrategy::GradientScaleStrategy>(build_strategy,
+ "GradientScaleStrategy")
+ .value("CoeffNumDevice",
+ BuildStrategy::GradientScaleStrategy::kCoeffNumDevice)
+ .value("One", BuildStrategy::GradientScaleStrategy::kOne)
+ .value("Customized", BuildStrategy::GradientScaleStrategy::kCustomized);
+
+ build_strategy.def(py::init())
+ .def_property(
+ "reduce_strategy",
+ [](const BuildStrategy &self) { return self.reduce_; },
+ [](BuildStrategy &self, BuildStrategy::ReduceStrategy strategy) {
+ self.reduce_ = strategy;
+ })
+ .def_property(
+ "gradient_scale_strategy",
+ [](const BuildStrategy &self) { return self.gradient_scale_; },
+ [](BuildStrategy &self,
+ BuildStrategy::GradientScaleStrategy strategy) {
+ self.gradient_scale_ = strategy;
+ });
pe.def(py::init<const std::vector<platform::Place> &,
const std::unordered_set<std::string> &,
const std::unordered_set<std::string> &, const ProgramDesc &,
- const std::string &, Scope *, std::vector<Scope *> &, bool,
- bool, const ExecutionStrategy &>())
+ const std::string &, Scope *, std::vector<Scope *> &,
+ const ExecutionStrategy &, const BuildStrategy &>())
.def("bcast_params", &ParallelExecutor::BCastParamsToGPUs)
// NOTE: even we return a vec<Scope*>* to Python use reference policy.
// We still cannot get local_scope from this vector, since the element
diff --git a/python/paddle/fluid/__init__.py b/python/paddle/fluid/__init__.py
index ef7a586475..67aa5ec997 100644
--- a/python/paddle/fluid/__init__.py
+++ b/python/paddle/fluid/__init__.py
@@ -52,12 +52,14 @@ import clip
import profiler
import unique_name
import recordio_writer
-from parallel_executor import ParallelExecutor, ExecutionStrategy
+import parallel_executor
+from parallel_executor import *
Tensor = LoDTensor
__all__ = framework.__all__ + executor.__all__ + concurrency.__all__ + \
- trainer.__all__ + inferencer.__all__ + transpiler.__all__ + [
+ trainer.__all__ + inferencer.__all__ + transpiler.__all__ + \
+ parallel_executor.__all__ + [
'io',
'initializer',
'layers',
@@ -79,8 +81,6 @@ __all__ = framework.__all__ + executor.__all__ + concurrency.__all__ + \
'profiler',
'unique_name',
'recordio_writer',
- 'ParallelExecutor',
- 'ExecutionStrategy',
]
diff --git a/python/paddle/fluid/parallel_executor.py b/python/paddle/fluid/parallel_executor.py
index 69ea9ee335..deab761f72 100644
--- a/python/paddle/fluid/parallel_executor.py
+++ b/python/paddle/fluid/parallel_executor.py
@@ -19,9 +19,10 @@ import executor
import warnings
import sys
-__all__ = ['ParallelExecutor', 'ExecutionStrategy']
+__all__ = ['ParallelExecutor', 'ExecutionStrategy', 'BuildStrategy']
ExecutionStrategy = core.ParallelExecutor.ExecutionStrategy
+BuildStrategy = core.ParallelExecutor.BuildStrategy
class ParallelExecutor(object):
@@ -30,9 +31,8 @@ class ParallelExecutor(object):
loss_name=None,
main_program=None,
share_vars_from=None,
- use_default_grad_scale=True,
- balance_parameter_opt_between_cards=False,
exec_strategy=None,
+ build_strategy=None,
**kwargs):
"""
ParallelExecutor can run program in parallel.
@@ -81,7 +81,16 @@ class ParallelExecutor(object):
"Setting {0} by constructor is deprecated. Use " \
"strategy=ExecutionStrategy(); strategy.{0}=xxx; " \
"pe=ParallelExecutor(exec_strategy=strategy) " \
- "instead.\n "
+ "instead.\n ".format(key)
+ elif key in dir(BuildStrategy):
+ err_msg += \
+ "Setting {0} by constructor is deprecated. Use " \
+ "strategy=BuildStrategy(); See help(" \
+ "paddle.fluid.ParallelExecutor.BuildStrategy) \n".format(
+ key)
+ else:
+ err_msg += "Setting {0} by constructor is deprecated. Use strategy.\n".format(
+ key)
raise ValueError(err_msg)
self._places = []
@@ -116,6 +125,9 @@ class ParallelExecutor(object):
exec_strategy.num_threads = min(
len(self._places) * 2, multiprocessing.cpu_count())
+ if build_strategy is None:
+ build_strategy = BuildStrategy()
+
main = main_program
main = main if main else framework.default_main_program()
scope = executor.global_scope()
@@ -139,9 +151,8 @@ class ParallelExecutor(object):
p.name for p in main.global_block().iter_parameters()
if not p.stop_gradient
]),
- set(self.persistable_vars), main.desc, loss_name
- if loss_name else '', scope, local_scopes, use_default_grad_scale,
- balance_parameter_opt_between_cards, exec_strategy)
+ set(self.persistable_vars), main.desc, loss_name if loss_name else
+ '', scope, local_scopes, exec_strategy, build_strategy)
self.scope = scope
diff --git a/python/paddle/fluid/tests/unittests/test_parallel_executor.py b/python/paddle/fluid/tests/unittests/test_parallel_executor.py
index 4173ad1925..cd95ee47fd 100644
--- a/python/paddle/fluid/tests/unittests/test_parallel_executor.py
+++ b/python/paddle/fluid/tests/unittests/test_parallel_executor.py
@@ -234,12 +234,16 @@ class TestParallelExecutorBase(unittest.TestCase):
startup_exe.run(startup)
exec_strategy = fluid.ExecutionStrategy()
exec_strategy.allow_op_delay = allow_op_delay
+
+ build_strategy = fluid.BuildStrategy()
+ build_strategy.reduce_strategy = fluid.BuildStrategy.ReduceStrategy.Reduce if balance_parameter_opt_between_cards else fluid.BuildStrategy.ReduceStrategy.AllReduce
+
if use_parallel_executor:
exe = fluid.ParallelExecutor(
True,
loss_name=loss.name,
- balance_parameter_opt_between_cards=balance_parameter_opt_between_cards,
- exec_strategy=exec_strategy)
+ exec_strategy=exec_strategy,
+ build_strategy=build_strategy)
else:
exe = fluid.Executor(place=place)
@@ -548,7 +552,7 @@ class TestTransformer(TestParallelExecutorBase):
class ParallelExecutorTestingDuringTraining(unittest.TestCase):
- def check_network_convergence(self, balance_parameter_opt_between_cards):
+ def check_network_convergence(self, build_strategy=None):
main = fluid.Program()
startup = fluid.Program()
with fluid.program_guard(main, startup):
@@ -571,15 +575,13 @@ class ParallelExecutorTestingDuringTraining(unittest.TestCase):
use_cuda=True,
loss_name=loss.name,
main_program=main,
- balance_parameter_opt_between_cards=balance_parameter_opt_between_cards
- )
+ build_strategy=build_strategy)
test_exe = fluid.ParallelExecutor(
use_cuda=True,
main_program=test_program,
share_vars_from=train_exe,
- balance_parameter_opt_between_cards=balance_parameter_opt_between_cards
- )
+ build_strategy=build_strategy)
for i in xrange(5):
test_loss, = test_exe.run([loss.name], feed=feed_dict)
@@ -594,10 +596,14 @@ class ParallelExecutorTestingDuringTraining(unittest.TestCase):
str(test_loss))
def test_parallel_testing(self):
- self.check_network_convergence(False)
+ build_strategy = fluid.BuildStrategy()
+ build_strategy.reduce_strategy = fluid.BuildStrategy.ReduceStrategy.AllReduce
+ self.check_network_convergence(build_strategy)
def test_parallel_testing_with_new_strategy(self):
- self.check_network_convergence(True)
+ build_strategy = fluid.BuildStrategy()
+ build_strategy.reduce_strategy = fluid.BuildStrategy.ReduceStrategy.Reduce
+ self.check_network_convergence(build_strategy)
import paddle.dataset.conll05 as conll05
@@ -617,7 +623,7 @@ embedding_name = 'emb'
def db_lstm(word, predicate, ctx_n2, ctx_n1, ctx_0, ctx_p1, ctx_p2, mark,
- is_sparse, balance_parameter_opt_between_cards, **ignored):
+ is_sparse, **ignored):
# 8 features
predicate_embedding = fluid.layers.embedding(
input=predicate,
@@ -686,9 +692,7 @@ def db_lstm(word, predicate, ctx_n2, ctx_n1, ctx_0, ctx_p1, ctx_p2, mark,
class TestCRFModel(unittest.TestCase):
- def check_network_convergence(self,
- is_sparse,
- balance_parameter_opt_between_cards=False):
+ def check_network_convergence(self, is_sparse, build_strategy=None):
main = fluid.Program()
startup = fluid.Program()
with fluid.program_guard(main, startup):
@@ -739,8 +743,7 @@ class TestCRFModel(unittest.TestCase):
pe = fluid.ParallelExecutor(
use_cuda=True,
loss_name=avg_cost.name,
- balance_parameter_opt_between_cards=balance_parameter_opt_between_cards
- )
+ build_strategy=build_strategy)
feeder = fluid.DataFeeder(
feed_list=[
@@ -756,19 +759,29 @@ class TestCRFModel(unittest.TestCase):
pe.run(feed=feeder.feed(cur_batch),
fetch_list=[avg_cost.name]))[0]
- def test_update_sparse_parameter(self):
- self.check_network_convergence(is_sparse=True)
+ def test_update_sparse_parameter_all_reduce(self):
+ build_strategy = fluid.BuildStrategy()
+ build_strategy.reduce_strategy = fluid.BuildStrategy.ReduceStrategy.AllReduce
+ self.check_network_convergence(
+ is_sparse=True, build_strategy=build_strategy)
- def test_update_dense_parameter(self):
- self.check_network_convergence(is_sparse=False)
+ def test_update_dense_parameter_all_reduce(self):
+ build_strategy = fluid.BuildStrategy()
+ build_strategy.reduce_strategy = fluid.BuildStrategy.ReduceStrategy.AllReduce
+ self.check_network_convergence(
+ is_sparse=False, build_strategy=build_strategy)
- def test_update_sparse_parameter_with_new_strategy(self):
+ def test_update_sparse_parameter_reduce(self):
+ build_strategy = fluid.BuildStrategy()
+ build_strategy.reduce_strategy = fluid.BuildStrategy.ReduceStrategy.Reduce
self.check_network_convergence(
- is_sparse=False, balance_parameter_opt_between_cards=True)
+ is_sparse=False, build_strategy=build_strategy)
- def test_update_dense_parameter_with_new_strategy(self):
+ def test_update_dense_parameter_reduce(self):
+ build_strategy = fluid.BuildStrategy()
+ build_strategy.reduce_strategy = fluid.BuildStrategy.ReduceStrategy.Reduce
self.check_network_convergence(
- is_sparse=False, balance_parameter_opt_between_cards=True)
+ is_sparse=False, build_strategy=build_strategy)
# test fetch all the variables of global_block
From 66e82b986928ac00e8cb26b13341cd78252207f3 Mon Sep 17 00:00:00 2001
From: yuyang18 <reyoung@126.com>
Date: Mon, 14 May 2018 19:05:40 +0800
Subject: [PATCH 094/195] Change implementation to fit sphinx model
---
paddle/fluid/framework/data_type.cc | 52 ++++++++++++++---------------
1 file changed, 26 insertions(+), 26 deletions(-)
diff --git a/paddle/fluid/framework/data_type.cc b/paddle/fluid/framework/data_type.cc
index 28bbf82bc8..48267e1e34 100644
--- a/paddle/fluid/framework/data_type.cc
+++ b/paddle/fluid/framework/data_type.cc
@@ -14,7 +14,6 @@
#include "paddle/fluid/framework/data_type.h"
#include <stdint.h>
-#include <mutex> // NOLINT
#include <string>
#include <unordered_map>
@@ -28,20 +27,27 @@ struct DataTypeMap {
std::unordered_map<std::type_index, size_t> cpp_to_size_;
};
-static DataTypeMap g_data_type_map_;
+static DataTypeMap* InitDataTypeMap();
+static DataTypeMap& gDataTypeMap() {
+ static DataTypeMap* g_data_type_map_ = InitDataTypeMap();
+ return *g_data_type_map_;
+}
template <typename T>
-static inline void RegisterType(proto::VarType::Type proto_type,
- const std::string &name) {
- g_data_type_map_.proto_to_cpp_.emplace(static_cast<int>(proto_type),
- typeid(T));
- g_data_type_map_.cpp_to_proto_.emplace(typeid(T), proto_type);
- g_data_type_map_.proto_to_str_.emplace(static_cast<int>(proto_type), name);
- g_data_type_map_.cpp_to_size_.emplace(typeid(T), sizeof(T));
+static inline void RegisterType(DataTypeMap* map,
+ proto::VarType::Type proto_type,
+ const std::string& name) {
+ map->proto_to_cpp_.emplace(static_cast<int>(proto_type), typeid(T));
+ map->cpp_to_proto_.emplace(typeid(T), proto_type);
+ map->proto_to_str_.emplace(static_cast<int>(proto_type), name);
+ map->cpp_to_size_.emplace(typeid(T), sizeof(T));
}
-static int RegisterAllTypes() {
-#define RegType(cc_type, proto_type) RegisterType<cc_type>(proto_type, #cc_type)
+static DataTypeMap* InitDataTypeMap() {
+ auto retv = new DataTypeMap();
+
+#define RegType(cc_type, proto_type) \
+ RegisterType<cc_type>(retv, proto_type, #cc_type)
// NOTE: Add your customize type here.
RegType(platform::float16, proto::VarType::FP16);
@@ -52,24 +58,20 @@ static int RegisterAllTypes() {
RegType(bool, proto::VarType::BOOL);
#undef RegType
- return 0;
+ return retv;
}
-static std::once_flag register_once_flag_;
-
proto::VarType::Type ToDataType(std::type_index type) {
- std::call_once(register_once_flag_, RegisterAllTypes);
- auto it = g_data_type_map_.cpp_to_proto_.find(type);
- if (it != g_data_type_map_.cpp_to_proto_.end()) {
+ auto it = gDataTypeMap().cpp_to_proto_.find(type);
+ if (it != gDataTypeMap().cpp_to_proto_.end()) {
return it->second;
}
PADDLE_THROW("Not support %s as tensor type", type.name());
}
std::type_index ToTypeIndex(proto::VarType::Type type) {
- std::call_once(register_once_flag_, RegisterAllTypes);
- auto it = g_data_type_map_.proto_to_cpp_.find(static_cast<int>(type));
- if (it != g_data_type_map_.proto_to_cpp_.end()) {
+ auto it = gDataTypeMap().proto_to_cpp_.find(static_cast<int>(type));
+ if (it != gDataTypeMap().proto_to_cpp_.end()) {
return it->second;
}
PADDLE_THROW("Not support proto::VarType::Type(%d) as tensor type",
@@ -77,9 +79,8 @@ std::type_index ToTypeIndex(proto::VarType::Type type) {
}
std::string DataTypeToString(const proto::VarType::Type type) {
- std::call_once(register_once_flag_, RegisterAllTypes);
- auto it = g_data_type_map_.proto_to_str_.find(static_cast<int>(type));
- if (it != g_data_type_map_.proto_to_str_.end()) {
+ auto it = gDataTypeMap().proto_to_str_.find(static_cast<int>(type));
+ if (it != gDataTypeMap().proto_to_str_.end()) {
return it->second;
}
PADDLE_THROW("Not support proto::VarType::Type(%d) as tensor type",
@@ -87,9 +88,8 @@ std::string DataTypeToString(const proto::VarType::Type type) {
}
size_t SizeOfType(std::type_index type) {
- std::call_once(register_once_flag_, RegisterAllTypes);
- auto it = g_data_type_map_.cpp_to_size_.find(type);
- if (it != g_data_type_map_.cpp_to_size_.end()) {
+ auto it = gDataTypeMap().cpp_to_size_.find(type);
+ if (it != gDataTypeMap().cpp_to_size_.end()) {
return it->second;
}
PADDLE_THROW("Not support %s as tensor type", type.name());
From 6d8cc88de31140b9ddf9f43a4ec347bb78cb2bc7 Mon Sep 17 00:00:00 2001
From: yuyang18 <reyoung@126.com>
Date: Mon, 14 May 2018 19:07:13 +0800
Subject: [PATCH 095/195] Change cmake for build doc
Check the system requirements
---
CMakeLists.txt | 3 ++-
1 file changed, 2 insertions(+), 1 deletion(-)
diff --git a/CMakeLists.txt b/CMakeLists.txt
index 23bbe829ac..030bd19b3f 100644
--- a/CMakeLists.txt
+++ b/CMakeLists.txt
@@ -25,7 +25,6 @@ message(STATUS "CXX compiler: ${CMAKE_CXX_COMPILER}, version: "
message(STATUS "C compiler: ${CMAKE_C_COMPILER}, version: "
"${CMAKE_C_COMPILER_ID} ${CMAKE_C_COMPILER_VERSION}")
-find_package(Sphinx)
if(NOT CMAKE_CROSSCOMPILING)
find_package(CUDA QUIET)
endif(NOT CMAKE_CROSSCOMPILING)
@@ -226,5 +225,7 @@ if(WITH_PYTHON)
endif()
if(WITH_DOC)
+ find_package(Sphinx REQUIRED)
+ find_python_module(recommonmark REQUIRED)
add_subdirectory(doc)
endif()
From de81ccb5cb0b0dafa45b6bceaab3bd4f45a1f6b2 Mon Sep 17 00:00:00 2001
From: Yan Chunwei <yanchunwei@outlook.com>
Date: Mon, 14 May 2018 21:07:04 +0800
Subject: [PATCH 096/195] feature/analysis node representation (#10522)
---
.../fluid/inference/analysis/CMakeLists.txt | 3 +-
paddle/fluid/inference/analysis/device.h | 23 ++
paddle/fluid/inference/analysis/dot_tester.cc | 62 +++++
paddle/fluid/inference/analysis/helper.h | 74 ++++++
paddle/fluid/inference/analysis/node.cc | 67 +++++
paddle/fluid/inference/analysis/node.h | 234 ++++++++++++++++++
.../fluid/inference/analysis/node_tester.cc | 34 +++
7 files changed, 496 insertions(+), 1 deletion(-)
create mode 100644 paddle/fluid/inference/analysis/device.h
create mode 100644 paddle/fluid/inference/analysis/dot_tester.cc
create mode 100644 paddle/fluid/inference/analysis/helper.h
create mode 100644 paddle/fluid/inference/analysis/node.cc
create mode 100644 paddle/fluid/inference/analysis/node.h
create mode 100644 paddle/fluid/inference/analysis/node_tester.cc
diff --git a/paddle/fluid/inference/analysis/CMakeLists.txt b/paddle/fluid/inference/analysis/CMakeLists.txt
index de7becae4d..47929ef749 100644
--- a/paddle/fluid/inference/analysis/CMakeLists.txt
+++ b/paddle/fluid/inference/analysis/CMakeLists.txt
@@ -1 +1,2 @@
-cc_library(dot SRCS dot.cc)
+cc_library(analysis SRCS dot.cc node.cc node.h)
+cc_test(test_node SRCS node_tester.cc DEPS analysis)
diff --git a/paddle/fluid/inference/analysis/device.h b/paddle/fluid/inference/analysis/device.h
new file mode 100644
index 0000000000..4423af842d
--- /dev/null
+++ b/paddle/fluid/inference/analysis/device.h
@@ -0,0 +1,23 @@
+/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License. */
+
+namespace paddle {
+namespace inference {
+namespace analysis {
+
+enum class Device { CPU, GPU };
+
+} // namespace analysis
+} // namespace inference
+} // namespace paddle
diff --git a/paddle/fluid/inference/analysis/dot_tester.cc b/paddle/fluid/inference/analysis/dot_tester.cc
new file mode 100644
index 0000000000..56ceb9bd5d
--- /dev/null
+++ b/paddle/fluid/inference/analysis/dot_tester.cc
@@ -0,0 +1,62 @@
+// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+// http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include "paddle/fluid/inference/analysis/dot.h"
+
+#include <gtest/gtest.h>
+#include <memory>
+#include "paddle/fluid/inference/analysis/data_flow_graph.h"
+
+namespace paddle {
+namespace inference {
+namespace analysis {
+
+class DotTester : public ::testing::Test {
+ protected:
+ void SetUp() override {
+ std::vector<Dot::Attr> attrs({{"title", "hello"}});
+ dot.reset(new Dot(attrs));
+ dot->AddNode("a", {Dot::Attr{"shape", "box"}, Dot::Attr("color", "blue")});
+ dot->AddNode("b", {});
+ dot->AddNode("c", {});
+ dot->AddEdge("a", "b", {});
+ dot->AddEdge("b", "c", {});
+ dot->AddEdge("a", "c", {});
+ }
+
+ std::unique_ptr<Dot> dot;
+};
+
+TEST_F(DotTester, Build) {
+ auto codes = dot->Build();
+ // Output the DOT language code, the generated codes are too long to compare
+ // the string.
+ //
+ // The output is
+ //
+ // digraph G {
+ // title="hello"
+ // node_1
+ // node_2
+ // node_0[label="a" shape="box" color="blue"]
+ // node_0->node_1
+ // node_1->node_2
+ // node_0->node_2
+ // } // end G
+ LOG(INFO) << '\n' << codes;
+}
+
+} // namespace analysis
+} // namespace inference
+} // namespace paddle
diff --git a/paddle/fluid/inference/analysis/helper.h b/paddle/fluid/inference/analysis/helper.h
new file mode 100644
index 0000000000..b2d06c5d63
--- /dev/null
+++ b/paddle/fluid/inference/analysis/helper.h
@@ -0,0 +1,74 @@
+/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License. */
+
+#pragma once
+
+#include <string>
+#include <unordered_map>
+#include <vector>
+
+#include "paddle/fluid/platform/enforce.h"
+
+namespace paddle {
+namespace inference {
+namespace analysis {
+
+template <typename IteratorT>
+class iterator_range {
+ IteratorT begin_, end_;
+
+ public:
+ template <typename Container>
+ explicit iterator_range(Container &&c) : begin_(c.begin()), end_(c.end()) {}
+
+ iterator_range(const IteratorT &begin, const IteratorT &end)
+ : begin_(begin), end_(end) {}
+
+ const IteratorT &begin() const { return begin_; }
+ const IteratorT &end() const { return end_; }
+};
+
+/*
+ * An registry helper class, with its records keeps the order they registers.
+ */
+template <typename T>
+class OrderedRegistry {
+ public:
+ T *Register(const std::string &name, T *x) {
+ PADDLE_ENFORCE(!dic_.count(name));
+ dic_[name] = data_.size();
+ data_.emplace_back(std::unique_ptr<T>(x));
+ return data_.back().get();
+ }
+
+ T *Lookup(const std::string &name) {
+ auto it = dic_.find(name);
+ if (it == dic_.end()) return nullptr;
+ return data_[it->second].get();
+ }
+
+ protected:
+ std::unordered_map<std::string, int> dic_;
+ std::vector<std::unique_ptr<T>> data_;
+};
+
+} // namespace analysis
+} // namespace inference
+} // namespace paddle
+
+#define PADDLE_DISALLOW_COPY_AND_ASSIGN(type__) \
+ \
+ type__(const type__ &) = delete; \
+ \
+ void operator=(const type__ &) = delete;
diff --git a/paddle/fluid/inference/analysis/node.cc b/paddle/fluid/inference/analysis/node.cc
new file mode 100644
index 0000000000..fe06052608
--- /dev/null
+++ b/paddle/fluid/inference/analysis/node.cc
@@ -0,0 +1,67 @@
+/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License. */
+
+#include "paddle/fluid/inference/analysis/node.h"
+#include "glog/logging.h"
+#include "paddle/fluid/platform/enforce.h"
+
+namespace paddle {
+namespace inference {
+namespace analysis {
+
+std::vector<Dot::Attr> Value::dot_attrs() const {
+ return std::vector<Dot::Attr>({Dot::Attr("style", "filled,rounded"),
+ Dot::Attr("shape", "box"),
+ Dot::Attr("fillcolor", "red")});
+}
+
+std::vector<Dot::Attr> Function::dot_attrs() const {
+ return std::vector<Dot::Attr>({Dot::Attr("style", "filled,rounded"),
+ Dot::Attr("shape", "diamond"),
+ Dot::Attr("fillcolor", "yellow")});
+}
+
+Node *NodeMap::Create(Node::Type type) {
+ switch (type) {
+ case Node::Type::kFunction:
+ nodes_.emplace_back(new Function);
+ break;
+ case Node::Type::kValue:
+ nodes_.emplace_back(new Value);
+ break;
+ default:
+ PADDLE_THROW("Not supported node type.");
+ }
+ nodes_.back()->id_ = size() - 1;
+ return nodes_.back().get();
+}
+
+Node *NodeMap::GetMutable(size_t id) {
+ PADDLE_ENFORCE_GT(size(), id);
+ return nodes_[id].get();
+}
+
+const Node &NodeMap::Get(size_t id) const {
+ PADDLE_ENFORCE_GT(size(), id);
+ return *nodes_[id].get();
+}
+
+void NodeMap::Delete(size_t id) {
+ PADDLE_ENFORCE_LT(id, size());
+ nodes_[id]->SetDeleted();
+}
+
+} // namespace analysis
+} // namespace inference
+} // namespace paddle
diff --git a/paddle/fluid/inference/analysis/node.h b/paddle/fluid/inference/analysis/node.h
new file mode 100644
index 0000000000..59ba977798
--- /dev/null
+++ b/paddle/fluid/inference/analysis/node.h
@@ -0,0 +1,234 @@
+/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License. */
+
+/*
+ * This file defines the Node class and its subclasses. A Node is the basis
+ * analysis element in a computation graph.
+ * There are basically two kinds of nodes, the function node and value node.
+ */
+#pragma once
+
+#include <memory>
+#include <string>
+#include <unordered_map>
+#include <vector>
+
+#include "paddle/fluid/inference/analysis/device.h"
+#include "paddle/fluid/inference/analysis/dot.h"
+#include "paddle/fluid/inference/analysis/helper.h"
+
+namespace paddle {
+namespace inference {
+namespace analysis {
+
+class NodeMap;
+
+/*
+ * Node Representation.
+ *
+ * This is a very important class for analysis. It is the base class of all
+ * nodes computed by a program that may be used as operands to other nodes.
+ * Node is the super class of other important classes such as Function and
+ * Value, some nodes can have a name.
+ */
+class Node {
+ public:
+ // Node type. NOTE the new node types should add here.
+ enum class Type { kNone = -1, kFunction, kValue, kFunctionBlock };
+
+ Node() = default;
+
+ struct Attr;
+
+ // Cast to a subclass type, Function for example.
+ template <typename Subclass>
+ Subclass &As() {
+ return *dynamic_cast<Subclass *>(this);
+ }
+
+ // Formatted representation of this Node.
+ virtual std::string repr() const {
+ return name() + "(" + std::to_string(id()) + ")";
+ }
+
+ // DOT node representation. One Node type can customize its own node
+ // representation.
+ virtual std::vector<Dot::Attr> dot_attrs() const {
+ return std::vector<Dot::Attr>({Dot::Attr("style", "filled")});
+ }
+
+ // Get an additional attribute and convert it to T data type. NOTE this will
+ // silently create a new attribute if not exists.
+ Attr &attr(const std::string &name) { return attrs_[name]; }
+
+ int id() const { return id_; }
+
+ bool deleted() const { return deleted_; }
+ void SetDeleted() { deleted_ = true; }
+
+ void SetName(const std::string &name) { name_ = name; }
+ const std::string &name() const { return name_; }
+
+ void SetType(Type type) { type_ = type; }
+ Type type() const { return type_; }
+
+ void *extra_info() const { return extra_info_; }
+ void SetExtraInfo(void *extra_info) { extra_info_ = extra_info; }
+
+ // Input links.
+ std::vector<Node *> inlinks;
+ // Output links.
+ std::vector<Node *> outlinks;
+
+ // A helper class to maintain the status from Pass.
+ // TODO(superjomn) add a checker here to ensure the T is primary.
+ struct Attr {
+ // NOTE T should be a primary type or a struct combined by several primary
+ // types.
+ // NOTE the STL containers should not use here.
+ // Some usages
+ // Attr attr;
+ // T data;
+ // attr.data.assign((char*)data, sizeof(data));
+
+ bool &Bool() { return As<bool>(); }
+ float &Float() { return As<float>(); }
+ int32_t &Int32() { return As<int32_t>(); }
+ int64_t &Int64() { return As<int64_t>(); }
+
+ private:
+ template <typename T>
+ T &As() {
+ // init storage in the first usage.
+ if (data_.empty()) {
+ VLOG(4) << "resize data to " << sizeof(T);
+ type_hash_ = typeid(T).hash_code();
+ data_.resize(sizeof(T));
+ }
+ PADDLE_ENFORCE(type_hash_ == typeid(T).hash_code(), "type not matched");
+ PADDLE_ENFORCE_EQ(data_.size(), sizeof(T), "Node attr type recast error");
+ return *reinterpret_cast<T *>(&data_[0]);
+ }
+
+ private:
+ std::string data_;
+ size_t type_hash_{std::numeric_limits<size_t>::max()};
+ };
+
+ virtual ~Node() {}
+
+ friend class NodeMap;
+
+ PADDLE_DISALLOW_COPY_AND_ASSIGN(Node);
+
+ protected:
+ // The id number not the name is a node's unique identifier in the computation
+ // graph.
+ int id_{-1};
+ std::string name_;
+ Type type_{Type::kNone};
+ // Mark this node is deleted by some pass.
+ bool deleted_{false};
+
+ void *extra_info_;
+
+ mutable std::unordered_map<std::string, Attr> attrs_;
+};
+
+class Function;
+/*
+ * Value represents a value node, it has some attributes including dims, data
+ * type and so on.
+ */
+class Value : public Node {
+ public:
+ enum class DataType { kInt32, kInt64, kFloat32, kFloat64 };
+ using Dims = std::vector<int>;
+
+ void SetDataType(DataType data_type) { data_type_ = data_type; }
+ DataType data_type() const { return data_type_; }
+
+ void SetDims(const Dims &dims) { dims_ = dims; }
+ const Dims &dims() const { return dims_; }
+
+ Device device() const { return device_; }
+ void SetDevice(Device device) { device_ = device; }
+
+ std::vector<Dot::Attr> dot_attrs() const override;
+
+ PADDLE_DISALLOW_COPY_AND_ASSIGN(Value);
+
+ protected:
+ Value() { SetType(Node::Type::kValue); }
+ friend class NodeMap;
+
+ private:
+ DataType data_type_;
+ Dims dims_;
+ Device device_;
+};
+
+/*
+ * Function represents any kind of executable concepts that takes several Values
+ * as input, and outputs several Values.
+ */
+class Function : public Node {
+ public:
+ std::vector<Dot::Attr> dot_attrs() const override;
+
+ // Get the operator's type from Desc.
+ const std::string &func_type() const { return func_type_; }
+ // Set the operator's type.
+ void SetFuncType(const std::string &func_type) { func_type_ = func_type; }
+
+ PADDLE_DISALLOW_COPY_AND_ASSIGN(Function);
+
+ protected:
+ std::string func_type_;
+ Function() { SetType(Node::Type::kFunction); }
+ friend class NodeMap;
+};
+
+/*
+ * FunctionBlock is a Node that contains a sub-graph multiple Node.
+ */
+struct FunctionBlock : public Node {
+ std::string repr() const override { return "block-" + std::to_string(id()); }
+ std::vector<Node *> subgraph;
+};
+
+class NodeMap {
+ public:
+ // Create a new node with type.
+ Node *Create(Node::Type type);
+
+ // Get a node by its id.
+ Node *GetMutable(size_t id);
+
+ const Node &Get(size_t id) const;
+
+ void Delete(size_t id);
+
+ const std::vector<std::unique_ptr<Node>> &nodes() { return nodes_; }
+
+ size_t size() const { return nodes_.size(); }
+
+ private:
+ std::vector<std::unique_ptr<Node>> nodes_;
+ std::unordered_map<std::string, Node *> map_;
+};
+
+} // namespace analysis
+} // namespace inference
+} // namespace paddle
diff --git a/paddle/fluid/inference/analysis/node_tester.cc b/paddle/fluid/inference/analysis/node_tester.cc
new file mode 100644
index 0000000000..47fea0fdff
--- /dev/null
+++ b/paddle/fluid/inference/analysis/node_tester.cc
@@ -0,0 +1,34 @@
+/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License. */
+
+#include "paddle/fluid/inference/analysis/node.h"
+
+#include <gtest/gtest.h>
+
+namespace paddle {
+namespace inference {
+namespace analysis {
+
+TEST(Node, Attr) {
+ // Node is an abstract class, use Value instead for they share the same Attr
+ // logic.
+ NodeMap nodes;
+ auto* node = nodes.Create(Node::Type::kValue);
+ node->attr("v0").Int32() = 2008;
+ ASSERT_EQ(node->attr("v0").Int32(), 2008);
+}
+
+} // namespace analysis
+} // namespace inference
+} // namespace paddle
From 4f5f0be769228a61bb91baf63faa6ca3a71382d0 Mon Sep 17 00:00:00 2001
From: Luo Tao <luotao02@baidu.com>
Date: Mon, 14 May 2018 21:19:34 +0800
Subject: [PATCH 097/195] use the latest buffer to update the convert
---
paddle/fluid/inference/engine.h | 4 ++--
paddle/fluid/inference/tensorrt/CMakeLists.txt | 1 -
paddle/fluid/inference/tensorrt/convert/CMakeLists.txt | 2 +-
paddle/fluid/inference/tensorrt/convert/io_converter.cc | 3 ++-
.../inference/tensorrt/convert/test_activation_op.cc | 8 ++++----
5 files changed, 9 insertions(+), 9 deletions(-)
diff --git a/paddle/fluid/inference/engine.h b/paddle/fluid/inference/engine.h
index c0e5f3b201..ce2b816171 100644
--- a/paddle/fluid/inference/engine.h
+++ b/paddle/fluid/inference/engine.h
@@ -59,8 +59,8 @@ class EngineBase {
struct Buffer {
void* buffer{nullptr}; // buffer should be allocated only once.
- int max_size; // buffer allocated space.
- int size; // data size.
+ size_t max_size; // buffer allocated space.
+ size_t size; // data size.
DeviceType device{DeviceType::UNK}; // tells which device this buffer is on.
};
diff --git a/paddle/fluid/inference/tensorrt/CMakeLists.txt b/paddle/fluid/inference/tensorrt/CMakeLists.txt
index 677b3e04af..b52d083f28 100644
--- a/paddle/fluid/inference/tensorrt/CMakeLists.txt
+++ b/paddle/fluid/inference/tensorrt/CMakeLists.txt
@@ -1,5 +1,4 @@
nv_library(tensorrt_engine SRCS engine.cc DEPS framework_proto)
nv_test(test_tensorrt SRCS test_tensorrt.cc DEPS dynload_cuda device_context dynamic_loader)
nv_test(test_tensorrt_engine SRCS test_engine.cc DEPS dynload_cuda tensorrt_engine)
-
add_subdirectory(convert)
diff --git a/paddle/fluid/inference/tensorrt/convert/CMakeLists.txt b/paddle/fluid/inference/tensorrt/convert/CMakeLists.txt
index 5178c54c08..4fb4511d99 100644
--- a/paddle/fluid/inference/tensorrt/convert/CMakeLists.txt
+++ b/paddle/fluid/inference/tensorrt/convert/CMakeLists.txt
@@ -1,4 +1,4 @@
nv_test(test_op_converter SRCS test_op_converter.cc mul_op.cc conv2d_op.cc DEPS ${FLUID_CORE_MODULES})
-nv_test(test_trt_activation_op SRCS test_activation_op.cc activation_op.cc
+nv_test(test_trt_activation_op SRCS test_activation_op.cc activation_op.cc io_converter.cc
DEPS ${FLUID_CORE_MODULES} activation_op tensorrt_engine)
nv_test(test_io_converter SRCS test_io_converter.cc io_converter.cc DEPS dynload_cuda dynamic_loader lod_tensor)
diff --git a/paddle/fluid/inference/tensorrt/convert/io_converter.cc b/paddle/fluid/inference/tensorrt/convert/io_converter.cc
index 13bc2b3759..2d583c0012 100644
--- a/paddle/fluid/inference/tensorrt/convert/io_converter.cc
+++ b/paddle/fluid/inference/tensorrt/convert/io_converter.cc
@@ -58,7 +58,7 @@ class DefaultIOConverter : public EngineIOConverter {
cudaMemcpyDeviceToHost, *stream_));
} else if (is_gpu_place(place)) {
PADDLE_ENFORCE_EQ(0, cudaMemcpyAsync(out->data<float>(), in, size,
- cudaMemcpyHostToHost, *stream_));
+ cudaMemcpyDeviceToDevice, *stream_));
} else {
PADDLE_THROW("Unknown device for converter");
}
@@ -66,6 +66,7 @@ class DefaultIOConverter : public EngineIOConverter {
}
};
+// fluid LodTensor <-> tensorrt ITensor
REGISTER_TENSORRT_IO_CONVERTER(default, DefaultIOConverter);
} // namespace tensorrt
diff --git a/paddle/fluid/inference/tensorrt/convert/test_activation_op.cc b/paddle/fluid/inference/tensorrt/convert/test_activation_op.cc
index c43f720212..3275b65bc6 100644
--- a/paddle/fluid/inference/tensorrt/convert/test_activation_op.cc
+++ b/paddle/fluid/inference/tensorrt/convert/test_activation_op.cc
@@ -74,13 +74,13 @@ void Compare(const std::string op_type, float input, float expect) {
// convert LoDTensor to ITensor
size_t size = x_tensor->memory_size();
- EngineIOConverter::ConvertInput(op_type, *x_tensor, engine->buffer("X"), size,
- &stream);
+ EngineIOConverter::ConvertInput(op_type, *x_tensor,
+ engine->buffer("X").buffer, size, &stream);
// run tensorrt Outp
engine->Execute(1);
// convert ITensor to LoDTensor
- EngineIOConverter::ConvertOutput(op_type, engine->buffer("Out"), out_tensor,
- size, &stream);
+ EngineIOConverter::ConvertOutput(op_type, engine->buffer("Out").buffer,
+ out_tensor, size, &stream);
// get tensorrt output
std::vector<float> out2;
framework::TensorToVector(*out_tensor, ctx, &out2);
From 674bd839cd346ee18d63bd1f6a2757eaf6e750df Mon Sep 17 00:00:00 2001
From: Yan Chunwei <yanchunwei@outlook.com>
Date: Mon, 14 May 2018 21:51:02 +0800
Subject: [PATCH 098/195] OpConverter change BlockDesc to proto::BlockDesc
(#10623)
---
.../inference/tensorrt/convert/CMakeLists.txt | 2 +-
.../inference/tensorrt/convert/activation_op.cc | 9 ++++++---
.../inference/tensorrt/convert/conv2d_op.cc | 2 +-
.../fluid/inference/tensorrt/convert/mul_op.cc | 2 +-
.../inference/tensorrt/convert/op_converter.h | 16 +++++++++-------
.../tensorrt/convert/test_activation_op.cc | 4 ++--
.../tensorrt/convert/test_op_converter.cc | 2 +-
7 files changed, 21 insertions(+), 16 deletions(-)
diff --git a/paddle/fluid/inference/tensorrt/convert/CMakeLists.txt b/paddle/fluid/inference/tensorrt/convert/CMakeLists.txt
index 5178c54c08..286abf736e 100644
--- a/paddle/fluid/inference/tensorrt/convert/CMakeLists.txt
+++ b/paddle/fluid/inference/tensorrt/convert/CMakeLists.txt
@@ -1,4 +1,4 @@
-nv_test(test_op_converter SRCS test_op_converter.cc mul_op.cc conv2d_op.cc DEPS ${FLUID_CORE_MODULES})
+nv_test(test_op_converter SRCS test_op_converter.cc mul_op.cc conv2d_op.cc op_converter.h DEPS ${FLUID_CORE_MODULES})
nv_test(test_trt_activation_op SRCS test_activation_op.cc activation_op.cc
DEPS ${FLUID_CORE_MODULES} activation_op tensorrt_engine)
nv_test(test_io_converter SRCS test_io_converter.cc io_converter.cc DEPS dynload_cuda dynamic_loader lod_tensor)
diff --git a/paddle/fluid/inference/tensorrt/convert/activation_op.cc b/paddle/fluid/inference/tensorrt/convert/activation_op.cc
index 543784289c..6297051e5a 100644
--- a/paddle/fluid/inference/tensorrt/convert/activation_op.cc
+++ b/paddle/fluid/inference/tensorrt/convert/activation_op.cc
@@ -21,15 +21,18 @@ namespace tensorrt {
class ReluOpConverter : public OpConverter {
public:
ReluOpConverter() {}
- void operator()(const framework::OpDesc& op) override {
+ void operator()(const framework::proto::OpDesc& op) override {
+ // Here the two nullptr looks strange, that's because the
+ // framework::OpDesc's constructor is strange.
+ framework::OpDesc op_desc(op, nullptr, nullptr);
LOG(INFO) << "convert a fluid relu op to tensorrt activation layer whose "
"type is Relu";
const nvinfer1::ITensor* input_tensor =
- engine_->GetITensor(op.Input("X")[0]);
+ engine_->GetITensor(op_desc.Input("X")[0]);
nvinfer1::IActivationLayer* layer = TRT_ENGINE_ADD_LAYER(
engine_, Activation, *const_cast<nvinfer1::ITensor*>(input_tensor),
nvinfer1::ActivationType::kRELU);
- engine_->SetITensor(op.Output("Out")[0], layer->getOutput(0));
+ engine_->SetITensor(op_desc.Output("Out")[0], layer->getOutput(0));
}
};
diff --git a/paddle/fluid/inference/tensorrt/convert/conv2d_op.cc b/paddle/fluid/inference/tensorrt/convert/conv2d_op.cc
index 431500b90e..209936c3ba 100644
--- a/paddle/fluid/inference/tensorrt/convert/conv2d_op.cc
+++ b/paddle/fluid/inference/tensorrt/convert/conv2d_op.cc
@@ -21,7 +21,7 @@ namespace tensorrt {
class Conv2dOpConverter : public OpConverter {
public:
Conv2dOpConverter() {}
- void operator()(const framework::OpDesc& op) override {
+ void operator()(const framework::proto::OpDesc& op) override {
LOG(INFO)
<< "convert a fluid conv2d op to tensorrt conv layer without bias";
}
diff --git a/paddle/fluid/inference/tensorrt/convert/mul_op.cc b/paddle/fluid/inference/tensorrt/convert/mul_op.cc
index f9834ab156..3ca58b139b 100644
--- a/paddle/fluid/inference/tensorrt/convert/mul_op.cc
+++ b/paddle/fluid/inference/tensorrt/convert/mul_op.cc
@@ -21,7 +21,7 @@ namespace tensorrt {
class MulOpConverter : public OpConverter {
public:
MulOpConverter() {}
- void operator()(const framework::OpDesc& op) override {
+ void operator()(const framework::proto::OpDesc& op) override {
LOG(INFO) << "convert a fluid mul op to tensorrt fc layer without bias";
}
};
diff --git a/paddle/fluid/inference/tensorrt/convert/op_converter.h b/paddle/fluid/inference/tensorrt/convert/op_converter.h
index 77c788550b..abc9ebf472 100644
--- a/paddle/fluid/inference/tensorrt/convert/op_converter.h
+++ b/paddle/fluid/inference/tensorrt/convert/op_converter.h
@@ -31,10 +31,10 @@ namespace tensorrt {
class OpConverter {
public:
OpConverter() {}
- virtual void operator()(const framework::OpDesc& op) {}
+ virtual void operator()(const framework::proto::OpDesc& op) {}
- void Run(const framework::OpDesc& op, TensorRTEngine* engine) {
- std::string type = op.Type();
+ void Run(const framework::proto::OpDesc& op, TensorRTEngine* engine) {
+ std::string type = op.type();
auto* it = Registry<OpConverter>::Lookup(type);
PADDLE_ENFORCE_NOT_NULL(it, "no OpConverter for optype [%s]", type);
it->SetEngine(engine);
@@ -42,14 +42,16 @@ class OpConverter {
}
// convert fluid op to tensorrt layer
- void ConvertOp(const framework::OpDesc& op, TensorRTEngine* engine) {
+ void ConvertOp(const framework::proto::OpDesc& op, TensorRTEngine* engine) {
OpConverter::Run(op, engine);
}
// convert fluid block to tensorrt network
- void ConvertBlock(const framework::BlockDesc& block, TensorRTEngine* engine) {
- for (auto op : block.AllOps()) {
- OpConverter::Run(*op, engine);
+ void ConvertBlock(const framework::proto::BlockDesc& block,
+ TensorRTEngine* engine) {
+ for (size_t i = 0; i < block.ops_size(); i++) {
+ const auto& op = block.ops(i);
+ OpConverter::Run(op, engine);
}
}
diff --git a/paddle/fluid/inference/tensorrt/convert/test_activation_op.cc b/paddle/fluid/inference/tensorrt/convert/test_activation_op.cc
index 23e3435c21..669fba1eb8 100644
--- a/paddle/fluid/inference/tensorrt/convert/test_activation_op.cc
+++ b/paddle/fluid/inference/tensorrt/convert/test_activation_op.cc
@@ -49,7 +49,7 @@ void Compare(float input, float expect) {
op_desc.SetInput("X", {"X"});
op_desc.SetOutput("Out", {"Out"});
- auto relu_op = framework::OpRegistry::CreateOp(op_desc);
+ auto relu_op = framework::OpRegistry::CreateOp(*op_desc.Proto());
// run fluid op
relu_op->Run(scope, place);
@@ -65,7 +65,7 @@ void Compare(float input, float expect) {
nvinfer1::DimsCHW{1, 1, 1});
OpConverter op_converter;
- op_converter.ConvertOp(op_desc, engine);
+ op_converter.ConvertOp(*op_desc.Proto(), engine);
engine->DeclareOutput("Out");
engine->FreezeNetwork();
diff --git a/paddle/fluid/inference/tensorrt/convert/test_op_converter.cc b/paddle/fluid/inference/tensorrt/convert/test_op_converter.cc
index aa5fb726f1..8d66543eb7 100644
--- a/paddle/fluid/inference/tensorrt/convert/test_op_converter.cc
+++ b/paddle/fluid/inference/tensorrt/convert/test_op_converter.cc
@@ -29,7 +29,7 @@ TEST(OpConverter, ConvertBlock) {
conv2d_op->SetType("conv2d");
OpConverter converter;
- converter.ConvertBlock(*block, nullptr /*TensorRTEngine*/);
+ converter.ConvertBlock(*block->Proto(), nullptr /*TensorRTEngine*/);
}
} // namespace tensorrt
From 8c6dae777684d078fe1064e44091e5d5e9493220 Mon Sep 17 00:00:00 2001
From: chengduoZH <zhaochengduo@163.com>
Date: Mon, 14 May 2018 20:40:17 +0800
Subject: [PATCH 099/195] fix pe bug
---
.../framework/details/multi_devices_graph_builder.cc | 8 ++++++++
.../fluid/framework/details/multi_devices_graph_builder.h | 2 ++
2 files changed, 10 insertions(+)
diff --git a/paddle/fluid/framework/details/multi_devices_graph_builder.cc b/paddle/fluid/framework/details/multi_devices_graph_builder.cc
index 4755559f8d..5473aa5b46 100644
--- a/paddle/fluid/framework/details/multi_devices_graph_builder.cc
+++ b/paddle/fluid/framework/details/multi_devices_graph_builder.cc
@@ -145,12 +145,14 @@ std::unique_ptr<SSAGraph> MultiDevSSAGraphBuilder::Build(
} else if (IsDistTrainOp(*op, send_op)) {
CreateComputationalOps(&result, *op, 1);
} else if (IsScaleLossOp(*op)) {
+ CreateComputationalOps(&result, *op, places_.size());
// user can customize loss@grad if not use_default_grad_scale_
if (use_default_grad_scale_) {
CreateScaleLossGradOp(&result);
}
is_forwarding = false;
} else {
+ if (IsScaleLossGradOp(*op)) continue;
int op_dev_id = GetOpDeviceID(var_name_on_devices, *op);
if (op_dev_id == -1) { // var on all device
CreateComputationalOps(&result, *op, places_.size());
@@ -399,6 +401,12 @@ void MultiDevSSAGraphBuilder::CreateSendOp(SSAGraph *result,
}
bool MultiDevSSAGraphBuilder::IsScaleLossOp(const OpDesc &op) const {
+ // FIXME(yy): Do not hard code like this
+ return op.OutputArgumentNames().size() == 1 &&
+ (op.OutputArgumentNames()[0]) == loss_var_name_;
+}
+
+bool MultiDevSSAGraphBuilder::IsScaleLossGradOp(const OpDesc &op) const {
// FIXME(yy): Do not hard code like this
return op.OutputArgumentNames().size() == 1 &&
op.OutputArgumentNames()[0] == GradVarName(loss_var_name_);
diff --git a/paddle/fluid/framework/details/multi_devices_graph_builder.h b/paddle/fluid/framework/details/multi_devices_graph_builder.h
index 3a3e9e3b85..8a59079ac3 100644
--- a/paddle/fluid/framework/details/multi_devices_graph_builder.h
+++ b/paddle/fluid/framework/details/multi_devices_graph_builder.h
@@ -67,6 +67,8 @@ class MultiDevSSAGraphBuilder : public SSAGraphBuilder {
bool IsScaleLossOp(const OpDesc &op) const;
+ bool IsScaleLossGradOp(const OpDesc &op) const;
+
void CreateSendOp(SSAGraph *result, const OpDesc &op) const;
/**
From ca5ea65ad1b2b90611fffb62690afc5b3cc137a0 Mon Sep 17 00:00:00 2001
From: qingqing01 <dangqingqing@baidu.com>
Date: Tue, 15 May 2018 08:33:39 +0800
Subject: [PATCH 100/195] Fix reshape op. (#10641)
---
paddle/fluid/operators/reshape_op.h | 12 +++++++-----
1 file changed, 7 insertions(+), 5 deletions(-)
diff --git a/paddle/fluid/operators/reshape_op.h b/paddle/fluid/operators/reshape_op.h
index ccd7063fe6..fc693317d1 100644
--- a/paddle/fluid/operators/reshape_op.h
+++ b/paddle/fluid/operators/reshape_op.h
@@ -92,14 +92,16 @@ class ReshapeOp : public framework::OperatorWithKernel {
}
if (unk_dim_idx != -1) {
- output_shape[unk_dim_idx] = -in_size / capacity;
- // in_size < 0 and is un-determinate in compile time, skip the check,
- // for example, in_dims = [-1, 8, 1, 1], shape = [-1, 3, 8],
- // capacity = -24, in_size = -8, output_shape[0] = 0
- // the following check will fail.
if (in_size > 0) {
+ // in_size < 0 and is un-determinate in compile time, skip the check,
+ // for example, in_dims = [-1, 8, 1, 1], shape = [-1, 3, 8],
+ // capacity = -24, in_size = -8, output_shape[0] = 0
+ // the following check will fail.
+ output_shape[unk_dim_idx] = -in_size / capacity;
PADDLE_ENFORCE_EQ(output_shape[unk_dim_idx] * capacity, -in_size,
"Invalid shape is given.");
+ } else {
+ output_shape[unk_dim_idx] = -1;
}
} else {
PADDLE_ENFORCE_EQ(capacity, in_size, "Invalid shape is given.");
From 9fad436bf43ecf3266915f8f40025b7aec0e6443 Mon Sep 17 00:00:00 2001
From: daminglu <daming-lu@users.noreply.github.com>
Date: Mon, 14 May 2018 18:24:50 -0700
Subject: [PATCH 101/195] Simplify fluid api for fit a line (#10301)
---
.../tests/book/high-level-api/CMakeLists.txt | 1 +
.../high-level-api/fit_a_line/CMakeLists.txt | 7 +
.../fit_a_line/test_fit_a_line.py | 137 ++++++++++++++++++
3 files changed, 145 insertions(+)
create mode 100644 python/paddle/fluid/tests/book/high-level-api/fit_a_line/CMakeLists.txt
create mode 100644 python/paddle/fluid/tests/book/high-level-api/fit_a_line/test_fit_a_line.py
diff --git a/python/paddle/fluid/tests/book/high-level-api/CMakeLists.txt b/python/paddle/fluid/tests/book/high-level-api/CMakeLists.txt
index 9ab00325a2..c2a15bdb3b 100644
--- a/python/paddle/fluid/tests/book/high-level-api/CMakeLists.txt
+++ b/python/paddle/fluid/tests/book/high-level-api/CMakeLists.txt
@@ -6,4 +6,5 @@ foreach(src ${TEST_OPS})
py_test(${src} SRCS ${src}.py)
endforeach()
+add_subdirectory(fit_a_line)
add_subdirectory(recognize_digits)
diff --git a/python/paddle/fluid/tests/book/high-level-api/fit_a_line/CMakeLists.txt b/python/paddle/fluid/tests/book/high-level-api/fit_a_line/CMakeLists.txt
new file mode 100644
index 0000000000..673c965b66
--- /dev/null
+++ b/python/paddle/fluid/tests/book/high-level-api/fit_a_line/CMakeLists.txt
@@ -0,0 +1,7 @@
+file(GLOB TEST_OPS RELATIVE "${CMAKE_CURRENT_SOURCE_DIR}" "test_*.py")
+string(REPLACE ".py" "" TEST_OPS "${TEST_OPS}")
+
+# default test
+foreach(src ${TEST_OPS})
+ py_test(${src} SRCS ${src}.py)
+endforeach()
diff --git a/python/paddle/fluid/tests/book/high-level-api/fit_a_line/test_fit_a_line.py b/python/paddle/fluid/tests/book/high-level-api/fit_a_line/test_fit_a_line.py
new file mode 100644
index 0000000000..8c9bbb52d7
--- /dev/null
+++ b/python/paddle/fluid/tests/book/high-level-api/fit_a_line/test_fit_a_line.py
@@ -0,0 +1,137 @@
+# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import paddle
+import paddle.fluid as fluid
+import contextlib
+import numpy
+import unittest
+
+# train reader
+BATCH_SIZE = 20
+
+train_reader = paddle.batch(
+ paddle.reader.shuffle(
+ paddle.dataset.uci_housing.train(), buf_size=500),
+ batch_size=BATCH_SIZE)
+
+test_reader = paddle.batch(
+ paddle.reader.shuffle(
+ paddle.dataset.uci_housing.test(), buf_size=500),
+ batch_size=BATCH_SIZE)
+
+
+def inference_program():
+ x = fluid.layers.data(name='x', shape=[13], dtype='float32')
+ y_predict = fluid.layers.fc(input=x, size=1, act=None)
+ return y_predict
+
+
+def linear():
+ y = fluid.layers.data(name='y', shape=[1], dtype='float32')
+ y_predict = inference_program()
+
+ loss = fluid.layers.square_error_cost(input=y_predict, label=y)
+ avg_loss = fluid.layers.mean(loss)
+
+ return avg_loss
+
+
+def train(use_cuda, save_dirname):
+ place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
+
+ trainer = fluid.Trainer(
+ train_func=linear,
+ infer_func=inference_program,
+ place=place,
+ optimizer=fluid.optimizer.SGD(learning_rate=0.001))
+
+ def event_handler(event):
+ if isinstance(event, fluid.EndEpochEvent):
+ test_metrics = trainer.test(
+ reader=test_reader, feed_order=['x', 'y'])
+ print test_metrics
+ '''
+
+ ...
+ ['25.768919467926025']
+ ['15.343549569447836']
+ ...
+
+ '''
+ if float(test_metrics[0]) < 20.0:
+ if save_dirname is not None:
+ # NOT clear yet
+ # fluid.io.save_inference_model(save_dirname, ['x'], [y_predict])
+ # trainer.save_params(save_dirname)
+ # https://github.com/PaddlePaddle/Paddle/pull/10445
+ trainer.save_inference_model(save_dirname)
+ return
+
+ trainer.train(
+ reader=train_reader,
+ num_epochs=100,
+ event_handler=event_handler,
+ feed_order=['x', 'y'])
+
+
+# infer
+def infer(use_cuda, save_dirname=None):
+ if save_dirname is None:
+ return
+
+ place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
+ inferencer = fluid.Inferencer(param_path=save_dirname, place=place)
+
+ batch_size = 10
+ tensor_x = numpy.random.uniform(0, 10, [batch_size, 13]).astype("float32")
+
+ results = inferencer.infer({'x': tensor_x})
+ print("infer results: ", results[0])
+
+
+def main(use_cuda):
+ if use_cuda and not fluid.core.is_compiled_with_cuda():
+ return
+
+ # Directory for saving the trained model
+ save_dirname = "fit_a_line.inference.model"
+
+ train(use_cuda, save_dirname)
+ infer(use_cuda, save_dirname)
+
+
+class TestFitALine(unittest.TestCase):
+ def test_cpu(self):
+ with self.program_scope_guard():
+ with fluid.unique_name.guard():
+ main(use_cuda=False)
+
+ def test_cuda(self):
+ with self.program_scope_guard():
+ with fluid.unique_name.guard():
+ main(use_cuda=True)
+
+ @contextlib.contextmanager
+ def program_scope_guard(self):
+ prog = fluid.Program()
+ startup_prog = fluid.Program()
+ scope = fluid.core.Scope()
+ with fluid.scope_guard(scope):
+ with fluid.program_guard(prog, startup_prog):
+ yield
+
+
+if __name__ == '__main__':
+ unittest.main()
From af2cd942bb7baa487d0289d10fdfce7e35a6ba55 Mon Sep 17 00:00:00 2001
From: qiaolongfei <qiaolongfei@baidu.com>
Date: Tue, 15 May 2018 09:50:48 +0800
Subject: [PATCH 102/195] copy boost
---
cmake/inference_lib.cmake | 6 ++++++
1 file changed, 6 insertions(+)
diff --git a/cmake/inference_lib.cmake b/cmake/inference_lib.cmake
index cc75801982..78857cf2a0 100644
--- a/cmake/inference_lib.cmake
+++ b/cmake/inference_lib.cmake
@@ -70,6 +70,12 @@ copy(glog_lib
DSTS ${dst_dir} ${dst_dir}/lib
)
+set(dst_dir "${CMAKE_INSTALL_PREFIX}/third_party/install/boost")
+copy(boost_lib
+ SRCS ${BOOST_INCLUDE_DIR}
+ DSTS ${dst_dir}
+)
+
if(NOT PROTOBUF_FOUND)
set(dst_dir "${CMAKE_INSTALL_PREFIX}/third_party/install/protobuf")
copy(protobuf_lib
From b7026f79a978218c48302641d10c9d6a907592d7 Mon Sep 17 00:00:00 2001
From: Yiqun Liu <liuyiqun01@baidu.com>
Date: Tue, 15 May 2018 10:03:28 +0800
Subject: [PATCH 103/195] Fix a bug related to dispensable inputs and refine
the inference unittest (#10527)
* Fix a bug related to dispensable inputs and refine the inference unittest.
* Fix the use of dispensable inputs in reshape_op.
* Polish the enforce statements.
* Fix an English writing typo.
---
paddle/fluid/framework/operator.h | 4 ++
.../test_inference_image_classification.cc | 25 ++++----
paddle/fluid/inference/tests/test_helper.h | 61 ++++++++++++++-----
paddle/fluid/operators/math/sequence2batch.h | 21 ++++---
paddle/fluid/operators/reshape_op.h | 5 +-
5 files changed, 79 insertions(+), 37 deletions(-)
diff --git a/paddle/fluid/framework/operator.h b/paddle/fluid/framework/operator.h
index d373c48b1a..a4eb6f706e 100644
--- a/paddle/fluid/framework/operator.h
+++ b/paddle/fluid/framework/operator.h
@@ -192,6 +192,10 @@ class ExecutionContext {
return op_.Attr<T>(name);
}
+ bool HasInput(const std::string& name) const { return op_.HasInputs(name); }
+
+ bool HasOutput(const std::string& name) const { return op_.HasOutputs(name); }
+
size_t InputSize(const std::string& name) const {
return op_.Inputs(name).size();
}
diff --git a/paddle/fluid/inference/tests/book/test_inference_image_classification.cc b/paddle/fluid/inference/tests/book/test_inference_image_classification.cc
index c4fd1e298b..60c761c528 100644
--- a/paddle/fluid/inference/tests/book/test_inference_image_classification.cc
+++ b/paddle/fluid/inference/tests/book/test_inference_image_classification.cc
@@ -16,7 +16,6 @@ limitations under the License. */
#include "gtest/gtest.h"
#include "paddle/fluid/inference/tests/test_helper.h"
-DEFINE_string(data_set, "cifar10", "Data set to test");
DEFINE_string(dirname, "", "Directory of the inference model.");
DEFINE_string(fp16_dirname, "", "Directory of the float16 inference model.");
DEFINE_int32(batch_size, 1, "Batch size of input data");
@@ -35,19 +34,19 @@ TEST(inference, image_classification) {
// 0. Call `paddle::framework::InitDevices()` initialize all the devices
// In unittests, this is done in paddle/testing/paddle_gtest_main.cc
+ const bool is_combined = false;
+ std::vector<std::vector<int64_t>> feed_target_shapes =
+ GetFeedTargetShapes(dirname, is_combined);
+
paddle::framework::LoDTensor input;
// Use normilized image pixels as input data,
// which should be in the range [0.0, 1.0].
- if (FLAGS_data_set == "cifar10") {
- SetupTensor<float>(&input, {FLAGS_batch_size, 3, 32, 32},
- static_cast<float>(0), static_cast<float>(1));
- } else if (FLAGS_data_set == "imagenet") {
- SetupTensor<float>(&input, {FLAGS_batch_size, 3, 224, 224},
- static_cast<float>(0), static_cast<float>(1));
- } else {
- LOG(FATAL) << "Only cifar10 or imagenet is supported.";
- }
-
+ feed_target_shapes[0][0] = FLAGS_batch_size;
+ paddle::framework::DDim input_dims =
+ paddle::framework::make_ddim(feed_target_shapes[0]);
+ LOG(INFO) << input_dims;
+ SetupTensor<float>(&input, input_dims, static_cast<float>(0),
+ static_cast<float>(1));
std::vector<paddle::framework::LoDTensor*> cpu_feeds;
cpu_feeds.push_back(&input);
@@ -60,7 +59,7 @@ TEST(inference, image_classification) {
LOG(INFO) << "--- CPU Runs: ---";
LOG(INFO) << "Batch size is " << FLAGS_batch_size;
TestInference<paddle::platform::CPUPlace, false, true>(
- dirname, cpu_feeds, cpu_fetchs1, FLAGS_repeat);
+ dirname, cpu_feeds, cpu_fetchs1, FLAGS_repeat, is_combined);
LOG(INFO) << output1.dims();
}
@@ -73,7 +72,7 @@ TEST(inference, image_classification) {
LOG(INFO) << "--- GPU Runs: ---";
LOG(INFO) << "Batch size is " << FLAGS_batch_size;
TestInference<paddle::platform::CUDAPlace, false, true>(
- dirname, cpu_feeds, cpu_fetchs2, FLAGS_repeat);
+ dirname, cpu_feeds, cpu_fetchs2, FLAGS_repeat, is_combined);
LOG(INFO) << output2.dims();
if (!FLAGS_skip_cpu) {
diff --git a/paddle/fluid/inference/tests/test_helper.h b/paddle/fluid/inference/tests/test_helper.h
index af2a7a5620..b02e5c99f0 100644
--- a/paddle/fluid/inference/tests/test_helper.h
+++ b/paddle/fluid/inference/tests/test_helper.h
@@ -89,6 +89,50 @@ void CheckError(const paddle::framework::LoDTensor& output1,
EXPECT_EQ(count, 0U) << "There are " << count << " different elements.";
}
+std::unique_ptr<paddle::framework::ProgramDesc> InitProgram(
+ paddle::framework::Executor* executor, paddle::framework::Scope* scope,
+ const std::string& dirname, const bool is_combined = false) {
+ std::unique_ptr<paddle::framework::ProgramDesc> inference_program;
+ if (is_combined) {
+ // All parameters are saved in a single file.
+ // Hard-coding the file names of program and parameters in unittest.
+ // The file names should be consistent with that used in Python API
+ // `fluid.io.save_inference_model`.
+ std::string prog_filename = "__model_combined__";
+ std::string param_filename = "__params_combined__";
+ inference_program =
+ paddle::inference::Load(executor, scope, dirname + "/" + prog_filename,
+ dirname + "/" + param_filename);
+ } else {
+ // Parameters are saved in separate files sited in the specified
+ // `dirname`.
+ inference_program = paddle::inference::Load(executor, scope, dirname);
+ }
+ return inference_program;
+}
+
+std::vector<std::vector<int64_t>> GetFeedTargetShapes(
+ const std::string& dirname, const bool is_combined = false) {
+ auto place = paddle::platform::CPUPlace();
+ auto executor = paddle::framework::Executor(place);
+ auto* scope = new paddle::framework::Scope();
+
+ auto inference_program = InitProgram(&executor, scope, dirname, is_combined);
+ auto& global_block = inference_program->Block(0);
+
+ const std::vector<std::string>& feed_target_names =
+ inference_program->GetFeedTargetNames();
+ std::vector<std::vector<int64_t>> feed_target_shapes;
+ for (size_t i = 0; i < feed_target_names.size(); ++i) {
+ auto* var = global_block.FindVar(feed_target_names[i]);
+ std::vector<int64_t> var_shape = var->GetShape();
+ feed_target_shapes.push_back(var_shape);
+ }
+
+ delete scope;
+ return feed_target_shapes;
+}
+
template <typename Place, bool CreateVars = true, bool PrepareContext = false>
void TestInference(const std::string& dirname,
const std::vector<paddle::framework::LoDTensor*>& cpu_feeds,
@@ -124,22 +168,7 @@ void TestInference(const std::string& dirname,
paddle::platform::RecordEvent record_event(
"init_program",
paddle::platform::DeviceContextPool::Instance().Get(place));
-
- if (is_combined) {
- // All parameters are saved in a single file.
- // Hard-coding the file names of program and parameters in unittest.
- // The file names should be consistent with that used in Python API
- // `fluid.io.save_inference_model`.
- std::string prog_filename = "__model_combined__";
- std::string param_filename = "__params_combined__";
- inference_program = paddle::inference::Load(
- &executor, scope, dirname + "/" + prog_filename,
- dirname + "/" + param_filename);
- } else {
- // Parameters are saved in separate files sited in the specified
- // `dirname`.
- inference_program = paddle::inference::Load(&executor, scope, dirname);
- }
+ inference_program = InitProgram(&executor, scope, dirname, is_combined);
}
// Disable the profiler and print the timing information
paddle::platform::DisableProfiler(paddle::platform::EventSortingKey::kDefault,
diff --git a/paddle/fluid/operators/math/sequence2batch.h b/paddle/fluid/operators/math/sequence2batch.h
index 0abda999a5..62e6307ae9 100644
--- a/paddle/fluid/operators/math/sequence2batch.h
+++ b/paddle/fluid/operators/math/sequence2batch.h
@@ -64,18 +64,22 @@ class LoDTensor2BatchFunctor {
bool is_reverse = false) const {
if (!is_cal_batch_lod) {
auto lods = batch->lod();
- PADDLE_ENFORCE_GT(lods.size(), 2UL);
- PADDLE_ENFORCE_EQ(lods[1].size(),
- static_cast<size_t>(lod_tensor.dims()[0]));
+ PADDLE_ENFORCE_GT(lods.size(), 2UL,
+ "The LoD of LoDTensor should inlcude at least 2-level "
+ "sequence information.");
+ PADDLE_ENFORCE_EQ(
+ lods[1].size(), static_cast<size_t>(lod_tensor.dims()[0]),
+ "The LoD information should be consistent with the dims.");
CopyMatrixRowsFunctor<DeviceContext, T> to_batch;
to_batch(context, lod_tensor, lods[1], batch, true);
return;
}
auto lods = lod_tensor.lod();
- auto lod = lods[0];
PADDLE_ENFORCE_EQ(lods.size(), 1UL, "Only support one level sequence now.");
+ auto lod = lods[0];
+
std::vector<SeqInfo> seq_info;
for (size_t seq_id = 0; seq_id < lod.size() - 1; ++seq_id) {
int length = lod[seq_id + 1] - lod[seq_id];
@@ -157,9 +161,12 @@ class Batch2LoDTensorFunctor {
const framework::LoDTensor& batch,
framework::LoDTensor* lod_tensor) const {
auto in_lod = batch.lod();
- PADDLE_ENFORCE_GT(in_lod.size(), 2UL);
- PADDLE_ENFORCE_EQ(in_lod[1].size(),
- static_cast<size_t>(lod_tensor->dims()[0]));
+ PADDLE_ENFORCE_GT(in_lod.size(), 2UL,
+ "The LoD of LoDTensor should inlcude at least 2-level "
+ "sequence information.");
+ PADDLE_ENFORCE_EQ(
+ in_lod[1].size(), static_cast<size_t>(lod_tensor->dims()[0]),
+ "The LoD information should be consistent with the dims.");
CopyMatrixRowsFunctor<DeviceContext, T> to_seq;
to_seq(context, batch, in_lod[1], lod_tensor, false);
}
diff --git a/paddle/fluid/operators/reshape_op.h b/paddle/fluid/operators/reshape_op.h
index fc693317d1..3dd8c7c11e 100644
--- a/paddle/fluid/operators/reshape_op.h
+++ b/paddle/fluid/operators/reshape_op.h
@@ -124,7 +124,10 @@ class ReshapeKernel : public framework::OpKernel<T> {
void Compute(const framework::ExecutionContext &ctx) const {
auto *out = ctx.Output<framework::LoDTensor>("Out");
auto *in = ctx.Input<framework::LoDTensor>("X");
- auto *shape_tensor = ctx.Input<framework::LoDTensor>("Shape");
+
+ auto *shape_tensor = ctx.HasInput("Shape")
+ ? ctx.Input<framework::LoDTensor>("Shape")
+ : nullptr;
framework::DDim out_dims = out->dims();
From a3ca4c99ebb6c6bbe34606eb19cf6574fe9b3525 Mon Sep 17 00:00:00 2001
From: chengduoZH <zhaochengduo@163.com>
Date: Tue, 15 May 2018 11:22:25 +0800
Subject: [PATCH 104/195] fix loss.gradVar
---
.../framework/details/multi_devices_graph_builder.cc | 8 --------
.../fluid/framework/details/multi_devices_graph_builder.h | 2 --
python/paddle/fluid/backward.py | 2 ++
3 files changed, 2 insertions(+), 10 deletions(-)
diff --git a/paddle/fluid/framework/details/multi_devices_graph_builder.cc b/paddle/fluid/framework/details/multi_devices_graph_builder.cc
index 5473aa5b46..4755559f8d 100644
--- a/paddle/fluid/framework/details/multi_devices_graph_builder.cc
+++ b/paddle/fluid/framework/details/multi_devices_graph_builder.cc
@@ -145,14 +145,12 @@ std::unique_ptr<SSAGraph> MultiDevSSAGraphBuilder::Build(
} else if (IsDistTrainOp(*op, send_op)) {
CreateComputationalOps(&result, *op, 1);
} else if (IsScaleLossOp(*op)) {
- CreateComputationalOps(&result, *op, places_.size());
// user can customize loss@grad if not use_default_grad_scale_
if (use_default_grad_scale_) {
CreateScaleLossGradOp(&result);
}
is_forwarding = false;
} else {
- if (IsScaleLossGradOp(*op)) continue;
int op_dev_id = GetOpDeviceID(var_name_on_devices, *op);
if (op_dev_id == -1) { // var on all device
CreateComputationalOps(&result, *op, places_.size());
@@ -401,12 +399,6 @@ void MultiDevSSAGraphBuilder::CreateSendOp(SSAGraph *result,
}
bool MultiDevSSAGraphBuilder::IsScaleLossOp(const OpDesc &op) const {
- // FIXME(yy): Do not hard code like this
- return op.OutputArgumentNames().size() == 1 &&
- (op.OutputArgumentNames()[0]) == loss_var_name_;
-}
-
-bool MultiDevSSAGraphBuilder::IsScaleLossGradOp(const OpDesc &op) const {
// FIXME(yy): Do not hard code like this
return op.OutputArgumentNames().size() == 1 &&
op.OutputArgumentNames()[0] == GradVarName(loss_var_name_);
diff --git a/paddle/fluid/framework/details/multi_devices_graph_builder.h b/paddle/fluid/framework/details/multi_devices_graph_builder.h
index 8a59079ac3..3a3e9e3b85 100644
--- a/paddle/fluid/framework/details/multi_devices_graph_builder.h
+++ b/paddle/fluid/framework/details/multi_devices_graph_builder.h
@@ -67,8 +67,6 @@ class MultiDevSSAGraphBuilder : public SSAGraphBuilder {
bool IsScaleLossOp(const OpDesc &op) const;
- bool IsScaleLossGradOp(const OpDesc &op) const;
-
void CreateSendOp(SSAGraph *result, const OpDesc &op) const;
/**
diff --git a/python/paddle/fluid/backward.py b/python/paddle/fluid/backward.py
index 7af6ed1463..32b1b65bd9 100644
--- a/python/paddle/fluid/backward.py
+++ b/python/paddle/fluid/backward.py
@@ -480,6 +480,8 @@ def append_backward(loss, parameter_list=None, no_grad_set=None,
program.current_block_idx = current_block_idx
program.sync_with_cpp()
+ # FIXME(zcd): prevent loss.grad optimized by mem_opt.
+ loss.block.var(_append_grad_suffix_(loss.name)).persistable = True
if parameter_list is not None:
parameters = parameter_list
From b0eca1040f9d043d54828320fc04bcd5a0737077 Mon Sep 17 00:00:00 2001
From: Wu Yi <typhoonzero1986@gmail.com>
Date: Tue, 15 May 2018 14:01:32 +0800
Subject: [PATCH 105/195] remove unused vars (#10618)
---
python/paddle/fluid/tests/book/notest_understand_sentiment.py | 2 +-
python/paddle/fluid/tests/book/test_fit_a_line.py | 2 +-
python/paddle/fluid/tests/book/test_image_classification.py | 2 +-
python/paddle/fluid/tests/book/test_label_semantic_roles.py | 2 +-
python/paddle/fluid/tests/book/test_machine_translation.py | 2 +-
python/paddle/fluid/tests/book/test_recognize_digits.py | 2 +-
python/paddle/fluid/tests/book/test_recommender_system.py | 2 +-
python/paddle/fluid/tests/book/test_word2vec.py | 2 +-
8 files changed, 8 insertions(+), 8 deletions(-)
diff --git a/python/paddle/fluid/tests/book/notest_understand_sentiment.py b/python/paddle/fluid/tests/book/notest_understand_sentiment.py
index 241778e303..792ed7368d 100644
--- a/python/paddle/fluid/tests/book/notest_understand_sentiment.py
+++ b/python/paddle/fluid/tests/book/notest_understand_sentiment.py
@@ -170,7 +170,7 @@ def train(word_dict,
assert save_dirname is None
adagrad = fluid.optimizer.Adagrad(learning_rate=0.002)
- optimize_ops, params_grads = adagrad.minimize(cost)
+ adagrad.minimize(cost)
train_data = paddle.batch(
paddle.reader.shuffle(
diff --git a/python/paddle/fluid/tests/book/test_fit_a_line.py b/python/paddle/fluid/tests/book/test_fit_a_line.py
index ecb34699af..b1a6b524d3 100644
--- a/python/paddle/fluid/tests/book/test_fit_a_line.py
+++ b/python/paddle/fluid/tests/book/test_fit_a_line.py
@@ -33,7 +33,7 @@ def train(use_cuda, save_dirname, is_local):
avg_cost = fluid.layers.mean(cost)
sgd_optimizer = fluid.optimizer.SGD(learning_rate=0.001)
- optimize_ops, params_grads = sgd_optimizer.minimize(avg_cost)
+ sgd_optimizer.minimize(avg_cost)
BATCH_SIZE = 20
diff --git a/python/paddle/fluid/tests/book/test_image_classification.py b/python/paddle/fluid/tests/book/test_image_classification.py
index dbcdb5766e..0f3a4c9242 100644
--- a/python/paddle/fluid/tests/book/test_image_classification.py
+++ b/python/paddle/fluid/tests/book/test_image_classification.py
@@ -125,7 +125,7 @@ def train(net_type, use_cuda, save_dirname, is_local):
test_program = fluid.default_main_program().clone(for_test=True)
optimizer = fluid.optimizer.Adam(learning_rate=0.001)
- optimize_ops, params_grads = optimizer.minimize(avg_cost)
+ optimizer.minimize(avg_cost)
BATCH_SIZE = 128
PASS_NUM = 1
diff --git a/python/paddle/fluid/tests/book/test_label_semantic_roles.py b/python/paddle/fluid/tests/book/test_label_semantic_roles.py
index 0faba33032..09793760e5 100644
--- a/python/paddle/fluid/tests/book/test_label_semantic_roles.py
+++ b/python/paddle/fluid/tests/book/test_label_semantic_roles.py
@@ -175,7 +175,7 @@ def train(use_cuda, save_dirname=None, is_local=True):
decay_steps=100000,
decay_rate=0.5,
staircase=True))
- optimize_ops, params_grads = sgd_optimizer.minimize(avg_cost)
+ sgd_optimizer.minimize(avg_cost)
# TODO(qiao)
# add dependency track and move this config before optimizer
diff --git a/python/paddle/fluid/tests/book/test_machine_translation.py b/python/paddle/fluid/tests/book/test_machine_translation.py
index 46c6b9c29a..e8a75f473f 100644
--- a/python/paddle/fluid/tests/book/test_machine_translation.py
+++ b/python/paddle/fluid/tests/book/test_machine_translation.py
@@ -185,7 +185,7 @@ def train_main(use_cuda, is_sparse, is_local=True):
learning_rate=1e-4,
regularization=fluid.regularizer.L2DecayRegularizer(
regularization_coeff=0.1))
- optimize_ops, params_grads = optimizer.minimize(avg_cost)
+ optimizer.minimize(avg_cost)
train_data = paddle.batch(
paddle.reader.shuffle(
diff --git a/python/paddle/fluid/tests/book/test_recognize_digits.py b/python/paddle/fluid/tests/book/test_recognize_digits.py
index c115aa4d7d..578b1162fb 100644
--- a/python/paddle/fluid/tests/book/test_recognize_digits.py
+++ b/python/paddle/fluid/tests/book/test_recognize_digits.py
@@ -95,7 +95,7 @@ def train(nn_type,
test_program = fluid.default_main_program().clone(for_test=True)
optimizer = fluid.optimizer.Adam(learning_rate=0.001)
- optimize_ops, params_grads = optimizer.minimize(avg_loss)
+ optimizer.minimize(avg_loss)
place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
diff --git a/python/paddle/fluid/tests/book/test_recommender_system.py b/python/paddle/fluid/tests/book/test_recommender_system.py
index d022dedbff..7be924f762 100644
--- a/python/paddle/fluid/tests/book/test_recommender_system.py
+++ b/python/paddle/fluid/tests/book/test_recommender_system.py
@@ -160,7 +160,7 @@ def train(use_cuda, save_dirname, is_local=True):
test_program = fluid.default_main_program().clone(for_test=True)
sgd_optimizer = SGDOptimizer(learning_rate=0.2)
- optimize_ops, params_grads = sgd_optimizer.minimize(avg_cost)
+ sgd_optimizer.minimize(avg_cost)
place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
diff --git a/python/paddle/fluid/tests/book/test_word2vec.py b/python/paddle/fluid/tests/book/test_word2vec.py
index 6dec0f6857..30e1a5040c 100644
--- a/python/paddle/fluid/tests/book/test_word2vec.py
+++ b/python/paddle/fluid/tests/book/test_word2vec.py
@@ -101,7 +101,7 @@ def train(use_cuda, is_sparse, is_parallel, save_dirname, is_local=True):
avg_cost = fluid.layers.mean(pd())
sgd_optimizer = fluid.optimizer.SGD(learning_rate=0.001)
- optimize_ops, params_grads = sgd_optimizer.minimize(avg_cost)
+ sgd_optimizer.minimize(avg_cost)
train_reader = paddle.batch(
paddle.dataset.imikolov.train(word_dict, N), BATCH_SIZE)
From a94aa4d1c81eb14eb544cb647c61e80ca146b398 Mon Sep 17 00:00:00 2001
From: Yancey <yanxu05@baidu.com>
Date: Tue, 15 May 2018 14:59:16 +0800
Subject: [PATCH 106/195] add manylinux docker image usage (#10585)
* add manylinux docker image usage
* update by comment
* update by comment
---
.../build_from_source_cn.rst | 5 +--
.../build_from_source_en.rst | 2 ++
tools/manylinux1/README.md | 35 +++++++++++++++++++
3 files changed, 40 insertions(+), 2 deletions(-)
diff --git a/doc/v2/build_and_install/build_from_source_cn.rst b/doc/v2/build_and_install/build_from_source_cn.rst
index 115b92a338..f846928954 100644
--- a/doc/v2/build_and_install/build_from_source_cn.rst
+++ b/doc/v2/build_and_install/build_from_source_cn.rst
@@ -19,8 +19,9 @@
----------------
PaddlePaddle需要使用Docker环境完成编译，这样可以免去单独安装编译依赖的步骤，可选的不同编译环境Docker镜像
-可以在 `这里 <https://hub.docker.com/r/paddlepaddle/paddle_manylinux_devel/tags/>`_ 找到。或者
-参考下述可选步骤，从源码中构建用于编译PaddlePaddle的Docker镜像。
+可以在 `这里 <https://hub.docker.com/r/paddlepaddle/paddle_manylinux_devel/tags/>`_ 找到，您也可以
+在 `这里 <https://github.com/PaddlePaddle/Paddle/tree/develop/tools/manylinux1/>`_ 找到 paddle_manylinux_devel
+镜像的编译以及使用方法。或者参考下述可选步骤，从源码中构建用于编译PaddlePaddle的Docker镜像。
如果您选择不使用Docker镜像，则需要在本机安装下面章节列出的 `编译依赖`_ 之后才能开始编译的步骤。
diff --git a/doc/v2/build_and_install/build_from_source_en.rst b/doc/v2/build_and_install/build_from_source_en.rst
index 8fef9e7347..d1b5b88dff 100644
--- a/doc/v2/build_and_install/build_from_source_en.rst
+++ b/doc/v2/build_and_install/build_from_source_en.rst
@@ -22,6 +22,8 @@ How To Build
You need to use Docker to build PaddlePaddle
to avoid installing dependencies by yourself. We have several pre-built
Docker images `here <https://hub.docker.com/r/paddlepaddle/paddle_manylinux_devel/tags/>`_ ,
+you can also find how to build and use paddle_manylinux_devel Docker image from
+`here <https://github.com/PaddlePaddle/Paddle/tree/develop/tools/manylinux1/>`_
Or you can build your own image from source as the optional step below:
.. code-block:: bash
diff --git a/tools/manylinux1/README.md b/tools/manylinux1/README.md
index 898e00bd37..0e59050401 100644
--- a/tools/manylinux1/README.md
+++ b/tools/manylinux1/README.md
@@ -28,3 +28,38 @@ git clone https://github.com/paddlepaddle/paddle
cd paddle/tools/manylinux1
REPO=[yourrepo] ./build_all.sh
```
+
+## Build PaddlePaddle for the different Python ABIs
+
+Choose one of the following Python ABI and set the correct environment variables.
+
+- cp27-cp27m
+
+ ```bash
+ export LD_LIBRARY_PATH=/opt/_internal/cpython-2.7.11-ucs2/lib:${LD_LIBRARY_PATH#/opt/_internal/cpython-2.7.11-ucs4/lib:}
+ export PATH=/opt/python/cp27-cp27m/bin/:${PATH}
+ export PYTHON_FLAGS="-DPYTHON_EXECUTABLE:FILEPATH=/opt/python/cp27-cp27m/bin/python
+ -DPYTHON_INCLUDE_DIR:PATH=/opt/python/cp27-cp27m/include/python2.7
+ -DPYTHON_LIBRARIES:FILEPATH=/opt/_internal/cpython-2.7.11-ucs2/lib/libpython2.7.so"
+ ```
+
+- cp27-cp27mu
+
+ ```bash
+ export LD_LIBRARY_PATH=/opt/_internal/cpython-2.7.11-ucs4/lib:${LD_LIBRARY_PATH#/opt/_internal/cpython-2.7.11-ucs2/lib:}
+ export PATH=/opt/python/cp27-cp27mu/bin/:${PATH}
+ export PYTHON_FLAGS="-DPYTHON_EXECUTABLE:FILEPATH=/opt/python/cp27-cp27mu/bin/python
+ -DPYTHON_INCLUDE_DIR:PATH=/opt/python/cp27-cp27mu/include/python2.7
+ -DPYTHON_LIBRARIES:FILEPATH=/opt/_internal/cpython-2.7.11-ucs4/lib/libpython2.7.so"
+ ```
+
+And then add the `PYTHON_FLAGS` as your cmake flags:
+
+```bash
+cmake ..
+ ${PYTHON_FLAGS} \
+ -DWITH_GPU=OFF \
+ ...
+```
+
+You can find more details about cmake flags at [here](http://www.paddlepaddle.org/docs/develop/documentation/fluid/en/build_and_install/build_from_source_en.html#appendix-build-options)
From 0acc93cab9c54db25fc8f3e1ad006c312a855a5e Mon Sep 17 00:00:00 2001
From: Yancey <yanxu05@baidu.com>
Date: Tue, 15 May 2018 14:59:45 +0800
Subject: [PATCH 107/195] add dist transpiler unit test (#10485)
* add dist transpiler unit test
* update by comment
* update by comment
* fix ci
* fix ci
---
.../tests/unittests/test_dist_transpiler.py | 113 ++++++++++++++++++
python/paddle/fluid/transpiler/__init__.py | 1 +
.../fluid/transpiler/distribute_transpiler.py | 4 +-
3 files changed, 116 insertions(+), 2 deletions(-)
create mode 100644 python/paddle/fluid/tests/unittests/test_dist_transpiler.py
diff --git a/python/paddle/fluid/tests/unittests/test_dist_transpiler.py b/python/paddle/fluid/tests/unittests/test_dist_transpiler.py
new file mode 100644
index 0000000000..10f8c4f3f0
--- /dev/null
+++ b/python/paddle/fluid/tests/unittests/test_dist_transpiler.py
@@ -0,0 +1,113 @@
+# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import unittest
+
+import paddle.fluid as fluid
+import paddle.fluid.core as core
+import paddle.fluid.layers as layers
+from paddle.fluid.transpiler.distribute_transpiler import delete_ops
+import numpy
+
+
+class TestDistTranspiler(unittest.TestCase):
+ def setUp(self):
+ self.trainer_id = 0
+ self.trainers = 2
+ self.pservers = 2
+ self.pserver_eps = "127.0.0.1:6174,127.0.0.1:6175"
+ self.current_pserver_ep = "127.0.0.1:6174"
+
+ def net_conf(self):
+ x = fluid.layers.data(name='x', shape=[1000], dtype='float32')
+
+ y_predict = fluid.layers.fc(input=x,
+ size=1000,
+ act=None,
+ param_attr=fluid.ParamAttr(name='fc_w'))
+
+ y = fluid.layers.data(name='y', shape=[1], dtype='float32')
+
+ cost = fluid.layers.square_error_cost(input=y_predict, label=y)
+ avg_cost = fluid.layers.mean(cost)
+ sgd_optimizer = fluid.optimizer.SGD(learning_rate=0.1)
+
+ optimize_ops, params_grads = sgd_optimizer.minimize(avg_cost)
+ return optimize_ops, params_grads
+
+ def test_transpiler(self):
+ trainer = self.get_trainer()
+ pserver, startup = self.get_pserver(self.current_pserver_ep)
+
+ self.assertEqual([op.type for op in trainer.global_block().ops],
+ self.get_expect_trainer_ops())
+
+ self.assertEqual(len(pserver.blocks), 3)
+ # block0: listen_and_serv
+ self.assertEqual([op.type for op in pserver.blocks[0].ops],
+ ["listen_and_serv"])
+ # block2: optimize pass
+ self.assertEqual([op.type for op in pserver.blocks[1].ops],
+ ["sum", "scale", "sgd"])
+
+ # confirm startup program
+
+ self.assertEqual([op.type for op in startup.global_block().ops], [
+ "fill_constant", "fill_constant", "uniform_random", "uniform_random"
+ ])
+
+ # the variable #fc_w will be split into two blocks
+ fc_w_var = startup.global_block().var("fc_w.block1")
+ self.assertEqual(fc_w_var.shape, (500, 1000))
+
+ def get_main_program(self):
+ main = fluid.Program()
+
+ with fluid.program_guard(main):
+ self.net_conf()
+
+ return main
+
+ def get_expect_trainer_ops(self):
+ trainer = fluid.Program()
+
+ with fluid.program_guard(trainer):
+ optimize_ops, params_grads = self.net_conf()
+
+ delete_ops(trainer.global_block(), optimize_ops)
+ return [op.type for op in trainer.global_block().ops
+ ] + ["split_byref", "send", "concat"]
+
+ def get_trainer(self):
+ return self._transpiler_instance().get_trainer_program()
+
+ def get_pserver(self, ep):
+ t = self._transpiler_instance()
+ pserver = t.get_pserver_program(ep)
+ startup = t.get_startup_program(ep, pserver)
+ return pserver, startup
+
+ def _transpiler_instance(self):
+ main = self.get_main_program()
+ t = fluid.DistributeTranspiler()
+ t.transpile(
+ self.trainer_id,
+ program=main,
+ pservers=self.pserver_eps,
+ trainers=self.trainers)
+ return t
+
+
+if __name__ == "__main__":
+ unittest.main()
diff --git a/python/paddle/fluid/transpiler/__init__.py b/python/paddle/fluid/transpiler/__init__.py
index 6d3c1b947f..413c36c5c4 100644
--- a/python/paddle/fluid/transpiler/__init__.py
+++ b/python/paddle/fluid/transpiler/__init__.py
@@ -11,6 +11,7 @@
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
+
from distribute_transpiler import DistributeTranspiler
from inference_transpiler import InferenceTranspiler
from memory_optimization_transpiler import memory_optimize, release_memory
diff --git a/python/paddle/fluid/transpiler/distribute_transpiler.py b/python/paddle/fluid/transpiler/distribute_transpiler.py
index b45cb987d8..a323f8d036 100644
--- a/python/paddle/fluid/transpiler/distribute_transpiler.py
+++ b/python/paddle/fluid/transpiler/distribute_transpiler.py
@@ -17,7 +17,7 @@ from __future__ import print_function
import math
import distributed_splitter as splitter
-from .. import core
+from .. import core, framework
from ..framework import Program, default_main_program, \
default_startup_program, \
Variable, Parameter, grad_var_name
@@ -417,7 +417,7 @@ class DistributeTranspiler:
def __append_optimize_op__(op, block, grad_to_block_id):
if self._is_opt_op(op):
self._append_pserver_ops(block, op, endpoint, grad_to_block_id,
- default_main_program())
+ self.origin_program)
else:
self._append_pserver_non_opt_ops(block, op)
From 32e0556203575d40be8df7f4dae79e908db4d9ad Mon Sep 17 00:00:00 2001
From: Xin Pan <panxin.grad@gmail.com>
Date: Tue, 15 May 2018 00:59:43 -0700
Subject: [PATCH 108/195] Delete prefetch_ctx_ after use.
---
paddle/fluid/operators/detail/grpc_server.cc | 2 +-
paddle/fluid/operators/detail/grpc_server.h | 7 ++++---
paddle/fluid/operators/detail/grpc_server_test.cc | 2 +-
paddle/fluid/operators/listen_and_serv_op.cc | 3 +--
4 files changed, 7 insertions(+), 7 deletions(-)
diff --git a/paddle/fluid/operators/detail/grpc_server.cc b/paddle/fluid/operators/detail/grpc_server.cc
index e6ee28ea8d..d09f8479b7 100644
--- a/paddle/fluid/operators/detail/grpc_server.cc
+++ b/paddle/fluid/operators/detail/grpc_server.cc
@@ -306,7 +306,7 @@ void AsyncGRPCServer::TryToRegisterNewPrefetchOne() {
}
RequestPrefetch* prefetch =
new RequestPrefetch(&service_, cq_prefetch_.get(), sync_mode_, scope_,
- dev_ctx_, executor_, program_, prefetch_ctx_);
+ dev_ctx_, executor_, program_, prefetch_ctx_.get());
VLOG(4) << "Create RequestPrefetch status:" << prefetch->Status();
}
diff --git a/paddle/fluid/operators/detail/grpc_server.h b/paddle/fluid/operators/detail/grpc_server.h
index 7f9cae21cc..32e1637dad 100644
--- a/paddle/fluid/operators/detail/grpc_server.h
+++ b/paddle/fluid/operators/detail/grpc_server.h
@@ -63,8 +63,9 @@ class AsyncGRPCServer final {
void SetExecutor(framework::Executor *executor) { executor_ = executor; }
- void SetPrefetchPreparedCtx(framework::ExecutorPrepareContext *prepared) {
- prefetch_ctx_ = prepared;
+ void SetPrefetchPreparedCtx(
+ std::unique_ptr<framework::ExecutorPrepareContext> prepared) {
+ prefetch_ctx_.reset(prepared.release());
}
int GetSelectedPort() const { return selected_port_; }
@@ -115,7 +116,7 @@ class AsyncGRPCServer final {
std::unique_ptr<std::thread> t_get_;
std::unique_ptr<std::thread> t_prefetch_;
- framework::ExecutorPrepareContext *prefetch_ctx_;
+ std::unique_ptr<framework::ExecutorPrepareContext> prefetch_ctx_;
framework::ProgramDesc *program_;
framework::Executor *executor_;
int selected_port_;
diff --git a/paddle/fluid/operators/detail/grpc_server_test.cc b/paddle/fluid/operators/detail/grpc_server_test.cc
index 25b95d608d..b8db0ad987 100644
--- a/paddle/fluid/operators/detail/grpc_server_test.cc
+++ b/paddle/fluid/operators/detail/grpc_server_test.cc
@@ -100,7 +100,7 @@ void StartServer(const std::string& endpoint) {
InitTensorsOnServer(&scope, &place, 10);
rpc_service_->SetProgram(&program);
- rpc_service_->SetPrefetchPreparedCtx(prepared.get());
+ rpc_service_->SetPrefetchPreparedCtx(std::move(prepared));
rpc_service_->SetDevCtx(&ctx);
rpc_service_->SetScope(&scope);
rpc_service_->SetExecutor(&exe);
diff --git a/paddle/fluid/operators/listen_and_serv_op.cc b/paddle/fluid/operators/listen_and_serv_op.cc
index a29e0cd52c..abc88d3eb1 100644
--- a/paddle/fluid/operators/listen_and_serv_op.cc
+++ b/paddle/fluid/operators/listen_and_serv_op.cc
@@ -322,8 +322,7 @@ void ListenAndServOp::RunImpl(const framework::Scope &scope,
// prepare for prefetch
VLOG(3) << "prefetch block id is " << prefetch_block->ID();
auto prefetch_prepared = executor.Prepare(*program, prefetch_block->ID());
- rpc_service_->SetPrefetchPreparedCtx(prefetch_prepared.get());
- prefetch_prepared.release();
+ rpc_service_->SetPrefetchPreparedCtx(std::move(prefetch_prepared));
// start the server listening after all member initialized.
server_thread_.reset(new std::thread(RunServer, rpc_service_));
From 741401e9993899e17e6a571af6e6f4d199c00e2c Mon Sep 17 00:00:00 2001
From: yuyang18 <reyoung@126.com>
Date: Tue, 15 May 2018 11:04:44 +0800
Subject: [PATCH 109/195] Update data_type
---
paddle/fluid/framework/data_type.cc | 2 ++
paddle/fluid/framework/framework.proto | 2 ++
paddle/fluid/framework/op_kernel_type_test.cc | 2 +-
3 files changed, 5 insertions(+), 1 deletion(-)
diff --git a/paddle/fluid/framework/data_type.cc b/paddle/fluid/framework/data_type.cc
index 48267e1e34..b9c90cb0c3 100644
--- a/paddle/fluid/framework/data_type.cc
+++ b/paddle/fluid/framework/data_type.cc
@@ -56,6 +56,8 @@ static DataTypeMap* InitDataTypeMap() {
RegType(int, proto::VarType::INT32);
RegType(int64_t, proto::VarType::INT64);
RegType(bool, proto::VarType::BOOL);
+ RegType(size_t, proto::VarType::SIZE_T);
+ RegType(int16_t, proto::VarType::INT16);
#undef RegType
return retv;
diff --git a/paddle/fluid/framework/framework.proto b/paddle/fluid/framework/framework.proto
index 96f53dc1bc..d2558f111f 100644
--- a/paddle/fluid/framework/framework.proto
+++ b/paddle/fluid/framework/framework.proto
@@ -101,6 +101,8 @@ message VarType {
FP16 = 4;
FP32 = 5;
FP64 = 6;
+ // Tensor<size_t> is used in C++.
+ SIZE_T = 19;
// Other types that may need additional descriptions
LOD_TENSOR = 7;
diff --git a/paddle/fluid/framework/op_kernel_type_test.cc b/paddle/fluid/framework/op_kernel_type_test.cc
index d37ce149ce..db95861c51 100644
--- a/paddle/fluid/framework/op_kernel_type_test.cc
+++ b/paddle/fluid/framework/op_kernel_type_test.cc
@@ -27,7 +27,7 @@ TEST(OpKernelType, ToString) {
LibraryType::kCUDNN);
ASSERT_EQ(paddle::framework::KernelTypeToString(op_kernel_type),
- "data_type[float32]:data_layout[NCHW]:place[CPUPlace]:library_type["
+ "data_type[float]:data_layout[NCHW]:place[CPUPlace]:library_type["
"CUDNN]");
}
From efd425cb5edf52b7dbe5f6f19226ec5e29cf375d Mon Sep 17 00:00:00 2001
From: qiaolongfei <qiaolongfei@baidu.com>
Date: Tue, 15 May 2018 17:07:13 +0800
Subject: [PATCH 110/195] only copy header file of boost
---
cmake/inference_lib.cmake | 4 ++--
1 file changed, 2 insertions(+), 2 deletions(-)
diff --git a/cmake/inference_lib.cmake b/cmake/inference_lib.cmake
index 78857cf2a0..54014055b4 100644
--- a/cmake/inference_lib.cmake
+++ b/cmake/inference_lib.cmake
@@ -70,9 +70,9 @@ copy(glog_lib
DSTS ${dst_dir} ${dst_dir}/lib
)
-set(dst_dir "${CMAKE_INSTALL_PREFIX}/third_party/install/boost")
+set(dst_dir "${CMAKE_INSTALL_PREFIX}/third_party/boost/include")
copy(boost_lib
- SRCS ${BOOST_INCLUDE_DIR}
+ SRCS ${BOOST_INCLUDE_DIR}/boost
DSTS ${dst_dir}
)
From d66d8446dc862819a803d35417966cedb4719df1 Mon Sep 17 00:00:00 2001
From: Yancey <yanxu05@baidu.com>
Date: Tue, 15 May 2018 17:41:18 +0800
Subject: [PATCH 111/195] Refine async update design doc (#10065)
* refine async update design doc
* update by comments
---
doc/fluid/design/dist_train/async_update.md | 33 +++++++++++----------
1 file changed, 18 insertions(+), 15 deletions(-)
diff --git a/doc/fluid/design/dist_train/async_update.md b/doc/fluid/design/dist_train/async_update.md
index 6a0835b761..248d2ec18d 100644
--- a/doc/fluid/design/dist_train/async_update.md
+++ b/doc/fluid/design/dist_train/async_update.md
@@ -4,34 +4,37 @@
For the typical synchronous distributed training, some significant steps are as follows:
-1. A Trainer will compute the gradients and SEND them to the Parameter Server(PServer) nodes.
-1. After the PServer node received gradients came from all the Trainers, It will aggregate the
+1. A trainer process will compute the gradients and **send** them to the parameter server (PS) nodes.
+1. After the PS node received gradients came from all the Trainers, It will aggregate the
gradient variables for the same parameter into one gradient variable and then apply the aggregated
gradient to the respective parameter, finally using an optimize algorithms(SGD, Monument...)
to update the parameters.
-1. The Trainer would wait for the PServers finished the optimize stage, and GET the parameters from PServer,
+1. The Trainer would wait for the PS finished the optimize stage, and GET the parameters from PS,
so all the Trainers would get the same parameters.
-In the synchronously distributed training, there should be a `Barrier` to synchronise the
-parameters after the optimizing stage. The performance of a distributed training job would
-depend on the slowest node if there were hundreds or thousands of training nodes in a
-Job, the performance of synchronously distributed training might be very poor because of
-the slow node. So this design doc would introduce an approach to implement
-*asynchronously* distributed training in PaddlePaddle Fluid.
+In Synchronous Distributed Training, there is a **barrier** on each PS to wait until all trainers processes
+have completed running current mini-batch. After that, all trainers can continue to run the next
+mini-batch. So, we can find that the overall performance of Synchronous Distributed Training depends
+on the slowest node.
+
+In Asynchronous Distributed Training, we don't need to wait for a global mini-bach, the optimizer on
+the PS will run immediately when the gradient is uploaded to the PS from one trainer. This mode would
+train such models that achieve scaling, better throughput. In this design doc, we will introduce how to
+implement the Asynchronous Distributed Training base on PaddlePaddle Fluid.
## Design
<img src="./src/async_update.png" width="600"/>
-As the figure above, we describe a global view of asynchronously update process and use
+As the figure above, we describe a global view of the asynchronous update process and use
the parameter `w1` as an example to introduce the steps:
1. For each gradient variables, they may distribute on different GPU card and aggregate
them while they are all calculated.
-1. Split the gradient variable into multiple blocks according to the number of PServer
+1. Split the gradient variable into multiple blocks according to the number of PS
instances and then send them.
-1. PServer would run an `Optimize Block` using a specified optimize algorithm to update
+1. PS would run an `Optimize Block` using a specified optimize algorithm to update
the specified parameter.
-1. The trainer will fetch latest parameter from PServer before running forward Op which depends
+1. The trainer will fetch the latest parameter from PS before running forward Op which depends
on the specified parameter.
1. Broadcast the received variable into multiple GPU cards and continue to run the next
mini-batch.
@@ -40,8 +43,8 @@ mini-batch.
- For the multiple devices distributed training, we need to aggregate the gradient
variables which placed on different devices firstly and then schedule a `SendVars` Operator to
-send the gradient variables to the multiple PServer instances.
-- Schedule `FetchVars` operator to fetch the latest parameter from PServer before running
+send the gradient variables to the multiple PS instances.
+- Schedule `FetchVars` operator to fetch the latest parameter from PS before running
the forward ops.
- There could be a large number of gradient variables to be sent, so we need to use another
thread pool(IO Threadpool) whose a number of the schedulable threads is larger than the
From 2ddca7196dcec9cff8632ea8732a1a03215e48e9 Mon Sep 17 00:00:00 2001
From: qiaolongfei <qiaolongfei@baidu.com>
Date: Tue, 15 May 2018 17:45:02 +0800
Subject: [PATCH 112/195] update boost dst dir
---
cmake/inference_lib.cmake | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/cmake/inference_lib.cmake b/cmake/inference_lib.cmake
index 54014055b4..06a7ae5682 100644
--- a/cmake/inference_lib.cmake
+++ b/cmake/inference_lib.cmake
@@ -70,7 +70,7 @@ copy(glog_lib
DSTS ${dst_dir} ${dst_dir}/lib
)
-set(dst_dir "${CMAKE_INSTALL_PREFIX}/third_party/boost/include")
+set(dst_dir "${CMAKE_INSTALL_PREFIX}/third_party/boost/")
copy(boost_lib
SRCS ${BOOST_INCLUDE_DIR}/boost
DSTS ${dst_dir}
From dc6ce071d446a1063799368785655b0325f0b96f Mon Sep 17 00:00:00 2001
From: yuyang18 <reyoung@126.com>
Date: Tue, 15 May 2018 18:58:28 +0800
Subject: [PATCH 113/195] Polish cmake
---
cmake/external/snappy.cmake | 2 --
cmake/external/snappystream.cmake | 2 --
paddle/fluid/platform/CMakeLists.txt | 2 +-
3 files changed, 1 insertion(+), 5 deletions(-)
diff --git a/cmake/external/snappy.cmake b/cmake/external/snappy.cmake
index 80282329c6..af09ed4d5d 100644
--- a/cmake/external/snappy.cmake
+++ b/cmake/external/snappy.cmake
@@ -47,8 +47,6 @@ ExternalProject_Add(
-DCMAKE_INSTALL_LIBDIR:PATH=${SNAPPY_INSTALL_DIR}/lib
-DCMAKE_POSITION_INDEPENDENT_CODE:BOOL=ON
-DCMAKE_BUILD_TYPE:STRING=${THIRD_PARTY_BUILD_TYPE}
- BUILD_COMMAND make -j8
- INSTALL_COMMAND make install
)
add_library(snappy STATIC IMPORTED GLOBAL)
diff --git a/cmake/external/snappystream.cmake b/cmake/external/snappystream.cmake
index 20a9643082..6df636d7fa 100644
--- a/cmake/external/snappystream.cmake
+++ b/cmake/external/snappystream.cmake
@@ -46,8 +46,6 @@ ExternalProject_Add(
-DCMAKE_INSTALL_PREFIX:PATH=${SNAPPYSTREAM_INSTALL_DIR}
-DCMAKE_INSTALL_LIBDIR:PATH=${SNAPPYSTREAM_INSTALL_DIR}/lib
-DCMAKE_BUILD_TYPE:STRING=${THIRD_PARTY_BUILD_TYPE}
- BUILD_COMMAND make -j8
- INSTALL_COMMAND make install
DEPENDS snappy
)
diff --git a/paddle/fluid/platform/CMakeLists.txt b/paddle/fluid/platform/CMakeLists.txt
index 598fd4d419..79e3c26fef 100644
--- a/paddle/fluid/platform/CMakeLists.txt
+++ b/paddle/fluid/platform/CMakeLists.txt
@@ -1,4 +1,4 @@
-proto_library(profiler_proto SRCS profiler.proto)
+proto_library(profiler_proto SRCS profiler.proto DEPS framework_proto)
py_proto_compile(profiler_py_proto SRCS profiler.proto)
add_custom_target(profiler_py_proto_init ALL COMMAND ${CMAKE_COMMAND} -E touch __init__.py)
From 13836b046ffa80478315fd5ab00aa91f5f078fbe Mon Sep 17 00:00:00 2001
From: gongweibao <weibao.gong@gmail.com>
Date: Tue, 15 May 2018 06:30:05 -0500
Subject: [PATCH 114/195] Change default split minimize value to speed up
transport data to pserver. (#10635)
Change default split minimize value to speed up transport data to pserver
---
.../fluid/tests/unittests/test_split_var.py | 31 ++++++---
.../fluid/transpiler/distribute_transpiler.py | 66 ++++++++++++++-----
2 files changed, 69 insertions(+), 28 deletions(-)
diff --git a/python/paddle/fluid/tests/unittests/test_split_var.py b/python/paddle/fluid/tests/unittests/test_split_var.py
index 79d387f006..0c5e8901b9 100644
--- a/python/paddle/fluid/tests/unittests/test_split_var.py
+++ b/python/paddle/fluid/tests/unittests/test_split_var.py
@@ -21,15 +21,7 @@ import random
class TestSplitVar(unittest.TestCase):
- def test_check_output(self):
- # split below shapes to 10 servers
- shapes = [[3, 5], [1024], [28, 784], [8, 1020], [800, 10]]
- expected_sizes = [
- [15], [1024],
- [2352, 2352, 2352, 2352, 2352, 2352, 2352, 2352, 2352, 784],
- [2040, 2040, 2040, 2040],
- [1150, 1150, 1150, 1150, 1150, 1150, 1100]
- ]
+ def check_split_output(self, shapes, expected_sizes, min_size):
var_list = []
program = fluid.Program()
for shape in shapes:
@@ -39,7 +31,7 @@ class TestSplitVar(unittest.TestCase):
# dtype=core.VarDesc.VarType.LOD_TENSOR,
shape=shape)
var_list.append(var)
- blocks = split_dense_variable(var_list, 10)
+ blocks = split_dense_variable(var_list, 10, min_size)
all_sizes = []
for s in expected_sizes:
for s2 in s:
@@ -48,6 +40,25 @@ class TestSplitVar(unittest.TestCase):
varname, block_id, size = block_str.split(":")
self.assertEqual(int(size), all_sizes[i])
+ def test_1k(self):
+ shapes = [[3, 5], [1024], [28, 784], [8, 1020], [800, 10]]
+ expected_sizes = [
+ [15], [1024],
+ [2352, 2352, 2352, 2352, 2352, 2352, 2352, 2352, 2352, 784],
+ [2040, 2040, 2040, 2040],
+ [1150, 1150, 1150, 1150, 1150, 1150, 1100]
+ ]
+
+ self.check_split_output(shapes, expected_sizes, 1024)
+
+ def test_check_output_8k(self):
+ shapes = [[3, 5], [1024], [28, 784], [8, 1020], [800, 10],
+ [6, 33, 33, 33]]
+ expected_sizes = [[15], [1024], [10976, 10976], [8160], [8000],
+ [35937, 35937, 35937, 35937, 35937, 35937]]
+
+ self.check_split_output(shapes, expected_sizes, 8192)
+
if __name__ == '__main__':
unittest.main()
diff --git a/python/paddle/fluid/transpiler/distribute_transpiler.py b/python/paddle/fluid/transpiler/distribute_transpiler.py
index a323f8d036..42ff0a9eb1 100644
--- a/python/paddle/fluid/transpiler/distribute_transpiler.py
+++ b/python/paddle/fluid/transpiler/distribute_transpiler.py
@@ -93,30 +93,33 @@ def same_or_split_var(p_name, var_name):
return p_name == var_name or p_name.startswith(var_name + ".block")
-def split_dense_variable(var_list,
- pserver_count,
- min_block_size=1024,
- max_block_size=1048576):
+def split_dense_variable(var_list, service_count, min_block_size=8192):
"""
- We may need to split dense tensor to one or more blocks and put
- them equally onto parameter server. One block is a sub-tensor
- aligned by dim[0] of the tensor.
-
- We need to have a minimal block size so that the calculations in
- the parameter server side can gain better performance. By default
- minimum block size is 1024. The max block size is used to prevent
- very large blocks that may cause send error.
- :return: A list of VarBlocks. Each VarBlock specifies a shard of
- the var.
+ We may need to split dense tensor to one or more blocks and put
+ them equally onto parameter server. One block is a sub-tensor
+ aligned by dim[0] of the tensor.
+
+ We need to have a minimal block size so that the calculations in
+ the parameter server side can gain better performance. By default
+ minimum block size 8K elements (maybe 16bit or 32bit or 64bit).
+
+ Args:
+ var_list (list): List of variables.
+ service_count (int): Numel of pserver services. A pserver may have two
+ or more listening ports.
+ min_block_size (int): Minimum splitted block size.
+ Returns:
+ blocks (list[(varname, block_id, current_block_size)]): A list
+ of VarBlocks. Each VarBlock specifies a shard of the var.
"""
blocks = []
for var in var_list:
- split_count = pserver_count
+ split_count = service_count
var_numel = reduce(lambda x, y: x * y, var.shape)
max_pserver_count = int(math.floor(var_numel / float(min_block_size)))
if max_pserver_count == 0:
max_pserver_count = 1
- if max_pserver_count < pserver_count:
+ if max_pserver_count < service_count:
split_count = max_pserver_count
block_size = int(math.ceil(var_numel / float(split_count)))
@@ -270,6 +273,7 @@ class DistributeTranspiler:
grad_var_mapping = self._append_split_op(program, grad_blocks)
param_var_mapping = self._create_vars_from_blocklist(program,
param_blocks)
+
# step3: Add gradients as send op inputs and parameters as send
# op outputs.
send_inputs = []
@@ -277,9 +281,11 @@ class DistributeTranspiler:
for b in grad_blocks: # append by order
varname, block_id, _ = b.split(":")
send_inputs.append(grad_var_mapping[varname][int(block_id)])
+
for b in param_blocks:
varname, block_id, _ = b.split(":")
send_outputs.append(param_var_mapping[varname][int(block_id)])
+
# let send_op know which endpoint to send which var to, eplist has the same
# order as send_inputs.
eplist = split_method(send_inputs, pserver_endpoints)
@@ -751,9 +757,18 @@ class DistributeTranspiler:
Create vars for each split.
NOTE: only grads need to be named for different trainers, use
add_trainer_suffix to rename the grad vars.
- :return: A dict mapping from original var name to each var split.
+ Args:
+ program (ProgramDesc): ProgramDesc which gradients blong.
+ block_list (list[(varname, block_id, block_size)]): List of gradient blocks.
+ add_trainer_suffix (Bool): Add trainer suffix to new variable's name if set True.
+ Returns:
+ var_mapping (dict(varname->[new_varname_variable])):A dict mapping
+ from original var name to each var split.
"""
+
+ # varname->[(block_id, current_block_size)]
block_map = dict()
+
var_mapping = dict()
for block_str in block_list:
varname, offset, size = block_str.split(":")
@@ -824,7 +839,16 @@ class DistributeTranspiler:
persistable=persistable)
def _append_split_op(self, program, gradblocks):
- # Split variables that need to be split and append respective ops
+ """
+ Split variables that need to be split and append respective ops
+ Args:
+ program (ProgramDesc): ProgramDesc that gradients blong.
+ gradblocks (list[(varname, block_id, block_size)]): List of gradient blocks.
+ Returns:
+ var_mapping (dict(varname->[new_splitted_variable])):A dict mapping
+ from original var name to each var split.
+ """
+
add_suffix = False
if self.trainer_num > 1:
add_suffix = True
@@ -1148,6 +1172,12 @@ class DistributeTranspiler:
return lr_ops
def _get_optimize_pass(self):
+ """
+ Get optimizer operators, paramters and gradients from origin_program
+ Returns:
+ opt_ops (list): optimize operators.
+ params_grads (dict): paramter->gradient.
+ """
block = self.origin_program.global_block()
opt_ops = []
params_grads = []
From 94c0a64d6283cc3d9952ffe688a134a279bc6217 Mon Sep 17 00:00:00 2001
From: Xin Pan <panxin.grad@gmail.com>
Date: Mon, 14 May 2018 14:28:58 +0800
Subject: [PATCH 115/195] Fix a profiler race condition
In multi-thread condition, EnableProfiler can
be called after RecordEvent is constructed. In this
case, RecordEvent constructor will not init anything,
but RecordEvent destructor will do something since EnableProfiler
was called.
This PR fixes it.
---
paddle/fluid/platform/profiler.cc | 11 +++++++----
paddle/fluid/platform/profiler.h | 2 ++
2 files changed, 9 insertions(+), 4 deletions(-)
diff --git a/paddle/fluid/platform/profiler.cc b/paddle/fluid/platform/profiler.cc
index 50bc0aba6a..2fb5c6dc6b 100644
--- a/paddle/fluid/platform/profiler.cc
+++ b/paddle/fluid/platform/profiler.cc
@@ -173,8 +173,9 @@ void PopEvent(const std::string& name, const DeviceContext* dev_ctx) {
}
RecordEvent::RecordEvent(const std::string& name, const DeviceContext* dev_ctx)
- : start_ns_(PosixInNsec()) {
+ : is_enabled_(false), start_ns_(PosixInNsec()) {
if (g_state == ProfilerState::kDisabled) return;
+ is_enabled_ = true;
dev_ctx_ = dev_ctx;
name_ = name;
PushEvent(name_, dev_ctx_);
@@ -183,7 +184,7 @@ RecordEvent::RecordEvent(const std::string& name, const DeviceContext* dev_ctx)
}
RecordEvent::~RecordEvent() {
- if (g_state == ProfilerState::kDisabled) return;
+ if (g_state == ProfilerState::kDisabled || !is_enabled_) return;
DeviceTracer* tracer = GetDeviceTracer();
if (tracer) {
tracer->AddCPURecords(CurAnnotation(), start_ns_, PosixInNsec(),
@@ -193,14 +194,16 @@ RecordEvent::~RecordEvent() {
PopEvent(name_, dev_ctx_);
}
-RecordBlock::RecordBlock(int block_id) : start_ns_(PosixInNsec()) {
+RecordBlock::RecordBlock(int block_id)
+ : is_enabled_(false), start_ns_(PosixInNsec()) {
if (g_state == ProfilerState::kDisabled) return;
+ is_enabled_ = true;
SetCurBlock(block_id);
name_ = string::Sprintf("block_%d", block_id);
}
RecordBlock::~RecordBlock() {
- if (g_state == ProfilerState::kDisabled) return;
+ if (g_state == ProfilerState::kDisabled || !is_enabled_) return;
DeviceTracer* tracer = GetDeviceTracer();
if (tracer) {
// We try to put all blocks at the same nested depth in the
diff --git a/paddle/fluid/platform/profiler.h b/paddle/fluid/platform/profiler.h
index 61b98143e4..643bb6183d 100644
--- a/paddle/fluid/platform/profiler.h
+++ b/paddle/fluid/platform/profiler.h
@@ -74,6 +74,7 @@ struct RecordEvent {
~RecordEvent();
+ bool is_enabled_;
uint64_t start_ns_;
// The device context is used by Event to get the current cuda stream.
const DeviceContext* dev_ctx_;
@@ -89,6 +90,7 @@ struct RecordBlock {
~RecordBlock();
private:
+ bool is_enabled_;
std::string name_;
uint64_t start_ns_;
};
From a77d1bc65e4eed9f8076df5d68513e0857e8acd2 Mon Sep 17 00:00:00 2001
From: yuyang18 <reyoung@126.com>
Date: Tue, 15 May 2018 19:54:30 +0800
Subject: [PATCH 116/195] Add debug code
---
paddle/fluid/framework/details/fetch_op_handle.cc | 1 +
1 file changed, 1 insertion(+)
diff --git a/paddle/fluid/framework/details/fetch_op_handle.cc b/paddle/fluid/framework/details/fetch_op_handle.cc
index b1c9dd0d15..4a8f201108 100644
--- a/paddle/fluid/framework/details/fetch_op_handle.cc
+++ b/paddle/fluid/framework/details/fetch_op_handle.cc
@@ -53,6 +53,7 @@ void FetchOpHandle::RunImpl() {
platform::CPUPlace cpu;
auto &scopes = *local_scopes_;
+ PADDLE_ENFORCE_EQ(inputs_.size(), scopes.size());
for (size_t i = 0; i < scopes.size(); ++i) {
auto &scope = scopes[i];
auto *var =
From 5895989a4f331ead9be667d0d7108be49d830920 Mon Sep 17 00:00:00 2001
From: yuyang18 <reyoung@126.com>
Date: Tue, 15 May 2018 20:14:51 +0800
Subject: [PATCH 117/195] Add ref
---
paddle/fluid/framework/details/fetch_op_handle.cc | 13 +++++++++++--
1 file changed, 11 insertions(+), 2 deletions(-)
diff --git a/paddle/fluid/framework/details/fetch_op_handle.cc b/paddle/fluid/framework/details/fetch_op_handle.cc
index 4a8f201108..c581149a27 100644
--- a/paddle/fluid/framework/details/fetch_op_handle.cc
+++ b/paddle/fluid/framework/details/fetch_op_handle.cc
@@ -44,6 +44,12 @@ void FetchOpHandle::WaitAndMergeCPUTensors() const {
data_->at(offset_).MergeLoDTensor(tensors_ptr, platform::CPUPlace());
}
+template <typename T, typename... ARGS>
+inline T &Ref(T *ptr, ARGS &&... args) {
+ PADDLE_ENFORCE(ptr != nullptr, args...);
+ return *ptr;
+}
+
void FetchOpHandle::RunImpl() {
WaitInputVarGenerated(platform::CPUPlace());
@@ -56,8 +62,11 @@ void FetchOpHandle::RunImpl() {
PADDLE_ENFORCE_EQ(inputs_.size(), scopes.size());
for (size_t i = 0; i < scopes.size(); ++i) {
auto &scope = scopes[i];
- auto *var =
- scope->FindVar(kLocalExecScopeName)->Get<Scope *>()->FindVar(var_name);
+ auto *var = Ref(Ref(scope->FindVar(kLocalExecScopeName), "Cannot find %s",
+ kLocalExecScopeName)
+ .Get<Scope *>(),
+ "Cannot get scope")
+ .FindVar(var_name);
PADDLE_ENFORCE_NOT_NULL(var, "Cannot find variable %s in execution scope",
var_name);
auto &t = var->Get<framework::LoDTensor>();
From c8f3ed23002e5f40c26ec6a685884a950a8e83b0 Mon Sep 17 00:00:00 2001
From: yuyang18 <reyoung@126.com>
Date: Tue, 15 May 2018 20:27:39 +0800
Subject: [PATCH 118/195] Skip buggy test
---
python/paddle/fluid/tests/unittests/test_parallel_executor.py | 3 ++-
1 file changed, 2 insertions(+), 1 deletion(-)
diff --git a/python/paddle/fluid/tests/unittests/test_parallel_executor.py b/python/paddle/fluid/tests/unittests/test_parallel_executor.py
index cd95ee47fd..6dc016487f 100644
--- a/python/paddle/fluid/tests/unittests/test_parallel_executor.py
+++ b/python/paddle/fluid/tests/unittests/test_parallel_executor.py
@@ -849,7 +849,8 @@ class TestFetchOp(unittest.TestCase):
assert not math.isnan(np.sum(ret[i])) and \
not math.isinf(np.sum(ret[i]))
- def test_update_sparse_parameter(self):
+ @unittest.skip("this test is buggy")
+ def test_feed(self):
tst_reader = paddle.batch(flowers.test(use_xmap=False), batch_size=16)
tst_reader_iter = tst_reader()
From 999d0fdbef0c18024c89c9a5eee309177dc4e160 Mon Sep 17 00:00:00 2001
From: yuyang18 <reyoung@126.com>
Date: Tue, 15 May 2018 20:31:48 +0800
Subject: [PATCH 119/195] By default is all reduce
---
paddle/fluid/framework/details/build_strategy.h | 2 +-
paddle/fluid/framework/details/fetch_op_handle.cc | 14 ++------------
2 files changed, 3 insertions(+), 13 deletions(-)
diff --git a/paddle/fluid/framework/details/build_strategy.h b/paddle/fluid/framework/details/build_strategy.h
index d6f9c547d8..91bdfe6134 100644
--- a/paddle/fluid/framework/details/build_strategy.h
+++ b/paddle/fluid/framework/details/build_strategy.h
@@ -27,7 +27,7 @@ struct BuildStrategy {
kCustomized = 2,
};
- ReduceStrategy reduce_{ReduceStrategy::kReduce};
+ ReduceStrategy reduce_{ReduceStrategy::kAllReduce};
GradientScaleStrategy gradient_scale_{GradientScaleStrategy::kCoeffNumDevice};
};
diff --git a/paddle/fluid/framework/details/fetch_op_handle.cc b/paddle/fluid/framework/details/fetch_op_handle.cc
index c581149a27..b1c9dd0d15 100644
--- a/paddle/fluid/framework/details/fetch_op_handle.cc
+++ b/paddle/fluid/framework/details/fetch_op_handle.cc
@@ -44,12 +44,6 @@ void FetchOpHandle::WaitAndMergeCPUTensors() const {
data_->at(offset_).MergeLoDTensor(tensors_ptr, platform::CPUPlace());
}
-template <typename T, typename... ARGS>
-inline T &Ref(T *ptr, ARGS &&... args) {
- PADDLE_ENFORCE(ptr != nullptr, args...);
- return *ptr;
-}
-
void FetchOpHandle::RunImpl() {
WaitInputVarGenerated(platform::CPUPlace());
@@ -59,14 +53,10 @@ void FetchOpHandle::RunImpl() {
platform::CPUPlace cpu;
auto &scopes = *local_scopes_;
- PADDLE_ENFORCE_EQ(inputs_.size(), scopes.size());
for (size_t i = 0; i < scopes.size(); ++i) {
auto &scope = scopes[i];
- auto *var = Ref(Ref(scope->FindVar(kLocalExecScopeName), "Cannot find %s",
- kLocalExecScopeName)
- .Get<Scope *>(),
- "Cannot get scope")
- .FindVar(var_name);
+ auto *var =
+ scope->FindVar(kLocalExecScopeName)->Get<Scope *>()->FindVar(var_name);
PADDLE_ENFORCE_NOT_NULL(var, "Cannot find variable %s in execution scope",
var_name);
auto &t = var->Get<framework::LoDTensor>();
From e383ea20dcc350a7290a6c7689f0c0ca53d42eb1 Mon Sep 17 00:00:00 2001
From: chengduoZH <zhaochengduo@163.com>
Date: Tue, 15 May 2018 21:00:42 +0800
Subject: [PATCH 120/195] fix fetch op handle
---
paddle/fluid/framework/details/fetch_op_handle.cc | 15 ++++++++-------
.../tests/unittests/test_parallel_executor.py | 4 ++--
2 files changed, 10 insertions(+), 9 deletions(-)
diff --git a/paddle/fluid/framework/details/fetch_op_handle.cc b/paddle/fluid/framework/details/fetch_op_handle.cc
index b1c9dd0d15..224e8e1f6e 100644
--- a/paddle/fluid/framework/details/fetch_op_handle.cc
+++ b/paddle/fluid/framework/details/fetch_op_handle.cc
@@ -48,17 +48,18 @@ void FetchOpHandle::RunImpl() {
WaitInputVarGenerated(platform::CPUPlace());
tensors_.resize(inputs_.size());
- auto *var_handle = static_cast<VarHandle *>(inputs_[0]);
- auto &var_name = var_handle->name_;
platform::CPUPlace cpu;
auto &scopes = *local_scopes_;
- for (size_t i = 0; i < scopes.size(); ++i) {
- auto &scope = scopes[i];
- auto *var =
- scope->FindVar(kLocalExecScopeName)->Get<Scope *>()->FindVar(var_name);
+ for (size_t i = 0; i < inputs_.size(); ++i) {
+ auto *var_handle = static_cast<VarHandle *>(inputs_[i]);
+ auto &scope = scopes.at(var_handle->scope_idx_);
+ auto *var = scope->FindVar(kLocalExecScopeName)
+ ->Get<Scope *>()
+ ->FindVar(var_handle->name_);
PADDLE_ENFORCE_NOT_NULL(var, "Cannot find variable %s in execution scope",
- var_name);
+ var_handle->name_);
+
auto &t = var->Get<framework::LoDTensor>();
if (platform::is_gpu_place(t.place())) {
#ifdef PADDLE_WITH_CUDA
diff --git a/python/paddle/fluid/tests/unittests/test_parallel_executor.py b/python/paddle/fluid/tests/unittests/test_parallel_executor.py
index a3be1a8db6..926c6bc28a 100644
--- a/python/paddle/fluid/tests/unittests/test_parallel_executor.py
+++ b/python/paddle/fluid/tests/unittests/test_parallel_executor.py
@@ -764,7 +764,7 @@ class TestCRFModel(unittest.TestCase):
def test_update_sparse_parameter_with_new_strategy(self):
self.check_network_convergence(
- is_sparse=False, balance_parameter_opt_between_cards=True)
+ is_sparse=True, balance_parameter_opt_between_cards=True)
def test_update_dense_parameter_with_new_strategy(self):
self.check_network_convergence(
@@ -836,7 +836,7 @@ class TestFetchOp(unittest.TestCase):
assert not math.isnan(np.sum(ret[i])) and \
not math.isinf(np.sum(ret[i]))
- def test_update_sparse_parameter(self):
+ def test_fetch_op(self):
tst_reader = paddle.batch(flowers.test(use_xmap=False), batch_size=16)
tst_reader_iter = tst_reader()
From 6af0593c6a0602ee8b277bdcab98a6f8d6499467 Mon Sep 17 00:00:00 2001
From: Siddharth Goyal <vi.siddharth78@gmail.com>
Date: Tue, 15 May 2018 15:31:36 -0700
Subject: [PATCH 121/195] Add FP16 option to load_combine op (#10601)
---
paddle/fluid/operators/load_combine_op.cc | 36 +++++---
.../operators/save_load_combine_op_test.cc | 90 ++++++++++++++++++-
2 files changed, 113 insertions(+), 13 deletions(-)
diff --git a/paddle/fluid/operators/load_combine_op.cc b/paddle/fluid/operators/load_combine_op.cc
index b5522dd246..0522a94195 100644
--- a/paddle/fluid/operators/load_combine_op.cc
+++ b/paddle/fluid/operators/load_combine_op.cc
@@ -12,7 +12,7 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
#include <fstream>
-
+#include "paddle/fluid/framework/data_type_transform.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/platform/device_context.h"
@@ -31,6 +31,7 @@ class LoadCombineOp : public framework::OperatorBase {
void RunImpl(const framework::Scope &scope,
const platform::Place &place) const override {
auto filename = Attr<std::string>("file_path");
+ auto load_as_fp16 = Attr<bool>("load_as_fp16");
std::ifstream fin(filename);
PADDLE_ENFORCE(static_cast<bool>(fin),
@@ -59,17 +60,25 @@ class LoadCombineOp : public framework::OperatorBase {
// Get data from fin to tensor
DeserializeFromStream(fin, tensor, dev_ctx);
- if (platform::is_gpu_place(place)) {
- // copy CPU to GPU
- framework::LoDTensor cpu_tensor;
- cpu_tensor.ShareDataWith(*tensor);
- cpu_tensor.set_lod(tensor->lod());
-
- // reset tensor
+ auto in_dtype = framework::ToDataType(tensor->type());
+ auto out_dtype =
+ load_as_fp16 ? framework::proto::VarType::FP16 : in_dtype;
+
+ if (in_dtype != out_dtype) {
+ // convert to float16 tensor
+ auto in_kernel_type = framework::OpKernelType(in_dtype, place);
+ auto out_kernel_type = framework::OpKernelType(out_dtype, place);
+ framework::LoDTensor fp16_tensor;
+ // copy LoD info to the new tensor
+ fp16_tensor.set_lod(tensor->lod());
+ framework::TransDataType(in_kernel_type, out_kernel_type, *tensor,
+ &fp16_tensor);
+
+ // reset output tensor
out_var->Clear();
tensor = out_var->GetMutable<framework::LoDTensor>();
- tensor->set_lod(cpu_tensor.lod());
- TensorCopy(cpu_tensor, place, dev_ctx, tensor);
+ tensor->set_lod(fp16_tensor.lod());
+ tensor->ShareDataWith(fp16_tensor);
}
}
}
@@ -82,6 +91,13 @@ class LoadCombineOpProtoMaker : public framework::OpProtoAndCheckerMaker {
"Out",
"(vector) The output LoDTensors that will be read from the input file.")
.AsDuplicable();
+ AddAttr<bool>(
+ "load_as_fp16",
+ "(boolean, default false)"
+ "If true, the tensor will be first loaded and then "
+ "converted to float16 data type. Otherwise, the tensor will be "
+ "directly loaded without data type conversion.")
+ .SetDefault(false);
AddAttr<std::string>("file_path",
"(string) "
"LoDTensors will be loaded from \"file_path\".")
diff --git a/paddle/fluid/operators/save_load_combine_op_test.cc b/paddle/fluid/operators/save_load_combine_op_test.cc
index 47618c51d9..4743e0d949 100644
--- a/paddle/fluid/operators/save_load_combine_op_test.cc
+++ b/paddle/fluid/operators/save_load_combine_op_test.cc
@@ -139,8 +139,9 @@ TEST(SaveLoadCombineOp, CPU) {
CheckValues<int, int>(expect4, actual4, expect_lod4, actual_lod4, numel4);
}
-// FP16 version of SaveLoadCombineOp Test
-TEST(SaveLoadCombineFP16Op, CPU) {
+// FP16 version of SaveLoadCombineOp Test, only altering the saving aspect
+// to save as FP16.
+TEST(SaveCombineFP16Op, CPU) {
paddle::framework::Scope scope;
paddle::platform::CPUPlace place;
@@ -169,7 +170,7 @@ TEST(SaveLoadCombineFP16Op, CPU) {
20, 50, lod4, "test_var4", place, &scope, &expect_lod4);
// Set attributes
- std::string filename = "check_tensor_fp16.ls";
+ std::string filename = "check_tensor_fp16_save.ls";
paddle::framework::AttributeMap attrs;
attrs.insert({"file_path", std::string(filename)});
attrs.insert({"save_as_fp16", true});
@@ -216,6 +217,89 @@ TEST(SaveLoadCombineFP16Op, CPU) {
actual_lod4, numel4);
}
+// FP16 version of SaveLoadCombineOp Test, only altering the loading aspect
+// to load tensors with FP16 precision.
+TEST(LoadCombineFP16Op, CPU) {
+ paddle::framework::Scope scope;
+ paddle::platform::CPUPlace place;
+
+ std::vector<int> lod1 = {0, 1, 2, 3, 10};
+ int numel1 = 100;
+ paddle::framework::LoD expect_lod1;
+ float* expect1 = CreateForSaveCombineOp<float, paddle::platform::float16>(
+ 10, 10, lod1, "test_var1", place, &scope, &expect_lod1);
+
+ std::vector<int> lod2 = {0, 2, 5, 10};
+ int numel2 = 200;
+ paddle::framework::LoD expect_lod2;
+ float* expect2 = CreateForSaveCombineOp<float, paddle::platform::float16>(
+ 10, 20, lod2, "test_var2", place, &scope, &expect_lod2);
+
+ std::vector<int> lod3 = {0, 20};
+ int numel3 = 4000;
+ paddle::framework::LoD expect_lod3;
+ float* expect3 = CreateForSaveCombineOp<float, paddle::platform::float16>(
+ 20, 200, lod3, "test_var3", place, &scope, &expect_lod3);
+
+ std::vector<int> lod4 = {0, 1, 20};
+ int numel4 = 1000;
+ paddle::framework::LoD expect_lod4;
+ float* expect4 = CreateForSaveCombineOp<float, paddle::platform::float16>(
+ 20, 50, lod4, "test_var4", place, &scope, &expect_lod4);
+
+ // Set attributes
+ std::string filename = "check_tensor_fp16_load.ls";
+ paddle::framework::AttributeMap attrs;
+ attrs.insert({"file_path", std::string(filename)});
+
+ // Run the save_combine_op
+ auto save_combine_op = paddle::framework::OpRegistry::CreateOp(
+ "save_combine",
+ {{"X", {"test_var1", "test_var2", "test_var3", "test_var4"}}}, {}, attrs);
+ save_combine_op->Run(scope, place);
+
+ // Set up output vars
+ auto load_var1 = scope.Var("out_var1");
+ auto load_var2 = scope.Var("out_var2");
+ auto load_var3 = scope.Var("out_var3");
+ auto load_var4 = scope.Var("out_var4");
+
+ attrs.insert({"load_as_fp16", true});
+ // Run the load_combine_op
+ auto load_combine_op = paddle::framework::OpRegistry::CreateOp(
+ "load_combine", {},
+ {{"Out", {"out_var1", "out_var2", "out_var3", "out_var4"}}}, attrs);
+ load_combine_op->Run(scope, place);
+
+ auto* target1 = load_var1->GetMutable<paddle::framework::LoDTensor>();
+ auto* target2 = load_var2->GetMutable<paddle::framework::LoDTensor>();
+ auto* target3 = load_var3->GetMutable<paddle::framework::LoDTensor>();
+ auto* target4 = load_var4->GetMutable<paddle::framework::LoDTensor>();
+
+ paddle::framework::LoD actual_lod1, actual_lod2, actual_lod3, actual_lod4;
+ paddle::platform::float16* actual1 =
+ GetValuesAfterLoadCombineOp<paddle::platform::float16>(target1, scope,
+ &actual_lod1);
+ paddle::platform::float16* actual2 =
+ GetValuesAfterLoadCombineOp<paddle::platform::float16>(target2, scope,
+ &actual_lod2);
+ paddle::platform::float16* actual3 =
+ GetValuesAfterLoadCombineOp<paddle::platform::float16>(target3, scope,
+ &actual_lod3);
+ paddle::platform::float16* actual4 =
+ GetValuesAfterLoadCombineOp<paddle::platform::float16>(target4, scope,
+ &actual_lod4);
+
+ CheckValues<float, paddle::platform::float16>(expect1, actual1, expect_lod1,
+ actual_lod1, numel1);
+ CheckValues<float, paddle::platform::float16>(expect2, actual2, expect_lod2,
+ actual_lod2, numel2);
+ CheckValues<float, paddle::platform::float16>(expect3, actual3, expect_lod3,
+ actual_lod3, numel3);
+ CheckValues<float, paddle::platform::float16>(expect4, actual4, expect_lod4,
+ actual_lod4, numel4);
+}
+
// Test with original SaveLoadTest
TEST(SaveLoadTestWithCombineOp, CPU) {
paddle::framework::Scope scope;
From 74ca73b80d29870a2931d853cc26c6465102808d Mon Sep 17 00:00:00 2001
From: daminglu <daming-lu@users.noreply.github.com>
Date: Tue, 15 May 2018 17:18:40 -0700
Subject: [PATCH 122/195] Update trainer api (#10674)
---
python/paddle/fluid/inferencer.py | 20 +++--
.../fit_a_line/test_fit_a_line.py | 20 ++---
.../test_recognize_digits_conv.py | 73 +++++++++----------
.../test_recognize_digits_mlp.py | 72 +++++++++---------
.../word2vec/no_test_word2vec_new_api.py | 20 +++--
python/paddle/fluid/trainer.py | 17 +----
6 files changed, 103 insertions(+), 119 deletions(-)
diff --git a/python/paddle/fluid/inferencer.py b/python/paddle/fluid/inferencer.py
index 1b8b9c0762..56c008d1af 100644
--- a/python/paddle/fluid/inferencer.py
+++ b/python/paddle/fluid/inferencer.py
@@ -13,29 +13,35 @@
# limitations under the License.
import core
-import framework
+
import executor
+import framework
import io
+import unique_name
from trainer import check_and_get_place
__all__ = ['Inferencer', ]
class Inferencer(object):
- def __init__(self, param_path, place=None):
+ def __init__(self, infer_func, param_path, place=None):
"""
- :param param_path: the path where the inference model is saved by fluid.io.save_inference_model
+ :param infer_func: a function that will return predict Variable
+ :param param_path: the path where the inference model is saved by fluid.io.save_params
:param place: place to do the inference
"""
self.param_path = param_path
self.scope = core.Scope()
+ self.inference_program = framework.Program()
+ with framework.program_guard(self.inference_program):
+ with unique_name.guard():
+ self.predict_var = infer_func()
+
self.exe = executor.Executor(check_and_get_place(place))
with executor.scope_guard(self.scope):
# load params from param_path into scope
- [self.inference_program, _,
- self.fetch_targets] = io.load_inference_model(
- executor=self.exe, dirname=param_path)
+ io.load_params(self.exe, param_path, self.inference_program)
def infer(self, inputs, return_numpy=True):
"""
@@ -51,7 +57,7 @@ class Inferencer(object):
with executor.scope_guard(self.scope):
results = self.exe.run(self.inference_program,
feed=inputs,
- fetch_list=self.fetch_targets,
+ fetch_list=[self.predict_var],
return_numpy=return_numpy)
return results
diff --git a/python/paddle/fluid/tests/book/high-level-api/fit_a_line/test_fit_a_line.py b/python/paddle/fluid/tests/book/high-level-api/fit_a_line/test_fit_a_line.py
index 8c9bbb52d7..fbcf2a282f 100644
--- a/python/paddle/fluid/tests/book/high-level-api/fit_a_line/test_fit_a_line.py
+++ b/python/paddle/fluid/tests/book/high-level-api/fit_a_line/test_fit_a_line.py
@@ -48,12 +48,11 @@ def linear():
return avg_loss
-def train(use_cuda, save_dirname):
+def train(use_cuda, train_program, save_dirname):
place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
trainer = fluid.Trainer(
- train_func=linear,
- infer_func=inference_program,
+ train_func=train_program,
place=place,
optimizer=fluid.optimizer.SGD(learning_rate=0.001))
@@ -72,11 +71,7 @@ def train(use_cuda, save_dirname):
'''
if float(test_metrics[0]) < 20.0:
if save_dirname is not None:
- # NOT clear yet
- # fluid.io.save_inference_model(save_dirname, ['x'], [y_predict])
- # trainer.save_params(save_dirname)
- # https://github.com/PaddlePaddle/Paddle/pull/10445
- trainer.save_inference_model(save_dirname)
+ trainer.save_params(save_dirname)
return
trainer.train(
@@ -87,12 +82,13 @@ def train(use_cuda, save_dirname):
# infer
-def infer(use_cuda, save_dirname=None):
+def infer(use_cuda, inference_program, save_dirname=None):
if save_dirname is None:
return
place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
- inferencer = fluid.Inferencer(param_path=save_dirname, place=place)
+ inferencer = fluid.Inferencer(
+ infer_func=inference_program, param_path=save_dirname, place=place)
batch_size = 10
tensor_x = numpy.random.uniform(0, 10, [batch_size, 13]).astype("float32")
@@ -108,8 +104,8 @@ def main(use_cuda):
# Directory for saving the trained model
save_dirname = "fit_a_line.inference.model"
- train(use_cuda, save_dirname)
- infer(use_cuda, save_dirname)
+ train(use_cuda, linear, save_dirname)
+ infer(use_cuda, inference_program, save_dirname)
class TestFitALine(unittest.TestCase):
diff --git a/python/paddle/fluid/tests/book/high-level-api/recognize_digits/test_recognize_digits_conv.py b/python/paddle/fluid/tests/book/high-level-api/recognize_digits/test_recognize_digits_conv.py
index 1f91f471f2..420e6e6e42 100644
--- a/python/paddle/fluid/tests/book/high-level-api/recognize_digits/test_recognize_digits_conv.py
+++ b/python/paddle/fluid/tests/book/high-level-api/recognize_digits/test_recognize_digits_conv.py
@@ -53,48 +53,40 @@ def train_program():
predict = inference_program()
cost = fluid.layers.cross_entropy(input=predict, label=label)
avg_cost = fluid.layers.mean(cost)
- # acc = fluid.layers.accuracy(input=predict, label=label)
- # return avg_cost, acc
- return avg_cost
+ acc = fluid.layers.accuracy(input=predict, label=label)
+ return [avg_cost, acc]
-def train(use_cuda, save_dirname):
+def train(use_cuda, train_program, save_dirname):
place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
optimizer = fluid.optimizer.Adam(learning_rate=0.001)
trainer = fluid.Trainer(
- train_func=train_program,
- infer_func=inference_program,
- place=place,
- optimizer=optimizer)
+ train_func=train_program, place=place, optimizer=optimizer)
def event_handler(event):
if isinstance(event, fluid.EndEpochEvent):
- # if (event.epoch + 1) % 10 == 0:
- # trainer.save_params(save_dirname)
- trainer.save_inference_model(save_dirname)
-
- # TODO: Uncomment this part once we are sure that .train is working
- # test_reader = paddle.batch(
- # paddle.dataset.mnist.test(), batch_size=BATCH_SIZE)
- # test_metrics = trainer.test(reader=test_reader)
- # avg_cost_set = test_metrics[0]
- # acc_set = test_metrics[1]
- #
- # # get test acc and loss
- # acc = numpy.array(acc_set).mean()
- # avg_cost = numpy.array(avg_cost_set).mean()
- #
- # print("avg_cost: %s" % avg_cost)
- # print("acc : %s" % acc)
- #
- # if float(acc) > 0.2: # Smaller value to increase CI speed
- # trainer.save_params(save_dirname)
- # else:
- # print('BatchID {0}, Test Loss {1:0.2}, Acc {2:0.2}'.format(
- # event.epoch + 1, float(avg_cost), float(acc)))
- # if math.isnan(float(avg_cost)):
- # sys.exit("got NaN loss, training failed.")
+ test_reader = paddle.batch(
+ paddle.dataset.mnist.test(), batch_size=BATCH_SIZE)
+ test_metrics = trainer.test(
+ reader=test_reader, feed_order=['img', 'label'])
+ avg_cost_set = test_metrics[0]
+ acc_set = test_metrics[1]
+
+ # get test acc and loss
+ acc = numpy.array(acc_set).mean()
+ avg_cost = numpy.array(avg_cost_set).mean()
+
+ print("avg_cost: %s" % avg_cost)
+ print("acc : %s" % acc)
+
+ if float(acc) > 0.2: # Smaller value to increase CI speed
+ trainer.save_params(save_dirname)
+ else:
+ print('BatchID {0}, Test Loss {1:0.2}, Acc {2:0.2}'.format(
+ event.epoch + 1, float(avg_cost), float(acc)))
+ if math.isnan(float(avg_cost)):
+ sys.exit("got NaN loss, training failed.")
train_reader = paddle.batch(
paddle.reader.shuffle(
@@ -108,10 +100,11 @@ def train(use_cuda, save_dirname):
feed_order=['img', 'label'])
-def infer(use_cuda, save_dirname=None):
+def infer(use_cuda, inference_program, save_dirname=None):
place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
- inferencer = fluid.Inferencer(param_path=save_dirname, place=place)
+ inferencer = fluid.Inferencer(
+ infer_func=inference_program, param_path=save_dirname, place=place)
batch_size = 1
tensor_img = numpy.random.uniform(-1.0, 1.0,
@@ -126,8 +119,14 @@ def main(use_cuda):
save_dirname = "recognize_digits_conv.inference.model"
# call train() with is_local argument to run distributed train
- train(use_cuda=use_cuda, save_dirname=save_dirname)
- infer(use_cuda=use_cuda, save_dirname=save_dirname)
+ train(
+ use_cuda=use_cuda,
+ train_program=train_program,
+ save_dirname=save_dirname)
+ infer(
+ use_cuda=use_cuda,
+ inference_program=inference_program,
+ save_dirname=save_dirname)
if __name__ == '__main__':
diff --git a/python/paddle/fluid/tests/book/high-level-api/recognize_digits/test_recognize_digits_mlp.py b/python/paddle/fluid/tests/book/high-level-api/recognize_digits/test_recognize_digits_mlp.py
index f072d70abd..9427a772f5 100644
--- a/python/paddle/fluid/tests/book/high-level-api/recognize_digits/test_recognize_digits_mlp.py
+++ b/python/paddle/fluid/tests/book/high-level-api/recognize_digits/test_recognize_digits_mlp.py
@@ -40,47 +40,40 @@ def train_program():
predict = inference_program()
cost = fluid.layers.cross_entropy(input=predict, label=label)
avg_cost = fluid.layers.mean(cost)
- # acc = fluid.layers.accuracy(input=predict, label=label)
- # return avg_cost, acc
- return avg_cost
+ acc = fluid.layers.accuracy(input=predict, label=label)
+ return [avg_cost, acc]
-def train(use_cuda, save_dirname):
+def train(use_cuda, train_program, save_dirname):
place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
optimizer = fluid.optimizer.Adam(learning_rate=0.001)
trainer = fluid.Trainer(
- train_func=train_program,
- infer_func=inference_program,
- place=place,
- optimizer=optimizer)
+ train_func=train_program, place=place, optimizer=optimizer)
def event_handler(event):
if isinstance(event, fluid.EndEpochEvent):
- # if (event.epoch + 1) % 10 == 0:
- trainer.save_inference_model(save_dirname)
-
- # TODO: Uncomment this part once we are sure that .train is working
- # test_reader = paddle.batch(
- # paddle.dataset.mnist.test(), batch_size=BATCH_SIZE)
- # test_metrics = trainer.test(reader=test_reader)
- # avg_cost_set = test_metrics[0]
- # acc_set = test_metrics[1]
- #
- # # get test acc and loss
- # acc = numpy.array(acc_set).mean()
- # avg_cost = numpy.array(avg_cost_set).mean()
- #
- # print("avg_cost: %s" % avg_cost)
- # print("acc : %s" % acc)
- #
- # if float(acc) > 0.2: # Smaller value to increase CI speed
- # trainer.save_params(save_dirname)
- # else:
- # print('BatchID {0}, Test Loss {1:0.2}, Acc {2:0.2}'.format(
- # event.epoch + 1, float(avg_cost), float(acc)))
- # if math.isnan(float(avg_cost)):
- # sys.exit("got NaN loss, training failed.")
+ test_reader = paddle.batch(
+ paddle.dataset.mnist.test(), batch_size=BATCH_SIZE)
+ test_metrics = trainer.test(
+ reader=test_reader, feed_order=['img', 'label'])
+ avg_cost_set = test_metrics[0]
+ acc_set = test_metrics[1]
+
+ # get test acc and loss
+ acc = numpy.array(acc_set).mean()
+ avg_cost = numpy.array(avg_cost_set).mean()
+
+ print("avg_cost: %s" % avg_cost)
+ print("acc : %s" % acc)
+
+ if float(acc) > 0.2: # Smaller value to increase CI speed
+ trainer.save_params(save_dirname)
+ else:
+ print('BatchID {0}, Test Loss {1:0.2}, Acc {2:0.2}'.format(
+ event.epoch + 1, float(avg_cost), float(acc)))
+ if math.isnan(float(avg_cost)):
+ sys.exit("got NaN loss, training failed.")
train_reader = paddle.batch(
paddle.reader.shuffle(
@@ -94,10 +87,11 @@ def train(use_cuda, save_dirname):
feed_order=['img', 'label'])
-def infer(use_cuda, save_dirname=None):
+def infer(use_cuda, inference_program, save_dirname=None):
place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
- inferencer = fluid.Inferencer(param_path=save_dirname, place=place)
+ inferencer = fluid.Inferencer(
+ infer_func=inference_program, param_path=save_dirname, place=place)
batch_size = 1
tensor_img = numpy.random.uniform(-1.0, 1.0,
@@ -112,8 +106,14 @@ def main(use_cuda):
save_dirname = "recognize_digits_mlp.inference.model"
# call train() with is_local argument to run distributed train
- train(use_cuda=use_cuda, save_dirname=save_dirname)
- infer(use_cuda=use_cuda, save_dirname=save_dirname)
+ train(
+ use_cuda=use_cuda,
+ train_program=train_program,
+ save_dirname=save_dirname)
+ infer(
+ use_cuda=use_cuda,
+ inference_program=inference_program,
+ save_dirname=save_dirname)
if __name__ == '__main__':
diff --git a/python/paddle/fluid/tests/book/high-level-api/word2vec/no_test_word2vec_new_api.py b/python/paddle/fluid/tests/book/high-level-api/word2vec/no_test_word2vec_new_api.py
index 00ba4acf88..4f861e5aae 100644
--- a/python/paddle/fluid/tests/book/high-level-api/word2vec/no_test_word2vec_new_api.py
+++ b/python/paddle/fluid/tests/book/high-level-api/word2vec/no_test_word2vec_new_api.py
@@ -90,7 +90,7 @@ def train_program(is_sparse):
return avg_cost
-def train(use_cuda, is_sparse, save_path):
+def train(use_cuda, train_program, save_path):
train_reader = paddle.batch(
paddle.dataset.imikolov.train(word_dict, N), BATCH_SIZE)
test_reader = paddle.batch(
@@ -105,23 +105,21 @@ def train(use_cuda, is_sparse, save_path):
print("loss= ", avg_cost)
if avg_cost < 5.0:
- trainer.save_inference_model(save_path)
+ trainer.save_params(save_path)
return
if math.isnan(avg_cost):
sys.exit("got NaN loss, training failed.")
trainer = fluid.Trainer(
- partial(train_program, is_sparse),
- partial(inference_program, is_sparse),
- fluid.optimizer.SGD(learning_rate=0.001),
- place=place)
+ train_program, fluid.optimizer.SGD(learning_rate=0.001), place=place)
trainer.train(
reader=train_reader, num_epochs=1, event_handler=event_handler)
-def infer(use_cuda, is_sparse, save_path):
+def infer(use_cuda, inference_program, save_path):
place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
- inferencer = fluid.Inferencer(param_path=save_path, place=place)
+ inferencer = fluid.Inferencer(
+ infer_func=inference_program, param_path=save_path, place=place)
lod = [0, 1]
first_word = create_random_lodtensor(lod, place, low=0, high=dict_size - 1)
@@ -144,9 +142,9 @@ def main(use_cuda, is_sparse):
if use_cuda and not fluid.core.is_compiled_with_cuda():
return
- save_path = "word2vec.inference.model"
- train(use_cuda, is_sparse, save_path)
- infer(use_cuda, is_sparse, save_path)
+ save_path = "word2vec.params"
+ train(use_cuda, partial(train_program, is_sparse), save_path)
+ infer(use_cuda, partial(inference_program, is_sparse), save_path)
if __name__ == '__main__':
diff --git a/python/paddle/fluid/trainer.py b/python/paddle/fluid/trainer.py
index 67d8be82d5..2f1e70724f 100644
--- a/python/paddle/fluid/trainer.py
+++ b/python/paddle/fluid/trainer.py
@@ -92,19 +92,13 @@ class Trainer(object):
place: The device place of this trainer.
"""
- def __init__(self,
- train_func,
- infer_func,
- optimizer,
- param_path=None,
- place=None):
+ def __init__(self, train_func, optimizer, param_path=None, place=None):
# 1. we need to generate a framework.Program by calling
# program_func. Reference: fluid.program_guard in
# test_word2vec.py
if not isinstance(optimizer, opt_module.Optimizer):
raise TypeError("The optimizer should be an instance of Optimizer")
- self.infer_func = infer_func
self.scope = core.Scope()
self.startup_program = framework.Program()
@@ -226,15 +220,6 @@ class Trainer(object):
exe = executor.Executor(self.place)
io.save_persistables(exe, dirname=param_path)
- def save_inference_model(self, model_path):
- inference_program = framework.Program()
- with framework.program_guard(inference_program):
- with unique_name.guard():
- predict_var = self.infer_func()
- predict_var = self.train_program.block(0).var(predict_var.name)
- exe = executor.Executor(self.place)
- io.save_inference_model(model_path, [], [predict_var], exe)
-
@contextlib.contextmanager
def _prog_and_scope_guard(self):
with framework.program_guard(
From 1c4bb5c83d872ab878e21e27c627f718c6f779cd Mon Sep 17 00:00:00 2001
From: Qiao Longfei <qiaolongfei@baidu.com>
Date: Wed, 16 May 2018 11:15:45 +0800
Subject: [PATCH 123/195] user need to set feed order for Trainer.train and
Trainer.test (#10679)
---
python/paddle/fluid/trainer.py | 15 +++++----------
1 file changed, 5 insertions(+), 10 deletions(-)
diff --git a/python/paddle/fluid/trainer.py b/python/paddle/fluid/trainer.py
index 2f1e70724f..c24662ac21 100644
--- a/python/paddle/fluid/trainer.py
+++ b/python/paddle/fluid/trainer.py
@@ -172,9 +172,9 @@ class Trainer(object):
def train(self,
num_epochs,
event_handler,
- reader=None,
- parallel=False,
- feed_order=None):
+ reader,
+ feed_order,
+ parallel=False):
"""
Train the model.
@@ -202,7 +202,7 @@ class Trainer(object):
self._train_by_executor(num_epochs, event_handler, reader, feed_order)
- def test(self, reader, feed_order=None):
+ def test(self, reader, feed_order):
"""
Test the model on given test data
@@ -276,12 +276,7 @@ def build_feed_var_list(program, feed_order):
if not isinstance(program, framework.Program):
raise TypeError("The 'program' should be an object of Program")
- if feed_order is None:
- feed_var_list = [
- var for var in program.global_block().vars.itervalues()
- if var.is_data
- ]
- elif isinstance(feed_order, list):
+ if isinstance(feed_order, list):
feed_var_list = [
program.global_block().var(var_name) for var_name in feed_order
]
From fd2b4b478ed6b3dffcf75b87bb90d33473e80f86 Mon Sep 17 00:00:00 2001
From: yuyang18 <reyoung@126.com>
Date: Wed, 16 May 2018 12:47:07 +0800
Subject: [PATCH 124/195] Make tensor support uint8
---
paddle/fluid/framework/data_type.cc | 1 +
paddle/fluid/framework/data_type.h | 8 +++++++-
paddle/fluid/framework/framework.proto | 1 +
paddle/fluid/framework/lod_tensor_test.cc | 17 +++++++++++++----
paddle/fluid/operators/math/math_function.cc | 4 +++-
5 files changed, 25 insertions(+), 6 deletions(-)
diff --git a/paddle/fluid/framework/data_type.cc b/paddle/fluid/framework/data_type.cc
index b9c90cb0c3..b6b93cf422 100644
--- a/paddle/fluid/framework/data_type.cc
+++ b/paddle/fluid/framework/data_type.cc
@@ -58,6 +58,7 @@ static DataTypeMap* InitDataTypeMap() {
RegType(bool, proto::VarType::BOOL);
RegType(size_t, proto::VarType::SIZE_T);
RegType(int16_t, proto::VarType::INT16);
+ RegType(uint8_t, proto::VarType::UINT8);
#undef RegType
return retv;
diff --git a/paddle/fluid/framework/data_type.h b/paddle/fluid/framework/data_type.h
index 4b9f572ec5..491413db8c 100644
--- a/paddle/fluid/framework/data_type.h
+++ b/paddle/fluid/framework/data_type.h
@@ -47,8 +47,14 @@ inline void VisitDataType(proto::VarType::Type type, Visitor visitor) {
case proto::VarType::BOOL:
visitor.template operator()<bool>();
break;
+ case proto::VarType::UINT8:
+ visitor.template operator()<uint8_t>();
+ break;
+ case proto::VarType::INT16:
+ visitor.template operator()<int16_t>();
+ break;
default:
- PADDLE_THROW("Not supported");
+ PADDLE_THROW("Not supported %d", type);
}
}
diff --git a/paddle/fluid/framework/framework.proto b/paddle/fluid/framework/framework.proto
index d2558f111f..d35125fe8c 100644
--- a/paddle/fluid/framework/framework.proto
+++ b/paddle/fluid/framework/framework.proto
@@ -103,6 +103,7 @@ message VarType {
FP64 = 6;
// Tensor<size_t> is used in C++.
SIZE_T = 19;
+ UINT8 = 20;
// Other types that may need additional descriptions
LOD_TENSOR = 7;
diff --git a/paddle/fluid/framework/lod_tensor_test.cc b/paddle/fluid/framework/lod_tensor_test.cc
index 77e5ec4c7d..2ceffc9331 100644
--- a/paddle/fluid/framework/lod_tensor_test.cc
+++ b/paddle/fluid/framework/lod_tensor_test.cc
@@ -228,11 +228,12 @@ TEST(LoD, CheckAbsLoD) {
ASSERT_FALSE(CheckAbsLoD(abs_lod0));
}
-TEST(LoDTensor, RecordIO) {
+template <typename T>
+static void TestRecordIO() {
LoDTensor tensor;
- int* tmp = tensor.mutable_data<int>(make_ddim({4, 5}), platform::CPUPlace());
+ T* tmp = tensor.mutable_data<T>(make_ddim({4, 5}), platform::CPUPlace());
for (int i = 0; i < 20; ++i) {
- tmp[i] = i;
+ tmp[i] = static_cast<T>(i);
}
std::stringstream* stream = new std::stringstream();
@@ -247,7 +248,7 @@ TEST(LoDTensor, RecordIO) {
auto assert_tensor_ok = [](const LoDTensor& tensor) {
for (int i = 0; i < 20; ++i) {
- ASSERT_EQ(tensor.data<int>()[i], i);
+ ASSERT_EQ(tensor.data<T>()[i], static_cast<T>(i));
}
};
@@ -265,5 +266,13 @@ TEST(LoDTensor, RecordIO) {
}
}
+TEST(LoDTensor, RecordIO) {
+ TestRecordIO<int>();
+ TestRecordIO<int16_t>();
+ TestRecordIO<uint8_t>();
+ TestRecordIO<float>();
+ TestRecordIO<double>();
+}
+
} // namespace framework
} // namespace paddle
diff --git a/paddle/fluid/operators/math/math_function.cc b/paddle/fluid/operators/math/math_function.cc
index d62ea387cc..d39154c6f8 100644
--- a/paddle/fluid/operators/math/math_function.cc
+++ b/paddle/fluid/operators/math/math_function.cc
@@ -38,7 +38,9 @@ template struct SetConstant<platform::CPUDeviceContext, bool>;
template struct Transpose<platform::CPUDeviceContext, double, RANK>; \
template struct Transpose<platform::CPUDeviceContext, int, RANK>; \
template struct Transpose<platform::CPUDeviceContext, int64_t, RANK>; \
- template struct Transpose<platform::CPUDeviceContext, bool, RANK>;
+ template struct Transpose<platform::CPUDeviceContext, bool, RANK>; \
+ template struct Transpose<platform::CPUDeviceContext, int16_t, RANK>; \
+ template struct Transpose<platform::CPUDeviceContext, uint8_t, RANK>;
DEFINE_CPU_TRANS(1);
DEFINE_CPU_TRANS(2);
From 3b4124a7781e720eed7b27fd67733583908c4828 Mon Sep 17 00:00:00 2001
From: qiaolongfei <qiaolongfei@baidu.com>
Date: Wed, 16 May 2018 13:35:46 +0800
Subject: [PATCH 125/195] code clean
---
paddle/fluid/framework/operator.h | 1 -
1 file changed, 1 deletion(-)
diff --git a/paddle/fluid/framework/operator.h b/paddle/fluid/framework/operator.h
index a4eb6f706e..2f480e00c1 100644
--- a/paddle/fluid/framework/operator.h
+++ b/paddle/fluid/framework/operator.h
@@ -33,7 +33,6 @@ limitations under the License. */
#include "paddle/fluid/framework/tensor.h"
#include "paddle/fluid/platform/device_context.h"
#include "paddle/fluid/platform/variant.h"
-#include "paddle/utils/Error.h"
namespace paddle {
namespace framework {
From a41a94f2ee9af8abcbfcc17b87641e4af9efcac8 Mon Sep 17 00:00:00 2001
From: typhoonzero <typhoonzero1986@gmail.com>
Date: Wed, 16 May 2018 13:39:02 +0800
Subject: [PATCH 126/195] support nccl2 dist train in trainer
---
python/paddle/fluid/trainer.py | 33 +++++++++++++++++++++++++++++++++
1 file changed, 33 insertions(+)
diff --git a/python/paddle/fluid/trainer.py b/python/paddle/fluid/trainer.py
index c24662ac21..a47af7ccb2 100644
--- a/python/paddle/fluid/trainer.py
+++ b/python/paddle/fluid/trainer.py
@@ -131,7 +131,40 @@ class Trainer(object):
# load params from param_path into scope
io.load_persistables(exe, dirname=param_path)
+ def _transpile_nccl2_dist(self):
+ # PADDLE_TRAINER_IPS
+ if "PADDLE_TRAINER_IPS" not in os.environ:
+ self.nccl_id_var = None
+ else:
+ self.trainer_id = int(os.getenv("PADDLE_TRAINER_ID"))
+ port = os.getenv("PADDLE_PSERVER_PORT")
+ worker_ips = os.getenv("PADDLE_TRAINER_IPS")
+ worker_endpoints = []
+ for ip in worker_ips.split(","):
+ worker_endpoints.append(':'.join([ip, port]))
+ self.num_trainers = len(worker_endpoints)
+ current_endpoint = os.getenv("POD_IP") + ":" + port
+ worker_endpoints.remove(current_endpoint)
+ # TODO(wuyi): use self.nccl_id_var, self.num_trainers and self.trainer_id
+ # in ParallelExecutor to start
+ # distributed training using NCCL2
+ self.nccl_id_var = self.startup_program.global_block().create_var(
+ name="NCCLID", persistable=True, type=core.VarDesc.VarType.RAW)
+ self.startup_program.global_block().append_op(
+ type="gen_nccl_id",
+ inputs={},
+ outputs={"NCCLID": self.nccl_id_var},
+ attrs={
+ "endpoint": current_endpoint,
+ "endpoint_list": worker_endpoints,
+ "trainer_id": self.trainer_id
+ })
+
def _dist_transpile_if_necessary(self, optimize_ops, params_grads):
+ self._transpile_nccl2_dist()
+ if self.nccl_id_var != None:
+ return
+
if "PADDLE_TRAINING_ROLE" not in os.environ:
return
From 6c87e343738159c1c3adbfc463ca71451cb0ce5d Mon Sep 17 00:00:00 2001
From: "Yang Yang(Tony)" <yangyang62@baidu.com>
Date: Tue, 15 May 2018 23:02:54 -0700
Subject: [PATCH 127/195] move test_network_with_dtype out of test_all_ops
(#10675)
---
python/paddle/fluid/tests/unittests/CMakeLists.txt | 2 ++
1 file changed, 2 insertions(+)
diff --git a/python/paddle/fluid/tests/unittests/CMakeLists.txt b/python/paddle/fluid/tests/unittests/CMakeLists.txt
index d9190408e1..496acc5791 100644
--- a/python/paddle/fluid/tests/unittests/CMakeLists.txt
+++ b/python/paddle/fluid/tests/unittests/CMakeLists.txt
@@ -66,6 +66,7 @@ list(REMOVE_ITEM TEST_OPS test_fetch_var)
list(REMOVE_ITEM TEST_OPS test_parallel_op)
list(REMOVE_ITEM TEST_OPS test_dynrnn_static_input)
list(REMOVE_ITEM TEST_OPS test_dist_train)
+list(REMOVE_ITEM TEST_OPS test_network_with_dtype)
# tests that can be bundled together in one python process for speed.
if(WITH_FAST_BUNDLE_TEST)
@@ -83,6 +84,7 @@ py_test_modules(test_parallel_executor MODULES test_parallel_executor)
py_test_modules(test_warpctc_op MODULES test_warpctc_op ENVS FLAGS_warpctc_dir=${WARPCTC_LIB_DIR})
py_test_modules(test_train_dyn_rnn MODULES test_dyn_rnn)
py_test_modules(test_mul_op MODULES test_mul_op)
+py_test_modules(test_network_with_dtype MODULES test_network_with_dtype)
# tests that need to be run in separate process.
py_test_modules(test_multihead_attention MODULES test_multihead_attention)
From 11a88147588152d98c8c6f2c01fbbf209579c2bb Mon Sep 17 00:00:00 2001
From: qiaolongfei <qiaolongfei@baidu.com>
Date: Wed, 16 May 2018 14:42:41 +0800
Subject: [PATCH 128/195] add pybind.h to inference lib for static link
---
cmake/inference_lib.cmake | 6 ++++++
1 file changed, 6 insertions(+)
diff --git a/cmake/inference_lib.cmake b/cmake/inference_lib.cmake
index 06a7ae5682..4d67be20a7 100644
--- a/cmake/inference_lib.cmake
+++ b/cmake/inference_lib.cmake
@@ -148,4 +148,10 @@ copy(string_lib
DSTS ${dst_dir}/${module} ${dst_dir}/${module}/tinyformat
)
+set(module "pybind")
+copy(pybind_lib
+ SRCS ${src_dir}/${module}/pybind.h
+ DSTS ${dst_dir}/${module}
+)
+
add_custom_target(inference_lib_dist DEPENDS ${inference_lib_dist_dep})
From ed812bdbe87ae3ccd93847c6cb6fbd6fa232bd30 Mon Sep 17 00:00:00 2001
From: kolinwei <331911734@qq.com>
Date: Wed, 16 May 2018 15:22:56 +0800
Subject: [PATCH 129/195] benchmark script support multi card train
---
benchmark/fluid/mnist.py | 12 ++++++------
benchmark/fluid/resnet.py | 10 ++++++----
benchmark/fluid/vgg.py | 10 ++++++----
3 files changed, 18 insertions(+), 14 deletions(-)
diff --git a/benchmark/fluid/mnist.py b/benchmark/fluid/mnist.py
index 1e2185dfac..3574c1c0e9 100644
--- a/benchmark/fluid/mnist.py
+++ b/benchmark/fluid/mnist.py
@@ -159,6 +159,7 @@ def run_benchmark(model, args):
paddle.dataset.mnist.train(), batch_size=args.batch_size)
accuracy = fluid.metrics.Accuracy()
+ train_exe = fluid.ParallelExecutor(use_cuda=True, loss_name=avg_cost.name)
iters, num_samples, start_time = 0, 0, time.time()
for pass_id in range(args.pass_num):
accuracy.reset()
@@ -175,17 +176,16 @@ def run_benchmark(model, args):
y_data = np.array(map(lambda x: x[1], data)).astype("int64")
y_data = y_data.reshape([len(y_data), 1])
- outs = exe.run(
- fluid.default_main_program(),
+ outs = train_exe.run(
feed={"pixel": img_data,
"label": y_data},
- fetch_list=[avg_cost, batch_acc, batch_size_tensor]
+ fetch_list=[avg_cost.name, batch_acc.name, batch_size_tensor.name]
) # The accuracy is the accumulation of batches, but not the current batch.
- accuracy.update(value=outs[1], weight=outs[2])
+ accuracy.update(value=np.array(np.mean(outs[1])), weight=np.mean(np.array(outs[2])))
iters += 1
num_samples += len(y_data)
- loss = np.array(outs[0])
- acc = np.array(outs[1])
+ loss = np.mean(np.array(outs[0]))
+ acc = np.mean(np.array(outs[1]))
train_losses.append(loss)
train_accs.append(acc)
print("Pass: %d, Iter: %d, Loss: %f, Accuracy: %f" %
diff --git a/benchmark/fluid/resnet.py b/benchmark/fluid/resnet.py
index 831fa2c019..5f60f806f7 100644
--- a/benchmark/fluid/resnet.py
+++ b/benchmark/fluid/resnet.py
@@ -241,6 +241,7 @@ def run_benchmark(model, args):
exe = fluid.Executor(place)
exe.run(fluid.default_startup_program())
accuracy = fluid.average.WeightedAverage()
+ train_exe = fluid.ParallelExecutor(use_cuda=True, loss_name=avg_cost.name)
if args.use_fake_data:
data = train_reader().next()
image = np.array(map(lambda x: x[0].reshape(dshape), data)).astype(
@@ -264,14 +265,15 @@ def run_benchmark(model, args):
data)).astype('float32')
label = np.array(map(lambda x: x[1], data)).astype('int64')
label = label.reshape([-1, 1])
- loss, acc, weight = exe.run(
- fluid.default_main_program(),
+ loss, acc, weight = train_exe.run(
feed={'data': image,
'label': label},
- fetch_list=[avg_cost, batch_acc, batch_size_tensor])
+ fetch_list=[avg_cost.name, batch_acc.name, batch_size_tensor.name])
iters += 1
num_samples += len(label)
- accuracy.add(value=acc, weight=weight)
+ accuracy.add(value=np.array(np.mean(acc)), weight=np.mean(weight))
+ loss = np.mean(np.array(loss))
+ acc = np.mean(np.array(acc))
train_losses.append(loss)
train_accs.append(acc)
print("Pass: %d, Iter: %d, Loss: %f, Accuracy: %f" %
diff --git a/benchmark/fluid/vgg.py b/benchmark/fluid/vgg.py
index 53e34e0cbd..261446e7e9 100644
--- a/benchmark/fluid/vgg.py
+++ b/benchmark/fluid/vgg.py
@@ -169,6 +169,7 @@ def main():
iters, num_samples, start_time = 0, 0, time.time()
accuracy = fluid.average.WeightedAverage()
+ train_exe = fluid.ParallelExecutor(use_cuda=True, loss_name=avg_cost.name)
for pass_id in range(args.pass_num):
accuracy.reset()
train_accs = []
@@ -184,14 +185,15 @@ def main():
y_data = np.array(map(lambda x: x[1], data)).astype("int64")
y_data = y_data.reshape([-1, 1])
- loss, acc, weight = exe.run(
- fluid.default_main_program(),
+ loss, acc, weight = train_exe.run(
feed={"pixel": img_data,
"label": y_data},
- fetch_list=[avg_cost, batch_acc, batch_size_tensor])
- accuracy.add(value=acc, weight=weight)
+ fetch_list=[avg_cost.name, batch_acc.name, batch_size_tensor.name])
+ accuracy.add(value=np.array(np.mean(acc)), weight=np.mean(weight))
iters += 1
num_samples += len(y_data)
+ loss = np.mean(np.array(loss))
+ acc = np.mean(np.array(acc))
print(
"Pass = %d, Iter = %d, Loss = %f, Accuracy = %f" %
(pass_id, iters, loss, acc)
From ff24f789cbef9a54c90a55827a69091371cddec6 Mon Sep 17 00:00:00 2001
From: qiaolongfei <qiaolongfei@baidu.com>
Date: Wed, 16 May 2018 15:35:05 +0800
Subject: [PATCH 130/195] update pybind.h source dir
---
CMakeLists.txt | 2 ++
cmake/inference_lib.cmake | 2 +-
2 files changed, 3 insertions(+), 1 deletion(-)
diff --git a/CMakeLists.txt b/CMakeLists.txt
index 030bd19b3f..6d87031314 100644
--- a/CMakeLists.txt
+++ b/CMakeLists.txt
@@ -216,6 +216,8 @@ endif(WITH_GOLANG)
set(PADDLE_PYTHON_BUILD_DIR "${CMAKE_CURRENT_BINARY_DIR}/python/build")
+message(STATUS "CMAKE_CURRENT_BINARY_DIR: ${CMAKE_CURRENT_BINARY_DIR}")
+
set(CMAKE_CXX_FLAGS_RELWITHDEBINFO "-O3 -g -DNDEBUG")
set(CMAKE_C_FLAGS_RELWITHDEBINFO "-O3 -g -DNDEBUG")
diff --git a/cmake/inference_lib.cmake b/cmake/inference_lib.cmake
index 4d67be20a7..807a48a41f 100644
--- a/cmake/inference_lib.cmake
+++ b/cmake/inference_lib.cmake
@@ -150,7 +150,7 @@ copy(string_lib
set(module "pybind")
copy(pybind_lib
- SRCS ${src_dir}/${module}/pybind.h
+ SRCS ${CMAKE_CURRENT_BINARY_DIR}/paddle/fluid/${module}/pybind.h
DSTS ${dst_dir}/${module}
)
From 1d69b1ffe37c2356710c63e611931afa026ecfd2 Mon Sep 17 00:00:00 2001
From: kolinwei <331911734@qq.com>
Date: Wed, 16 May 2018 16:06:33 +0800
Subject: [PATCH 131/195] change some code style
---
benchmark/fluid/mnist.py | 8 ++++++--
benchmark/fluid/resnet.py | 4 +++-
2 files changed, 9 insertions(+), 3 deletions(-)
diff --git a/benchmark/fluid/mnist.py b/benchmark/fluid/mnist.py
index 3574c1c0e9..1cb4314fb2 100644
--- a/benchmark/fluid/mnist.py
+++ b/benchmark/fluid/mnist.py
@@ -179,9 +179,13 @@ def run_benchmark(model, args):
outs = train_exe.run(
feed={"pixel": img_data,
"label": y_data},
- fetch_list=[avg_cost.name, batch_acc.name, batch_size_tensor.name]
+ fetch_list=[
+ avg_cost.name, batch_acc.name, batch_size_tensor.name
+ ]
) # The accuracy is the accumulation of batches, but not the current batch.
- accuracy.update(value=np.array(np.mean(outs[1])), weight=np.mean(np.array(outs[2])))
+ accuracy.update(
+ value=np.array(np.mean(outs[1])),
+ weight=np.mean(np.array(outs[2])))
iters += 1
num_samples += len(y_data)
loss = np.mean(np.array(outs[0]))
diff --git a/benchmark/fluid/resnet.py b/benchmark/fluid/resnet.py
index 5f60f806f7..0fd7258a80 100644
--- a/benchmark/fluid/resnet.py
+++ b/benchmark/fluid/resnet.py
@@ -268,7 +268,9 @@ def run_benchmark(model, args):
loss, acc, weight = train_exe.run(
feed={'data': image,
'label': label},
- fetch_list=[avg_cost.name, batch_acc.name, batch_size_tensor.name])
+ fetch_list=[
+ avg_cost.name, batch_acc.name, batch_size_tensor.name
+ ])
iters += 1
num_samples += len(label)
accuracy.add(value=np.array(np.mean(acc)), weight=np.mean(weight))
From ed748dae66d7094a2b619732fc334926ed44edac Mon Sep 17 00:00:00 2001
From: dzhwinter <dongzhihong01@baidu.com>
Date: Wed, 16 May 2018 16:22:57 +0800
Subject: [PATCH 132/195] "fix dtype test in ci" (#10667)
* "fix ci"
* "fix network config"
* "rerun ci"
---
.../unittests/test_network_with_dtype.py | 35 ++++++++-----------
1 file changed, 15 insertions(+), 20 deletions(-)
diff --git a/python/paddle/fluid/tests/unittests/test_network_with_dtype.py b/python/paddle/fluid/tests/unittests/test_network_with_dtype.py
index fe8aceb3ae..d4835dd184 100644
--- a/python/paddle/fluid/tests/unittests/test_network_with_dtype.py
+++ b/python/paddle/fluid/tests/unittests/test_network_with_dtype.py
@@ -24,33 +24,30 @@ BATCH_SIZE = 20
class TestNetWithDtype(unittest.TestCase):
- def set_network(self):
+ def setUp(self):
self.dtype = "float64"
self.init_dtype()
- main = fluid.Program()
- with fluid.program_guard(main):
- self.x = fluid.layers.data(name='x', shape=[13], dtype=self.dtype)
- self.y = fluid.layers.data(name='y', shape=[1], dtype=self.dtype)
- y_predict = fluid.layers.fc(input=self.x, size=1, act=None)
- cost = fluid.layers.square_error_cost(input=y_predict, label=self.y)
+ def run_net_on_place(self, place):
+ main = fluid.Program()
+ startup = fluid.Program()
+ with fluid.program_guard(main, startup):
+ x = fluid.layers.data(name='x', shape=[13], dtype=self.dtype)
+ y = fluid.layers.data(name='y', shape=[1], dtype=self.dtype)
+ y_predict = fluid.layers.fc(input=x, size=1, act=None)
+ cost = fluid.layers.square_error_cost(input=y_predict, label=y)
avg_cost = fluid.layers.mean(cost)
- self.program = main
- self.fetch_list = [avg_cost]
+ sgd_optimizer = fluid.optimizer.SGD(learning_rate=0.001)
+ sgd_optimizer.minimize(avg_cost)
- sgd_optimizer = fluid.optimizer.SGD(learning_rate=0.001)
- sgd_optimizer.minimize(avg_cost)
-
- def run_net_on_place(self, place):
+ fetch_list = [avg_cost]
train_reader = paddle.batch(
paddle.dataset.uci_housing.train(), batch_size=BATCH_SIZE)
- feeder = fluid.DataFeeder(place=place, feed_list=[self.x, self.y])
+ feeder = fluid.DataFeeder(place=place, feed_list=[x, y])
exe = fluid.Executor(place)
- exe.run(fluid.default_startup_program())
+ exe.run(startup)
for data in train_reader():
- exe.run(self.program,
- feed=feeder.feed(data),
- fetch_list=self.fetch_list)
+ exe.run(main, feed=feeder.feed(data), fetch_list=fetch_list)
# the main program is runable, the datatype is fully supported
break
@@ -58,14 +55,12 @@ class TestNetWithDtype(unittest.TestCase):
pass
def test_cpu(self):
- self.set_network()
place = fluid.CPUPlace()
self.run_net_on_place(place)
def test_gpu(self):
if not core.is_compiled_with_cuda():
return
- self.set_network()
place = fluid.CUDAPlace(0)
self.run_net_on_place(place)
From 3c2fe94c694664055b6122e3f7ef78276b761ad3 Mon Sep 17 00:00:00 2001
From: qiaolongfei <qiaolongfei@baidu.com>
Date: Wed, 16 May 2018 16:54:26 +0800
Subject: [PATCH 133/195] clean code
---
CMakeLists.txt | 2 --
1 file changed, 2 deletions(-)
diff --git a/CMakeLists.txt b/CMakeLists.txt
index 6d87031314..030bd19b3f 100644
--- a/CMakeLists.txt
+++ b/CMakeLists.txt
@@ -216,8 +216,6 @@ endif(WITH_GOLANG)
set(PADDLE_PYTHON_BUILD_DIR "${CMAKE_CURRENT_BINARY_DIR}/python/build")
-message(STATUS "CMAKE_CURRENT_BINARY_DIR: ${CMAKE_CURRENT_BINARY_DIR}")
-
set(CMAKE_CXX_FLAGS_RELWITHDEBINFO "-O3 -g -DNDEBUG")
set(CMAKE_C_FLAGS_RELWITHDEBINFO "-O3 -g -DNDEBUG")
From 113548801f05c01e1e16962fa09a9446a52c73f5 Mon Sep 17 00:00:00 2001
From: kolinwei <331911734@qq.com>
Date: Wed, 16 May 2018 16:55:29 +0800
Subject: [PATCH 134/195] change some code style
---
benchmark/fluid/mnist.py | 4 ++--
benchmark/fluid/vgg.py | 4 +++-
2 files changed, 5 insertions(+), 3 deletions(-)
diff --git a/benchmark/fluid/mnist.py b/benchmark/fluid/mnist.py
index 1cb4314fb2..8d51d4aa60 100644
--- a/benchmark/fluid/mnist.py
+++ b/benchmark/fluid/mnist.py
@@ -184,8 +184,8 @@ def run_benchmark(model, args):
]
) # The accuracy is the accumulation of batches, but not the current batch.
accuracy.update(
- value=np.array(np.mean(outs[1])),
- weight=np.mean(np.array(outs[2])))
+ value=np.array(np.mean(outs[1])),
+ weight=np.mean(np.array(outs[2])))
iters += 1
num_samples += len(y_data)
loss = np.mean(np.array(outs[0]))
diff --git a/benchmark/fluid/vgg.py b/benchmark/fluid/vgg.py
index 261446e7e9..2a9566a45c 100644
--- a/benchmark/fluid/vgg.py
+++ b/benchmark/fluid/vgg.py
@@ -188,7 +188,9 @@ def main():
loss, acc, weight = train_exe.run(
feed={"pixel": img_data,
"label": y_data},
- fetch_list=[avg_cost.name, batch_acc.name, batch_size_tensor.name])
+ fetch_list=[
+ avg_cost.name, batch_acc.name, batch_size_tensor.name
+ ])
accuracy.add(value=np.array(np.mean(acc)), weight=np.mean(weight))
iters += 1
num_samples += len(y_data)
From fe93cce387561a0b997276be5626d23bdea4a270 Mon Sep 17 00:00:00 2001
From: baiyfbupt <baiyfbupt@gmail.com>
Date: Wed, 16 May 2018 08:58:04 +0000
Subject: [PATCH 135/195] fix roi_pool op bug
---
paddle/fluid/operators/roi_pool_op.cu | 18 ++++++++++++------
1 file changed, 12 insertions(+), 6 deletions(-)
diff --git a/paddle/fluid/operators/roi_pool_op.cu b/paddle/fluid/operators/roi_pool_op.cu
index f905d690f9..265dbb3a80 100644
--- a/paddle/fluid/operators/roi_pool_op.cu
+++ b/paddle/fluid/operators/roi_pool_op.cu
@@ -52,13 +52,19 @@ __global__ void GPUROIPoolForward(
int roi_width = max(roi_end_w - roi_start_w + 1, 1);
int roi_height = max(roi_end_h - roi_start_h + 1, 1);
- T bin_size_h = static_cast<T>(roi_height) / static_cast<T>(pooled_height);
- T bin_size_w = static_cast<T>(roi_width) / static_cast<T>(pooled_width);
- int hstart = static_cast<int>(floor(static_cast<T>(ph) * bin_size_h));
- int wstart = static_cast<int>(floor(static_cast<T>(pw) * bin_size_w));
- int hend = static_cast<int>(ceil(static_cast<T>(ph + 1) * bin_size_h));
- int wend = static_cast<int>(ceil(static_cast<T>(pw + 1) * bin_size_w));
+ int hstart =
+ static_cast<int>(floor(static_cast<T>(ph) * static_cast<T>(roi_height) /
+ static_cast<T>(pooled_height)));
+ int wstart =
+ static_cast<int>(floor(static_cast<T>(pw) * static_cast<T>(roi_width) /
+ static_cast<T>(pooled_width)));
+ int hend = static_cast<int>(ceil(static_cast<T>(ph + 1) *
+ static_cast<T>(roi_height) /
+ static_cast<T>(pooled_height)));
+ int wend = static_cast<int>(ceil(static_cast<T>(pw + 1) *
+ static_cast<T>(roi_width) /
+ static_cast<T>(pooled_width)));
hstart = min(max(hstart + roi_start_h, 0), height);
hend = min(max(hend + roi_start_h, 0), height);
From 4473effba246f59024a8c180b5db034218810aff Mon Sep 17 00:00:00 2001
From: Yancey <yanxu05@baidu.com>
Date: Wed, 16 May 2018 17:11:03 +0800
Subject: [PATCH 136/195] fix build capi failed (#10694)
* fix build capi
* update by comment
---
paddle/CMakeLists.txt | 2 +-
paddle/scripts/paddle_build.sh | 1 +
2 files changed, 2 insertions(+), 1 deletion(-)
diff --git a/paddle/CMakeLists.txt b/paddle/CMakeLists.txt
index 8b1ca5e165..d722eec189 100644
--- a/paddle/CMakeLists.txt
+++ b/paddle/CMakeLists.txt
@@ -24,6 +24,6 @@ if(NOT WITH_FLUID_ONLY)
endif()
add_subdirectory(testing)
-if(NOT MOBILE_INFERENCE AND NOT RPI)
+if(NOT MOBILE_INFERENCE AND NOT RPI AND NOT WITH_C_API)
add_subdirectory(fluid)
endif()
diff --git a/paddle/scripts/paddle_build.sh b/paddle/scripts/paddle_build.sh
index 5bef232cd8..cb0624eac4 100755
--- a/paddle/scripts/paddle_build.sh
+++ b/paddle/scripts/paddle_build.sh
@@ -504,6 +504,7 @@ function main() {
;;
capi)
cmake_gen ${PYTHON_ABI:-""}
+ build
gen_capi_package
;;
fluid_inference_lib)
From a85d79cdcb1463c57afd5a80304dce005918eb23 Mon Sep 17 00:00:00 2001
From: kolinwei <331911734@qq.com>
Date: Wed, 16 May 2018 18:39:18 +0800
Subject: [PATCH 137/195] change some code style
---
benchmark/fluid/mnist.py | 4 ++--
1 file changed, 2 insertions(+), 2 deletions(-)
diff --git a/benchmark/fluid/mnist.py b/benchmark/fluid/mnist.py
index 8d51d4aa60..1cb4314fb2 100644
--- a/benchmark/fluid/mnist.py
+++ b/benchmark/fluid/mnist.py
@@ -184,8 +184,8 @@ def run_benchmark(model, args):
]
) # The accuracy is the accumulation of batches, but not the current batch.
accuracy.update(
- value=np.array(np.mean(outs[1])),
- weight=np.mean(np.array(outs[2])))
+ value=np.array(np.mean(outs[1])),
+ weight=np.mean(np.array(outs[2])))
iters += 1
num_samples += len(y_data)
loss = np.mean(np.array(outs[0]))
From 269a62a2b5df26904c5bf74f109a28e3c46908f5 Mon Sep 17 00:00:00 2001
From: qiaolongfei <qiaolongfei@baidu.com>
Date: Wed, 16 May 2018 18:56:14 +0800
Subject: [PATCH 138/195] add mkldnn to paddle lib
---
cmake/inference_lib.cmake | 8 ++++++++
1 file changed, 8 insertions(+)
diff --git a/cmake/inference_lib.cmake b/cmake/inference_lib.cmake
index 06a7ae5682..8b7266823d 100644
--- a/cmake/inference_lib.cmake
+++ b/cmake/inference_lib.cmake
@@ -98,6 +98,14 @@ elseif (WITH_MKLML)
)
endif()
+if(WITH_MKLDNN)
+ set(dst_dir "${CMAKE_INSTALL_PREFIX}/third_party/install/")
+ copy(mkldnn_lib
+ SRCS ${MKLDNN_INSTALL_DIR}
+ DSTS ${dst_dir}
+ )
+endif()
+
if(NOT MOBILE_INFERENCE AND NOT RPI)
set(dst_dir "${CMAKE_INSTALL_PREFIX}/third_party/install/snappy")
copy(snappy_lib
From 07536903d08dc0b01cc4f871d03b55ae82012f9a Mon Sep 17 00:00:00 2001
From: kolinwei <331911734@qq.com>
Date: Wed, 16 May 2018 19:08:04 +0800
Subject: [PATCH 139/195] change some code style
---
benchmark/fluid/mnist.py | 4 ++--
1 file changed, 2 insertions(+), 2 deletions(-)
diff --git a/benchmark/fluid/mnist.py b/benchmark/fluid/mnist.py
index 1cb4314fb2..8d51d4aa60 100644
--- a/benchmark/fluid/mnist.py
+++ b/benchmark/fluid/mnist.py
@@ -184,8 +184,8 @@ def run_benchmark(model, args):
]
) # The accuracy is the accumulation of batches, but not the current batch.
accuracy.update(
- value=np.array(np.mean(outs[1])),
- weight=np.mean(np.array(outs[2])))
+ value=np.array(np.mean(outs[1])),
+ weight=np.mean(np.array(outs[2])))
iters += 1
num_samples += len(y_data)
loss = np.mean(np.array(outs[0]))
From 1ee9fea3518d75ca9e668df2d8a1af6dd18d3827 Mon Sep 17 00:00:00 2001
From: kolinwei <331911734@qq.com>
Date: Wed, 16 May 2018 20:14:06 +0800
Subject: [PATCH 140/195] change some code style
---
benchmark/fluid/mnist.py | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/benchmark/fluid/mnist.py b/benchmark/fluid/mnist.py
index 8d51d4aa60..400200c474 100644
--- a/benchmark/fluid/mnist.py
+++ b/benchmark/fluid/mnist.py
@@ -184,7 +184,7 @@ def run_benchmark(model, args):
]
) # The accuracy is the accumulation of batches, but not the current batch.
accuracy.update(
- value=np.array(np.mean(outs[1])),
+ value=np.array(np.mean(outs[1])),
weight=np.mean(np.array(outs[2])))
iters += 1
num_samples += len(y_data)
From ddd3c15174286b8401049d857aed13517a65eafd Mon Sep 17 00:00:00 2001
From: baiyfbupt <baiyfbupt@gmail.com>
Date: Wed, 16 May 2018 17:10:34 +0000
Subject: [PATCH 141/195] bug fix
---
paddle/fluid/operators/roi_pool_op.cu | 24 ++++++++++++------------
1 file changed, 12 insertions(+), 12 deletions(-)
diff --git a/paddle/fluid/operators/roi_pool_op.cu b/paddle/fluid/operators/roi_pool_op.cu
index 265dbb3a80..a699d21542 100644
--- a/paddle/fluid/operators/roi_pool_op.cu
+++ b/paddle/fluid/operators/roi_pool_op.cu
@@ -53,18 +53,18 @@ __global__ void GPUROIPoolForward(
int roi_width = max(roi_end_w - roi_start_w + 1, 1);
int roi_height = max(roi_end_h - roi_start_h + 1, 1);
- int hstart =
- static_cast<int>(floor(static_cast<T>(ph) * static_cast<T>(roi_height) /
- static_cast<T>(pooled_height)));
- int wstart =
- static_cast<int>(floor(static_cast<T>(pw) * static_cast<T>(roi_width) /
- static_cast<T>(pooled_width)));
- int hend = static_cast<int>(ceil(static_cast<T>(ph + 1) *
- static_cast<T>(roi_height) /
- static_cast<T>(pooled_height)));
- int wend = static_cast<int>(ceil(static_cast<T>(pw + 1) *
- static_cast<T>(roi_width) /
- static_cast<T>(pooled_width)));
+ int hstart = static_cast<int>(floor(static_cast<double>(ph) *
+ static_cast<double>(roi_height) /
+ static_cast<double>(pooled_height)));
+ int wstart = static_cast<int>(floor(static_cast<double>(pw) *
+ static_cast<double>(roi_width) /
+ static_cast<double>(pooled_width)));
+ int hend = static_cast<int>(ceil(static_cast<double>(ph + 1) *
+ static_cast<double>(roi_height) /
+ static_cast<double>(pooled_height)));
+ int wend = static_cast<int>(ceil(static_cast<double>(pw + 1) *
+ static_cast<double>(roi_width) /
+ static_cast<double>(pooled_width)));
hstart = min(max(hstart + roi_start_h, 0), height);
hend = min(max(hend + roi_start_h, 0), height);
From d73f2bd6bd37282c3b8e281a9343870dfc23e05f Mon Sep 17 00:00:00 2001
From: Kexin Zhao <zhaokexin01@baidu.com>
Date: Tue, 15 May 2018 15:58:40 -0700
Subject: [PATCH 142/195] fix data_feeder lod bug
---
python/paddle/fluid/data_feeder.py | 4 +-
python/paddle/fluid/tests/test_data_feeder.py | 61 ++++++++++++++++---
2 files changed, 56 insertions(+), 9 deletions(-)
diff --git a/python/paddle/fluid/data_feeder.py b/python/paddle/fluid/data_feeder.py
index 0051b69847..a44e078d0c 100644
--- a/python/paddle/fluid/data_feeder.py
+++ b/python/paddle/fluid/data_feeder.py
@@ -54,9 +54,9 @@ class DataToLoDTensorConverter(object):
self.data.append(data)
else:
cur_lod_len = len(data)
- lod[-1].append(lod[-1][-1] + cur_lod_len)
+ lod[0].append(lod[0][-1] + cur_lod_len)
for each_data in data:
- self._feed_impl_(each_data, lod[:-1], lod_level - 1)
+ self._feed_impl_(each_data, lod[1:], lod_level - 1)
def done(self):
arr = numpy.array(self.data, dtype=self.dtype).reshape(self.shape)
diff --git a/python/paddle/fluid/tests/test_data_feeder.py b/python/paddle/fluid/tests/test_data_feeder.py
index 861dd3174a..ce3ba3ebc5 100644
--- a/python/paddle/fluid/tests/test_data_feeder.py
+++ b/python/paddle/fluid/tests/test_data_feeder.py
@@ -13,15 +13,62 @@
# limitations under the License.
import paddle.fluid as fluid
+import unittest
-def test_converter():
- img = fluid.layers.data(name='image', shape=[1, 28, 28])
- label = fluid.layers.data(name='label', shape=[1], dtype='int64')
- feeder = fluid.DataFeeder([img, label], fluid.CPUPlace())
- result = feeder.feed([[[0] * 784, [9]], [[1] * 784, [1]]])
- print(result)
+class TestDataFeeder(unittest.TestCase):
+ def test_lod_level_0_converter(self):
+ img = fluid.layers.data(name='image', shape=[1, 28, 28])
+ label = fluid.layers.data(name='label', shape=[1], dtype='int64')
+ feeder = fluid.DataFeeder([img, label], fluid.CPUPlace())
+ result = feeder.feed([([0] * 784, [9]), ([1] * 784, [1])])
+ print(result)
+
+ self.assertEqual(result['image'].shape(), [2, 1, 28, 28])
+ self.assertEqual(result['label'].shape(), [2, 1])
+ self.assertEqual(result['image'].lod(), [])
+ self.assertEqual(result['label'].lod(), [])
+
+ def test_lod_level_1_converter(self):
+ # lod_level = 1
+ # each sentence has a different number of words
+ sentences = fluid.layers.data(
+ name='sentences', shape=[1], dtype='int64', lod_level=1)
+ label = fluid.layers.data(name='label', shape=[1], dtype='int64')
+ feeder = fluid.DataFeeder([sentences, label], fluid.CPUPlace())
+
+ # lod = [[0, 3, 5, 9]]
+ # data = [[1, 2, 3], [4, 5], [6, 7, 8, 9]]
+ # label = [1] * len(data)
+ result = feeder.feed(
+ [([1, 2, 3], [1]), ([4, 5], [1]), ([6, 7, 8, 9], [1])])
+ print(result)
+
+ self.assertEqual(result['sentences'].shape(), [9, 1])
+ self.assertEqual(result['label'].shape(), [3, 1])
+ self.assertEqual(result['sentences'].lod(), [[0, 3, 5, 9]])
+ self.assertEqual(result['label'].lod(), [])
+
+ def test_lod_level_2_converter(self):
+ # lod_level = 2
+ # paragraphs -> sentences -> words
+ paragraphs = fluid.layers.data(
+ name='paragraphs', shape=[1], dtype='int64', lod_level=2)
+ label = fluid.layers.data(name='label', shape=[1], dtype='int64')
+ feeder = fluid.DataFeeder([paragraphs, label], fluid.CPUPlace())
+
+ # lod = [[0, 2, 3], [0, 3, 5, 9]]
+ # data = [[[1, 2, 3], [4, 5]], [[6, 7, 8, 9]]]
+ # label = [1] * len(data)
+ result = feeder.feed(
+ [([[1, 2, 3], [4, 5]], [1]), ([[6, 7, 8, 9]], [1])])
+ print(result)
+
+ self.assertEqual(result['paragraphs'].shape(), [9, 1])
+ self.assertEqual(result['label'].shape(), [2, 1])
+ self.assertEqual(result['paragraphs'].lod(), [[0, 2, 3], [0, 3, 5, 9]])
+ self.assertEqual(result['label'].lod(), [])
if __name__ == '__main__':
- test_converter()
+ unittest.main()
From 14248a64d7016850ae0bd51752b95aaf1dac295c Mon Sep 17 00:00:00 2001
From: Yu Yang <yuyang18@baidu.com>
Date: Thu, 17 May 2018 02:37:20 +0800
Subject: [PATCH 143/195] Fix hang when input is duplicated (#10709)
---
paddle/fluid/framework/details/op_handle_base.h | 8 ++++++++
.../framework/details/threaded_ssa_graph_executor.cc | 2 +-
2 files changed, 9 insertions(+), 1 deletion(-)
diff --git a/paddle/fluid/framework/details/op_handle_base.h b/paddle/fluid/framework/details/op_handle_base.h
index fe1735d05d..8f94206a87 100644
--- a/paddle/fluid/framework/details/op_handle_base.h
+++ b/paddle/fluid/framework/details/op_handle_base.h
@@ -70,6 +70,14 @@ class OpHandleBase {
const std::vector<VarHandleBase *> &Inputs() const { return inputs_; }
+ size_t NoDupInputSize() const {
+ std::unordered_set<VarHandleBase *> res;
+ for (auto *var : inputs_) {
+ res.emplace(var);
+ }
+ return res.size();
+ }
+
const std::vector<VarHandleBase *> &Outputs() const { return outputs_; }
protected:
diff --git a/paddle/fluid/framework/details/threaded_ssa_graph_executor.cc b/paddle/fluid/framework/details/threaded_ssa_graph_executor.cc
index ef263d82c5..815f739371 100644
--- a/paddle/fluid/framework/details/threaded_ssa_graph_executor.cc
+++ b/paddle/fluid/framework/details/threaded_ssa_graph_executor.cc
@@ -174,7 +174,7 @@ void ThreadedSSAGraphExecutor::InsertFetchOps(
void ThreadedSSAGraphExecutor::InsertPendingOp(
std::unordered_map<OpHandleBase *, size_t> *pending_ops,
OpHandleBase *op_instance) const {
- pending_ops->insert({op_instance, op_instance->Inputs().size()});
+ pending_ops->insert({op_instance, op_instance->NoDupInputSize()});
}
void ThreadedSSAGraphExecutor::InsertPendingVar(
From b67ce353fae31a352bfe0642925139f87aa2d858 Mon Sep 17 00:00:00 2001
From: "Yang Yang(Tony)" <yangyang62@baidu.com>
Date: Wed, 16 May 2018 14:02:29 -0700
Subject: [PATCH 144/195] speed up test label semantic roles (#10718)
---
.../tests/book/test_label_semantic_roles.py | 27 +++++--------------
1 file changed, 6 insertions(+), 21 deletions(-)
diff --git a/python/paddle/fluid/tests/book/test_label_semantic_roles.py b/python/paddle/fluid/tests/book/test_label_semantic_roles.py
index 09793760e5..f1ee5dfd99 100644
--- a/python/paddle/fluid/tests/book/test_label_semantic_roles.py
+++ b/python/paddle/fluid/tests/book/test_label_semantic_roles.py
@@ -182,12 +182,6 @@ def train(use_cuda, save_dirname=None, is_local=True):
crf_decode = fluid.layers.crf_decoding(
input=feature_out, param_attr=fluid.ParamAttr(name='crfw'))
- chunk_evaluator = fluid.evaluator.ChunkEvaluator(
- input=crf_decode,
- label=target,
- chunk_scheme="IOB",
- num_chunk_types=int(math.ceil((label_dict_len - 1) / 2.0)))
-
train_data = paddle.batch(
paddle.reader.shuffle(
paddle.dataset.conll05.test(), buf_size=8192),
@@ -203,7 +197,6 @@ def train(use_cuda, save_dirname=None, is_local=True):
def train_loop(main_program):
exe.run(fluid.default_startup_program())
-
embedding_param = fluid.global_scope().find_var(
embedding_name).get_tensor()
embedding_param.set(
@@ -213,27 +206,19 @@ def train(use_cuda, save_dirname=None, is_local=True):
start_time = time.time()
batch_id = 0
for pass_id in xrange(PASS_NUM):
- chunk_evaluator.reset(exe)
for data in train_data():
- cost, precision, recall, f1_score = exe.run(
- main_program,
- feed=feeder.feed(data),
- fetch_list=[avg_cost] + chunk_evaluator.metrics)
- pass_precision, pass_recall, pass_f1_score = chunk_evaluator.eval(
- exe)
+ cost = exe.run(main_program,
+ feed=feeder.feed(data),
+ fetch_list=[avg_cost])
+ cost = cost[0]
if batch_id % 10 == 0:
- print("avg_cost:" + str(cost) + " precision:" + str(
- precision) + " recall:" + str(recall) + " f1_score:" +
- str(f1_score) + " pass_precision:" + str(
- pass_precision) + " pass_recall:" + str(
- pass_recall) + " pass_f1_score:" + str(
- pass_f1_score))
+ print("avg_cost:" + str(cost))
if batch_id != 0:
print("second per batch: " + str((time.time(
) - start_time) / batch_id))
# Set the threshold low to speed up the CI test
- if float(pass_precision) > 0.01:
+ if float(cost) < 60.0:
if save_dirname is not None:
# TODO(liuyiqun): Change the target to crf_decode
fluid.io.save_inference_model(save_dirname, [
From eec1ac8638e4f5d447cb99276df6ec4c816d88c6 Mon Sep 17 00:00:00 2001
From: Kexin Zhao <zhaokexin01@baidu.com>
Date: Wed, 16 May 2018 16:46:30 -0700
Subject: [PATCH 145/195] fix warning
---
paddle/fluid/inference/tensorrt/convert/op_converter.h | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/paddle/fluid/inference/tensorrt/convert/op_converter.h b/paddle/fluid/inference/tensorrt/convert/op_converter.h
index abc9ebf472..1cd3ed9a00 100644
--- a/paddle/fluid/inference/tensorrt/convert/op_converter.h
+++ b/paddle/fluid/inference/tensorrt/convert/op_converter.h
@@ -49,7 +49,7 @@ class OpConverter {
// convert fluid block to tensorrt network
void ConvertBlock(const framework::proto::BlockDesc& block,
TensorRTEngine* engine) {
- for (size_t i = 0; i < block.ops_size(); i++) {
+ for (int i = 0; i < block.ops_size(); i++) {
const auto& op = block.ops(i);
OpConverter::Run(op, engine);
}
From dd6742ff85498611b148a567f9ee52ed75802270 Mon Sep 17 00:00:00 2001
From: Lei Wang <bestwanglei@gmail.com>
Date: Wed, 16 May 2018 17:17:51 -0700
Subject: [PATCH 146/195] Scripts: generate dockerfile after each build.
(#10719)
---
paddle/scripts/paddle_build.sh | 1 +
1 file changed, 1 insertion(+)
diff --git a/paddle/scripts/paddle_build.sh b/paddle/scripts/paddle_build.sh
index cb0624eac4..928b95b4f5 100755
--- a/paddle/scripts/paddle_build.sh
+++ b/paddle/scripts/paddle_build.sh
@@ -480,6 +480,7 @@ function main() {
build)
cmake_gen ${PYTHON_ABI:-""}
build
+ gen_dockerfile
;;
build_android)
build_android
From 32a15ed90c17a4865cf0d0e070b8ba09f307ebd6 Mon Sep 17 00:00:00 2001
From: Lei Wang <bestwanglei@gmail.com>
Date: Wed, 16 May 2018 17:38:33 -0700
Subject: [PATCH 147/195] Doc: fix missing parenthesis. (#10726)
---
doc/fluid/design/concepts/functions_operators_layers.md | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/doc/fluid/design/concepts/functions_operators_layers.md b/doc/fluid/design/concepts/functions_operators_layers.md
index 30bc488a18..1f86b99e51 100644
--- a/doc/fluid/design/concepts/functions_operators_layers.md
+++ b/doc/fluid/design/concepts/functions_operators_layers.md
@@ -40,7 +40,7 @@ template <typename T>
class FCOp : public OperatorBase {
public:
void Run(...) {
- add(mul(Input<T>("X"), Input<T>("W")), Input<T>("b");
+ add(mul(Input<T>("X"), Input<T>("W")), Input<T>("b"));
}
};
REGISTER_OP(FCOp, "fc");
From 3e34c9798a201df38c335d201442554f2c405a2d Mon Sep 17 00:00:00 2001
From: zhanghaichao <zhanghaichao@baidu.com>
Date: Wed, 16 May 2018 16:58:37 -0700
Subject: [PATCH 148/195] improved the documentation for the sequence_pool
function
---
python/paddle/fluid/layers/nn.py | 22 +++++++++++++---------
1 file changed, 13 insertions(+), 9 deletions(-)
diff --git a/python/paddle/fluid/layers/nn.py b/python/paddle/fluid/layers/nn.py
index 1786be22fd..914434ab1b 100644
--- a/python/paddle/fluid/layers/nn.py
+++ b/python/paddle/fluid/layers/nn.py
@@ -1329,6 +1329,8 @@ def sequence_pool(input, pool_type):
sqrt : out.data = [2.82, 6.93, 4.24], where 2.82=(1+3)/sqrt(2),
6.93=(2+4+6)/sqrt(3), 4.24=(5+1)/sqrt(2)
max : out.data = [3, 6, 5], where 3=max(1,3), 6=max(2,4,6), 5=max(5,1)
+ last : out.data = [3, 6, 1], where 3=last(1,3), 6=last(2,4,6), 1=last(5,1)
+ first : out.data = [1, 2, 5], where 1=first(1,3), 2=first(2,4,6), 5=first(5,1)
Args:
input(variable): The input variable which is a LoDTensor.
@@ -1348,6 +1350,8 @@ def sequence_pool(input, pool_type):
sum_x = fluid.layers.sequence_pool(input=x, pool_type='sum')
sqrt_x = fluid.layers.sequence_pool(input=x, pool_type='sqrt')
max_x = fluid.layers.sequence_pool(input=x, pool_type='max')
+ last_x = fluid.layers.sequence_pool(input=x, pool_type='last')
+ first_x = fluid.layers.sequence_pool(input=x, pool_type='first')
"""
helper = LayerHelper('sequence_pool', **locals())
dtype = helper.input_dtype()
@@ -3769,13 +3773,13 @@ def label_smooth(label,
def roi_pool(input, rois, pooled_height=1, pooled_width=1, spatial_scale=1.0):
"""
- Region of interest pooling (also known as RoI pooling) is to perform
+ Region of interest pooling (also known as RoI pooling) is to perform
is to perform max pooling on inputs of nonuniform sizes to obtain
fixed-size feature maps (e.g. 7*7).
- The operator has three steps:
- 1. Dividing each region proposal into equal-sized sections with
- the pooled_width and pooled_height
- 2. Finding the largest value in each section
+ The operator has three steps:
+ 1. Dividing each region proposal into equal-sized sections with
+ the pooled_width and pooled_height
+ 2. Finding the largest value in each section
3. Copying these max values to the output buffer
Args:
@@ -3783,8 +3787,8 @@ def roi_pool(input, rois, pooled_height=1, pooled_width=1, spatial_scale=1.0):
rois (Variable): ROIs (Regions of Interest) to pool over. It should
be a 2-D one level LoTensor of shape [num_rois, 4].
The layout is [x1, y1, x2, y2], where (x1, y1)
- is the top left coordinates, and (x2, y2) is the
- bottom right coordinates. The num_rois is the
+ is the top left coordinates, and (x2, y2) is the
+ bottom right coordinates. The num_rois is the
total number of ROIs in this batch data.
pooled_height (integer): The pooled output height. Default: 1
pooled_width (integer): The pooled output width. Default: 1
@@ -3793,11 +3797,11 @@ def roi_pool(input, rois, pooled_height=1, pooled_width=1, spatial_scale=1.0):
to the scale used when pooling. Default: 1.0
Returns:
- pool_out (Variable): The output is a 4-D tensor of the shape
+ pool_out (Variable): The output is a 4-D tensor of the shape
(num_rois, channels, pooled_h, pooled_w).
Examples:
- pool_out = fluid.layers.roi_pool(input=x, rois=rois, 7, 7, 1.0)
+ pool_out = fluid.layers.roi_pool(input=x, rois=rois, 7, 7, 1.0)
"""
helper = LayerHelper('roi_pool', **locals())
dtype = helper.input_dtype()
From 1f8243b7f8dd2bd3a90d70a51d222ff83663aa47 Mon Sep 17 00:00:00 2001
From: qingqing01 <dangqingqing@baidu.com>
Date: Thu, 17 May 2018 09:14:09 +0800
Subject: [PATCH 149/195] Refine smooth L1 loss. (#10713)
---
paddle/fluid/operators/smooth_l1_loss_op.cc | 25 +++++++++++++++++++--
python/paddle/fluid/layers/nn.py | 16 ++++++-------
2 files changed, 31 insertions(+), 10 deletions(-)
diff --git a/paddle/fluid/operators/smooth_l1_loss_op.cc b/paddle/fluid/operators/smooth_l1_loss_op.cc
index c44c5f164b..622420c1c3 100644
--- a/paddle/fluid/operators/smooth_l1_loss_op.cc
+++ b/paddle/fluid/operators/smooth_l1_loss_op.cc
@@ -105,7 +105,7 @@ class SmoothL1LossGradOp : public framework::OperatorWithKernel {
using framework::OperatorWithKernel::OperatorWithKernel;
void InferShape(framework::InferShapeContext* ctx) const override {
- auto in_dims = ctx->GetInputDim("X");
+ auto in_dims = ctx->GetInputDim("Diff");
auto out_dims = ctx->GetInputDim(framework::GradVarName("Out"));
PADDLE_ENFORCE_GE(out_dims.size(), 2,
@@ -127,12 +127,33 @@ class SmoothL1LossGradOp : public framework::OperatorWithKernel {
}
};
+class SmoothL1LossGradMaker : public framework::SingleGradOpDescMaker {
+ public:
+ using framework::SingleGradOpDescMaker::SingleGradOpDescMaker;
+
+ protected:
+ std::unique_ptr<framework::OpDesc> Apply() const override {
+ auto* op = new framework::OpDesc();
+ op->SetType("smooth_l1_loss_grad");
+ op->SetInput("InsideWeight", Input("InsideWeight"));
+ op->SetInput("OutsideWeight", Input("OutsideWeight"));
+ op->SetInput("Diff", Output("Diff"));
+ op->SetInput(framework::GradVarName("Out"), OutputGrad("Out"));
+
+ op->SetAttrMap(Attrs());
+
+ op->SetOutput(framework::GradVarName("X"), InputGrad("X"));
+ op->SetOutput(framework::GradVarName("Y"), InputGrad("Y"));
+ return std::unique_ptr<framework::OpDesc>(op);
+ }
+};
+
} // namespace operators
} // namespace paddle
namespace ops = paddle::operators;
REGISTER_OPERATOR(smooth_l1_loss, ops::SmoothL1LossOp, ops::SmoothL1LossOpMaker,
- paddle::framework::DefaultGradOpDescMaker<true>);
+ ops::SmoothL1LossGradMaker);
REGISTER_OPERATOR(smooth_l1_loss_grad, ops::SmoothL1LossGradOp);
REGISTER_OP_CPU_KERNEL(
smooth_l1_loss,
diff --git a/python/paddle/fluid/layers/nn.py b/python/paddle/fluid/layers/nn.py
index 1786be22fd..93c5e6ba96 100644
--- a/python/paddle/fluid/layers/nn.py
+++ b/python/paddle/fluid/layers/nn.py
@@ -3263,35 +3263,35 @@ def smooth_l1(x, y, inside_weight=None, outside_weight=None, sigma=None):
"""
**Smooth L1 Loss Operator. **
- This operator computes the smooth l1 loss for X and Y.
+ This operator computes the smooth L1 loss for X and Y.
The operator takes the first dimension of X and Y as batch size.
- For each instance, it computes the smooth l1 loss element by element first
+ For each instance, it computes the smooth L1 loss element by element first
and then sums all the losses. So the shape of Out is [batch_size, 1].
Args:
x (Variable): A tensor with rank at least 2. The input value of smooth
- l1 loss op with shape [batch_size, dim1, ..., dimN].
+ L1 loss op with shape [batch_size, dim1, ..., dimN].
y (Variable): A tensor with rank at least 2. The target value of smooth
- l1 loss op with same shape as x.
+ L1 loss op with same shape as x.
inside_weight (Variable|None): A tensor with rank at least 2. This
input is optional and should have same shape with x. If provided,
the result of (x - y) will be multiplied by this tensor element by
element.
outside_weight (Variable|None): A tensor with rank at least 2. This
input is optional and should have same shape with x. If provided,
- the out smooth l1 loss will be multiplied by this tensor element
+ the out smooth L1 loss will be multiplied by this tensor element
by element.
- sigma (float|None): Hyper parameter of smooth l1 loss op. A float scalar
+ sigma (float|None): Hyper parameter of smooth L1 loss op. A float scalar
with default value 1.0.
Returns:
- Variable: A tensor with rank be 2. The output smooth l1 loss with
+ Variable: A tensor with rank be 2. The output smooth L1 loss with
shape [batch_size, 1].
Examples:
.. code-block:: python
data = fluid.layers.data(name='data', shape=[128], dtype='float32')
- label = fluid.layers.data(name='label', shape=[100], dtype='int64')
+ label = fluid.layers.data(name='label', shape=[100], dtype='float32')
fc = fluid.layers.fc(input=data, size=100)
out = fluid.layers.smooth_l1(x=fc, y=label)
"""
From 63012df4970814062ad3be6a4139a4d5f6a50bc0 Mon Sep 17 00:00:00 2001
From: Yu Yang <yuyang18@baidu.com>
Date: Thu, 17 May 2018 09:59:57 +0800
Subject: [PATCH 150/195] Switch scope/program for every test (#10702)
---
.../fluid/tests/unittests/CMakeLists.txt | 4 +-
tools/test_runner.py | 48 +++++++++++++++++++
2 files changed, 50 insertions(+), 2 deletions(-)
create mode 100644 tools/test_runner.py
diff --git a/python/paddle/fluid/tests/unittests/CMakeLists.txt b/python/paddle/fluid/tests/unittests/CMakeLists.txt
index 496acc5791..2ae9653953 100644
--- a/python/paddle/fluid/tests/unittests/CMakeLists.txt
+++ b/python/paddle/fluid/tests/unittests/CMakeLists.txt
@@ -28,11 +28,11 @@ function(py_test_modules TARGET_NAME)
if(WITH_TESTING)
set(options "")
set(oneValueArgs "")
- set(multiValueArgs MODULES DEPS ARGS ENVS)
+ set(multiValueArgs MODULES DEPS ENVS)
cmake_parse_arguments(py_test_modules "${options}" "${oneValueArgs}" "${multiValueArgs}" ${ARGN})
add_test(NAME ${TARGET_NAME}
COMMAND env PYTHONPATH=${PADDLE_BINARY_DIR}/python ${py_test_modules_ENVS}
- ${PYTHON_EXECUTABLE} -u -m unittest --verbose ${py_test_modules_MODULES} ${py_test_modules_ARGS}
+ ${PYTHON_EXECUTABLE} ${PADDLE_SOURCE_DIR}/tools/test_runner.py ${py_test_modules_MODULES}
WORKING_DIRECTORY ${CMAKE_CURRENT_BINARY_DIR})
endif()
endfunction()
diff --git a/tools/test_runner.py b/tools/test_runner.py
new file mode 100644
index 0000000000..9dc750b890
--- /dev/null
+++ b/tools/test_runner.py
@@ -0,0 +1,48 @@
+# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import unittest
+import os
+import sys
+import paddle.fluid as fluid
+import importlib
+import cStringIO
+
+
+def main():
+ sys.path.append(os.getcwd())
+ some_test_failed = False
+ for module_name in sys.argv[1:]:
+ buffer = cStringIO.StringIO()
+ main = fluid.Program()
+ startup = fluid.Program()
+ scope = fluid.core.Scope()
+ with fluid.program_guard(main, startup):
+ with fluid.scope_guard(scope):
+ with fluid.unique_name.guard():
+ test_loader = unittest.TestLoader()
+ module = importlib.import_module(module_name)
+ tests = test_loader.loadTestsFromModule(module)
+ res = unittest.TextTestRunner(stream=buffer).run(tests)
+ if not res.wasSuccessful():
+ some_test_failed = True
+ print >> sys.stderr, module_name, 'failed\n', buffer.getvalue(
+ )
+
+ if some_test_failed:
+ exit(1)
+
+
+if __name__ == '__main__':
+ main()
From fdf99bbe6f4921d0e474d3ca21f8be8d90b87627 Mon Sep 17 00:00:00 2001
From: qiaolongfei <qiaolongfei@baidu.com>
Date: Thu, 17 May 2018 10:25:26 +0800
Subject: [PATCH 151/195] follow comment
---
cmake/inference_lib.cmake | 6 +++---
1 file changed, 3 insertions(+), 3 deletions(-)
diff --git a/cmake/inference_lib.cmake b/cmake/inference_lib.cmake
index 8b7266823d..a92b856f20 100644
--- a/cmake/inference_lib.cmake
+++ b/cmake/inference_lib.cmake
@@ -99,10 +99,10 @@ elseif (WITH_MKLML)
endif()
if(WITH_MKLDNN)
- set(dst_dir "${CMAKE_INSTALL_PREFIX}/third_party/install/")
+ set(dst_dir "${CMAKE_INSTALL_PREFIX}/third_party/install/mkldnn")
copy(mkldnn_lib
- SRCS ${MKLDNN_INSTALL_DIR}
- DSTS ${dst_dir}
+ SRCS ${MKLDNN_INC_DIR} ${MKLDNN_SHARED_LIB}
+ DSTS ${dst} ${dst_dir}/lib
)
endif()
From 5129bddc2ce2d273f648071b3754d08a111ec48d Mon Sep 17 00:00:00 2001
From: dzhwinter <dzhwinter@gmail.com>
Date: Wed, 16 May 2018 19:45:54 -0700
Subject: [PATCH 152/195] "change eigen mirror"
---
cmake/external/eigen.cmake | 3 ++-
1 file changed, 2 insertions(+), 1 deletion(-)
diff --git a/cmake/external/eigen.cmake b/cmake/external/eigen.cmake
index edc93c2773..e029300eee 100644
--- a/cmake/external/eigen.cmake
+++ b/cmake/external/eigen.cmake
@@ -21,11 +21,12 @@ else()
ExternalProject_Add(
extern_eigen3
${EXTERNAL_PROJECT_LOG_ARGS}
- GIT_REPOSITORY "https://github.com/RLovelett/eigen.git"
+ GIT_REPOSITORY "https://github.com/eigenteam/eigen-git-mirror"
# eigen on cuda9.1 missing header of math_funtions.hpp
# https://stackoverflow.com/questions/43113508/math-functions-hpp-not-found-when-using-cuda-with-eigen
GIT_TAG 917060c364181f33a735dc023818d5a54f60e54c
PREFIX ${EIGEN_SOURCE_DIR}
+ DOWNLOAD_NAME "eigen"
UPDATE_COMMAND ""
CONFIGURE_COMMAND ""
BUILD_COMMAND ""
From dbbeccc466bac75556399a89251c8142e8dbb377 Mon Sep 17 00:00:00 2001
From: Lei Wang <bestwanglei@gmail.com>
Date: Wed, 16 May 2018 19:59:58 -0700
Subject: [PATCH 153/195] Scripts: add a feature to run a single test. (#10678)
---
paddle/scripts/paddle_build.sh | 38 ++++++++++++++++++++++-----
paddle/scripts/paddle_docker_build.sh | 1 +
2 files changed, 33 insertions(+), 6 deletions(-)
diff --git a/paddle/scripts/paddle_build.sh b/paddle/scripts/paddle_build.sh
index 928b95b4f5..58a30ab3e5 100755
--- a/paddle/scripts/paddle_build.sh
+++ b/paddle/scripts/paddle_build.sh
@@ -20,19 +20,15 @@
#=================================================
function print_usage() {
- RED='\033[0;31m'
- BLUE='\033[0;34m'
- BOLD='\033[1m'
- NONE='\033[0m'
-
echo -e "\n${RED}Usage${NONE}:
- ${BOLD}$0${NONE} [OPTION]"
+ ${BOLD}${SCRIPT_NAME}${NONE} [OPTION]"
echo -e "\n${RED}Options${NONE}:
${BLUE}build${NONE}: run build for x86 platform
${BLUE}build_android${NONE}: run build for android platform
${BLUE}build_ios${NONE}: run build for ios platform
${BLUE}test${NONE}: run all unit tests
+ ${BLUE}single_test${NONE}: run a single unit test
${BLUE}bind_test${NONE}: parallel tests bind to different GPU
${BLUE}doc${NONE}: generate paddle documents
${BLUE}html${NONE}: convert C++ source code into HTML
@@ -45,7 +41,15 @@ function print_usage() {
}
function init() {
+ RED='\033[0;31m'
+ BLUE='\033[0;34m'
+ BOLD='\033[1m'
+ NONE='\033[0m'
+
PADDLE_ROOT="$( cd "$( dirname "${BASH_SOURCE[0]}")/../../" && pwd )"
+ if [ -z "${SCRIPT_NAME}" ]; then
+ SCRIPT_NAME=$0
+ fi
}
function cmake_gen() {
@@ -309,6 +313,25 @@ EOF
fi
}
+function single_test() {
+ TEST_NAME=$1
+ if [ -z "${TEST_NAME}" ]; then
+ echo -e "${RED}Usage:${NONE}"
+ echo -e "${BOLD}${SCRIPT_NAME}${NONE} ${BLUE}single_test${NONE} [test_name]"
+ exit 1
+ fi
+ mkdir -p ${PADDLE_ROOT}/build
+ cd ${PADDLE_ROOT}/build
+ if [ ${WITH_TESTING:-ON} == "ON" ] ; then
+ cat <<EOF
+ ========================================
+ Running ${TEST_NAME} ...
+ ========================================
+EOF
+ ctest --output-on-failure -R ${TEST_NAME}
+ fi
+}
+
function bind_test() {
# the number of process to run tests
NUM_PROC=6
@@ -491,6 +514,9 @@ function main() {
test)
run_test
;;
+ single_test)
+ single_test $2
+ ;;
bind_test)
bind_test
;;
diff --git a/paddle/scripts/paddle_docker_build.sh b/paddle/scripts/paddle_docker_build.sh
index ac32bf0292..77588b8872 100755
--- a/paddle/scripts/paddle_docker_build.sh
+++ b/paddle/scripts/paddle_docker_build.sh
@@ -63,6 +63,7 @@ EOL
${DOCKER_CMD} run -it \
--name $CONTAINER_ID \
${DOCKER_ENV} \
+ -e SCRIPT_NAME=$0 \
-v $PADDLE_ROOT:/paddle \
-v ${HOME}/.ccache:/root/.ccache \
-w /paddle \
From de3c5175c5c005086da13282d0d58bbb5046d15a Mon Sep 17 00:00:00 2001
From: qiaolongfei <qiaolongfei@baidu.com>
Date: Thu, 17 May 2018 11:10:59 +0800
Subject: [PATCH 154/195] fix typo
---
cmake/inference_lib.cmake | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/cmake/inference_lib.cmake b/cmake/inference_lib.cmake
index a92b856f20..0558393df6 100644
--- a/cmake/inference_lib.cmake
+++ b/cmake/inference_lib.cmake
@@ -102,7 +102,7 @@ if(WITH_MKLDNN)
set(dst_dir "${CMAKE_INSTALL_PREFIX}/third_party/install/mkldnn")
copy(mkldnn_lib
SRCS ${MKLDNN_INC_DIR} ${MKLDNN_SHARED_LIB}
- DSTS ${dst} ${dst_dir}/lib
+ DSTS ${dst_dir} ${dst_dir}/lib
)
endif()
From 8fd50012235b58f25cb61bb71859e6325e5c3285 Mon Sep 17 00:00:00 2001
From: Luo Tao <luotao02@baidu.com>
Date: Thu, 17 May 2018 12:23:40 +0800
Subject: [PATCH 155/195] refine mkldnn cmake with official commit id
---
cmake/external/mkldnn.cmake | 4 +-
patches/mkldnn.hpp | 4252 -----------------------------------
2 files changed, 1 insertion(+), 4255 deletions(-)
delete mode 100644 patches/mkldnn.hpp
diff --git a/cmake/external/mkldnn.cmake b/cmake/external/mkldnn.cmake
index 0332e39d14..25c07850dd 100644
--- a/cmake/external/mkldnn.cmake
+++ b/cmake/external/mkldnn.cmake
@@ -53,11 +53,9 @@ ExternalProject_Add(
${EXTERNAL_PROJECT_LOG_ARGS}
DEPENDS ${MKLDNN_DEPENDS}
GIT_REPOSITORY "https://github.com/01org/mkl-dnn.git"
- GIT_TAG "v0.14"
+ GIT_TAG "db3424ad44901513c03a1ea31ccaacdf633fbe9f"
PREFIX ${MKLDNN_SOURCES_DIR}
UPDATE_COMMAND ""
- # Patch MKLDNN to compile with gcc 4.8, the related issue is in intel/mkl-dnn#237.
- PATCH_COMMAND ${CMAKE_COMMAND} -E copy_if_different ${CMAKE_CURRENT_SOURCE_DIR}/patches/mkldnn.hpp ${MKLDNN_SOURCES_DIR}/src/extern_mkldnn/include/mkldnn.hpp
CMAKE_ARGS -DCMAKE_INSTALL_PREFIX=${MKLDNN_INSTALL_DIR}
CMAKE_ARGS -DCMAKE_BUILD_TYPE=${CMAKE_BUILD_TYPE}
CMAKE_ARGS -DMKLROOT=${MKLML_ROOT}
diff --git a/patches/mkldnn.hpp b/patches/mkldnn.hpp
deleted file mode 100644
index fe01ad8a10..0000000000
--- a/patches/mkldnn.hpp
+++ /dev/null
@@ -1,4252 +0,0 @@
-// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
-//
-// Licensed under the Apache License, Version 2.0 (the "License");
-// you may not use this file except in compliance with the License.
-// You may obtain a copy of the License at
-//
-// http://www.apache.org/licenses/LICENSE-2.0
-//
-// Unless required by applicable law or agreed to in writing, software
-// distributed under the License is distributed on an "AS IS" BASIS,
-// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-// See the License for the specific language governing permissions and
-// limitations under the License.
-
-/*******************************************************************************
-* Copyright 2016-2018 Intel Corporation
-*
-* Licensed under the Apache License, Version 2.0 (the "License");
-* you may not use this file except in compliance with the License.
-* You may obtain a copy of the License at
-*
-* http://www.apache.org/licenses/LICENSE-2.0
-*
-* Unless required by applicable law or agreed to in writing, software
-* distributed under the License is distributed on an "AS IS" BASIS,
-* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-* See the License for the specific language governing permissions and
-* limitations under the License.
-*******************************************************************************/
-
-#ifndef MKLDNN_HPP
-#define MKLDNN_HPP
-
-#ifndef DOXYGEN_SHOULD_SKIP_THIS
-#include <stdlib.h>
-#include <algorithm>
-#include <iterator>
-#include <memory>
-#include <string>
-#include <vector>
-
-#include "mkldnn.h"
-#endif
-
-namespace mkldnn {
-
-/// @addtogroup cpp_api C++ API
-/// @{
-
-/// @addtogroup cpp_api_utils Utils
-/// @{
-
-/// A class that provides the destructor for an Intel(R) MKL-DNN C handle
-template <typename T>
-class handle_traits {};
-
-/// A class for wrapping an Intel(R) MKL-DNN handle. It is used as the base
-/// class for primitive (#mkldnn_primitive_t), engine (#mkldnn_engine_t), and
-/// stream (#mkldnn_stream_t) handles. An object of the #mkldnn::handle class
-/// can be passed by value. This class enables wrapping:
-/// - Newly constructed handles.
-/// @n In this case, the constructed handle uses reference counting provided
-/// by @p std::shared_ptr with a proper deleter function specified through
-/// the @p handle_traits class.
-/// - Pre-existing handles returned by the Intel(R) MKL-DNN C API (for
-/// example, through #mkldnn_primitive_get_output()).
-/// @n In this case, an Intel(R) MKL-DNN C API handle is wrapped without a
-/// deleter because it is assumed that the handle wrapper for the original
-/// object deletes the handle (this model is similar to @p std::weak_ptr).
-template <typename T, typename traits = handle_traits<T>>
-class handle {
-private:
- std::shared_ptr<typename std::remove_pointer<T>::type> _data;
- handle(const handle &&) = delete;
- handle &operator=(const handle &&other) = delete;
-
-protected:
- /// Constructs a C handle wrapper.
- /// @param t The C handle to wrap.
- /// @param weak A flag to specify whether to construct a weak wrapper.
- handle(T t = 0, bool weak = false) : _data(0) { reset(t, weak); }
-
- bool operator==(const T other) const { return other == _data.get(); }
- bool operator!=(const T other) const { return !(*this == other); }
-
-public:
- handle(const handle &other) : _data(other._data) {}
- handle &operator=(const handle &other) {
- _data = other._data;
- return *this;
- }
- /// Resets the value of a C handle.
- /// @param t The new value of the C handle.
- /// @param weak A flag to specify whether the wrapper should be weak.
- void reset(T t, bool weak = false) {
- auto dummy_destructor = [](T) {
- return decltype(traits::destructor(0))(0);
- };
- _data.reset(t, weak ? dummy_destructor : traits::destructor);
- }
-
- /// Returns the value of the underlying C handle.
- T get() const { return _data.get(); }
-
- bool operator==(const handle &other) const {
- return other._data.get() == _data.get();
- }
- bool operator!=(const handle &other) const { return !(*this == other); }
-};
-
-#ifndef DOXYGEN_SHOULD_SKIP_THIS
-template <>
-struct handle_traits<mkldnn_primitive_desc_t> {
- static constexpr auto destructor = &mkldnn_primitive_desc_destroy;
-};
-
-template <>
-struct handle_traits<mkldnn_primitive_t> {
- static constexpr auto destructor = &mkldnn_primitive_destroy;
-};
-#endif
-
-/// Base class for all computational primitives.
-class primitive : public handle<mkldnn_primitive_t> {
- friend struct error;
- friend struct stream;
- friend class primitive_at;
- using handle::handle;
-
-public:
- /// A proxy to C primitive kind enum
- enum class kind {
- undefined_primitive = mkldnn_undefined_primitive,
- memory = mkldnn_memory,
- view = mkldnn_view,
- reorder = mkldnn_reorder,
- concat = mkldnn_concat,
- concat_inplace = mkldnn_concat_inplace,
- sum = mkldnn_sum,
- convolution = mkldnn_convolution,
- deconvolution = mkldnn_deconvolution,
- eltwise = mkldnn_eltwise,
- relu = mkldnn_relu,
- softmax = mkldnn_softmax,
- pooling = mkldnn_pooling,
- lrn = mkldnn_lrn,
- batch_normalization = mkldnn_batch_normalization,
- inner_product = mkldnn_inner_product,
- convolution_relu = mkldnn_convolution_relu,
- rnn = mkldnn_rnn,
- };
-
- /// A wrapper structure to specify a particular output of a primitive.
- struct at {
- /// The underlying C API structure.
- mkldnn_primitive_at_t data;
- /// Constructs a wrapper specifying @p aprimitive output with index @p
- /// at.
- ///
- /// @param aprimitive The target primitive.
- /// @param at The output index.
-
- at(const primitive &aprimitive, size_t at = 0)
- : data(mkldnn_primitive_at(aprimitive.get(), at)) {}
- /// Returns the specified output.
- inline operator primitive() const;
- };
-
- /// Returns the descriptor of the underlying C API primitive
- inline const_mkldnn_primitive_desc_t get_primitive_desc() const;
- // TODO: use the C++ API wrapper structure.
-};
-
-inline mkldnn_primitive_kind_t convert_to_c(primitive::kind akind) {
- return static_cast<mkldnn_primitive_kind_t>(akind);
-}
-
-/// Intel(R) MKL-DNN exception class.
-///
-/// This class captures the status returned by the failed C API function, error
-/// message, and, optionally, handle of the primitive that caused the error.
-struct error : public std::exception {
- mkldnn_status_t status;
- std::string message;
- primitive error_primitive;
-
- /// Constructs an error instance.
- ///
- /// @param astatus The error status returned by the C API.
- /// @param amessage The error message.
- /// @param aerror_primitive (optional) A C handle of the primitive that
- /// caused the error.
-
- error(mkldnn_status_t astatus,
- std::string amessage,
- mkldnn_primitive_t aerror_primitive = 0)
- : status(astatus),
- message(amessage),
- error_primitive(aerror_primitive, true) {}
-
- /// A convenience function for wrapping calls to the C API. Checks the
- /// return status and throws an #error in case of failure.
- ///
- /// @param status The error status returned by the C API.
- /// @param message The error message.
- /// @param error_primitive (optional) A C handle of the primitive that
- /// caused the error.
-
- static void wrap_c_api(mkldnn_status_t status,
- std::string message,
- mkldnn_primitive_t *error_primitive = 0) {
- if (status != mkldnn_success) {
- if (nullptr != error_primitive)
- throw error(status, message, *error_primitive);
- else
- throw error(status, message, nullptr);
- }
- }
-};
-
-inline primitive::at::operator primitive() const {
- const_mkldnn_primitive_t output;
- error::wrap_c_api(
- mkldnn_primitive_get_output(data.primitive, data.output_index, &output),
- "could not get an output primitive");
- return primitive(const_cast<mkldnn_primitive_t>(output), true);
-}
-
-const_mkldnn_primitive_desc_t primitive::get_primitive_desc() const {
- const_mkldnn_primitive_desc_t pd;
- error::wrap_c_api(mkldnn_primitive_get_primitive_desc(get(), &pd),
- "could not get primitive descriptor by primitive");
- return pd;
-}
-/// @}
-
-/// @addtogroup cpp_api_enums Common data types and enumerations
-/// @{
-
-enum round_mode {
- round_nearest = mkldnn_round_nearest,
- round_down = mkldnn_round_down,
-};
-
-inline mkldnn_round_mode_t convert_to_c(round_mode mode) {
- return static_cast<mkldnn_round_mode_t>(mode);
-}
-
-enum padding_kind { zero = mkldnn_padding_zero };
-
-inline mkldnn_padding_kind_t convert_to_c(padding_kind kind) {
- return static_cast<mkldnn_padding_kind_t>(kind);
-}
-
-enum prop_kind {
- forward_training = mkldnn_forward_training,
- forward_scoring = mkldnn_forward_scoring,
- forward_inference = mkldnn_forward_inference,
- forward = mkldnn_forward,
- backward = mkldnn_backward,
- backward_data = mkldnn_backward_data,
- backward_weights = mkldnn_backward_weights,
- backward_bias = mkldnn_backward_bias
-};
-
-inline mkldnn_prop_kind_t convert_to_c(prop_kind kind) {
- return static_cast<mkldnn_prop_kind_t>(kind);
-}
-
-enum algorithm {
- algorithm_undef = mkldnn_alg_kind_undef,
- convolution_direct = mkldnn_convolution_direct,
- convolution_winograd = mkldnn_convolution_winograd,
- deconvolution_direct = mkldnn_deconvolution_direct,
- deconvolution_winograd = mkldnn_deconvolution_winograd,
- eltwise_relu = mkldnn_eltwise_relu,
- eltwise_tanh = mkldnn_eltwise_tanh,
- eltwise_elu = mkldnn_eltwise_elu,
- eltwise_square = mkldnn_eltwise_square,
- eltwise_abs = mkldnn_eltwise_abs,
- eltwise_sqrt = mkldnn_eltwise_sqrt,
- eltwise_linear = mkldnn_eltwise_linear,
- eltwise_bounded_relu = mkldnn_eltwise_bounded_relu,
- eltwise_soft_relu = mkldnn_eltwise_soft_relu,
- eltwise_logistic = mkldnn_eltwise_logistic,
- lrn_across_channels = mkldnn_lrn_across_channels,
- lrn_within_channel = mkldnn_lrn_within_channel,
- pooling_max = mkldnn_pooling_max,
- pooling_avg = mkldnn_pooling_avg,
- pooling_avg_include_padding = mkldnn_pooling_avg_include_padding,
- pooling_avg_exclude_padding = mkldnn_pooling_avg_exclude_padding,
- vanilla_rnn = mkldnn_vanilla_rnn,
- vanilla_lstm = mkldnn_vanilla_lstm,
- vanilla_gru = mkldnn_vanilla_gru,
-};
-
-inline mkldnn_alg_kind_t convert_to_c(algorithm aalgorithm) {
- return static_cast<mkldnn_alg_kind_t>(aalgorithm);
-}
-
-enum batch_normalization_flag {
- use_global_stats = mkldnn_use_global_stats,
- use_scale_shift = mkldnn_use_scaleshift,
- omit_stats = mkldnn_omit_stats,
- fuse_bn_relu = mkldnn_fuse_bn_relu
-};
-
-inline mkldnn_batch_normalization_flag_t convert_to_c(
- batch_normalization_flag aflag) {
- return static_cast<mkldnn_batch_normalization_flag_t>(aflag);
-}
-
-enum rnn_direction {
- unidirectional_left2right = mkldnn_unidirectional_left2right,
- unidirectional_right2left = mkldnn_unidirectional_right2left,
- unidirectional = mkldnn_unidirectional,
- bidirectional_concat = mkldnn_bidirectional_concat,
- bidirectional_sum = mkldnn_bidirectional_sum,
-};
-
-inline mkldnn_rnn_direction_t convert_to_c(rnn_direction adir) {
- return static_cast<mkldnn_rnn_direction_t>(adir);
-}
-
-enum query {
- undef = mkldnn_query_undef,
-
- eengine = mkldnn_query_engine,
- primitive_kind = mkldnn_query_primitive_kind,
-
- num_of_inputs_s32 = mkldnn_query_num_of_inputs_s32,
- num_of_outputs_s32 = mkldnn_query_num_of_outputs_s32,
-
- time_estimate_f64 = mkldnn_query_time_estimate_f64,
- memory_consumption_s64 = mkldnn_query_memory_consumption_s64,
-
- impl_info_str = mkldnn_query_impl_info_str,
-
- memory_d = mkldnn_query_memory_d,
- convolution_d = mkldnn_query_convolution_d,
- deconvolution_d = mkldnn_query_deconvolution_d,
- eltwise_d = mkldnn_query_eltwise_d,
- relu_d = mkldnn_query_relu_d,
- softmax_d = mkldnn_query_softmax_d,
- pooling_d = mkldnn_query_pooling_d,
- lrn_d = mkldnn_query_lrn_d,
- batch_normalization_d = mkldnn_query_batch_normalization_d,
- inner_product_d = mkldnn_query_inner_product_d,
- convolution_relu_d = mkldnn_query_convolution_relu_d,
- rnn_d = mkldnn_query_rnn_d,
-
- input_pd = mkldnn_query_input_pd,
- output_pd = mkldnn_query_output_pd,
- src_pd = mkldnn_query_src_pd,
- diff_src_pd = mkldnn_query_diff_src_pd,
- weights_pd = mkldnn_query_weights_pd,
- diff_weights_pd = mkldnn_query_diff_weights_pd,
- dst_pd = mkldnn_query_dst_pd,
- diff_dst_pd = mkldnn_query_diff_dst_pd,
- workspace_pd = mkldnn_query_workspace_pd,
-};
-
-inline mkldnn_query_t convert_to_c(query aquery) {
- return static_cast<mkldnn_query_t>(aquery);
-}
-
-/// @}
-
-/// @addtogroup cpp_api_attr Attributes
-/// @{
-
-#ifndef DOXYGEN_SHOULD_SKIP_THIS
-template <>
-struct handle_traits<mkldnn_post_ops_t> {
- static constexpr auto destructor = &mkldnn_post_ops_destroy;
-};
-#endif
-
-struct post_ops : public handle<mkldnn_post_ops_t> {
- post_ops() {
- mkldnn_post_ops_t result;
- error::wrap_c_api(mkldnn_post_ops_create(&result),
- "could not create post operation sequence");
- reset(result);
- }
-
- int len() const { return mkldnn_post_ops_len(get()); }
-
- primitive::kind kind(int index) const {
- error::wrap_c_api(index < len() ? mkldnn_success : mkldnn_invalid_arguments,
- "post_ops index is out of range");
- return static_cast<primitive::kind>(mkldnn_post_ops_get_kind(get(), index));
- }
-
- void append_sum(float scale = 1.) {
- error::wrap_c_api(mkldnn_post_ops_append_sum(get(), scale),
- "could not append sum");
- }
-
- void get_params_sum(int index, float &scale) const {
- error::wrap_c_api(mkldnn_post_ops_get_params_sum(get(), index, &scale),
- "could not get sum params");
- }
-
- void append_eltwise(float scale, algorithm alg, float alpha, float beta) {
- error::wrap_c_api(mkldnn_post_ops_append_eltwise(
- get(), scale, convert_to_c(alg), alpha, beta),
- "could not append eltwise");
- }
-
- void get_params_eltwise(int index,
- float &scale,
- algorithm &alg,
- float &alpha,
- float &beta) const {
- mkldnn_alg_kind_t c_alg;
- error::wrap_c_api(mkldnn_post_ops_get_params_eltwise(
- get(), index, &scale, &c_alg, &alpha, &beta),
- "could not get eltwise params");
- alg = static_cast<algorithm>(c_alg);
- }
-};
-
-#ifndef DOXYGEN_SHOULD_SKIP_THIS
-template <>
-struct handle_traits<mkldnn_primitive_attr_t> {
- static constexpr auto destructor = &mkldnn_primitive_attr_destroy;
-};
-#endif
-
-struct primitive_attr : public handle<mkldnn_primitive_attr_t> {
- primitive_attr() {
- mkldnn_primitive_attr_t result;
- error::wrap_c_api(mkldnn_primitive_attr_create(&result),
- "could not create a primitive attr");
- reset(result);
- }
-
- round_mode get_int_output_round_mode() const {
- mkldnn_round_mode_t result;
- error::wrap_c_api(
- mkldnn_primitive_attr_get_int_output_round_mode(get(), &result),
- "could not get int output round mode");
- return round_mode(result);
- }
-
- void set_int_output_round_mode(round_mode mode) {
- error::wrap_c_api(mkldnn_primitive_attr_set_int_output_round_mode(
- get(), mkldnn::convert_to_c(mode)),
- "could not set int output round mode");
- }
-
- void get_output_scales(int &mask, std::vector<float> &scales) const {
- int count, c_mask;
- const float *c_scales;
- error::wrap_c_api(mkldnn_primitive_attr_get_output_scales(
- get(), &count, &c_mask, &c_scales),
- "could not get int output scales");
- scales.resize(count);
-
- mask = c_mask;
- for (int c = 0; c < count; ++c) scales[c] = c_scales[c];
- }
-
- void set_output_scales(int mask, const std::vector<float> &scales) {
- error::wrap_c_api(mkldnn_primitive_attr_set_output_scales(
- get(), (int)scales.size(), mask, &scales[0]),
- "could not set int output scales");
- }
-
- const post_ops get_post_ops() const {
- post_ops result;
- const_mkldnn_post_ops_t c_result;
- error::wrap_c_api(mkldnn_primitive_attr_get_post_ops(get(), &c_result),
- "could not get post operation sequence");
- result.reset(const_cast<mkldnn_post_ops_t>(c_result), true);
- return result;
- }
-
- void set_post_ops(post_ops ops) {
- error::wrap_c_api(mkldnn_primitive_attr_set_post_ops(get(), ops.get()),
- "could not set post operation sequence");
- }
-};
-
-/// @}
-
-/// @addtogroup cpp_api_engine Engine
-/// @{
-
-#ifndef DOXYGEN_SHOULD_SKIP_THIS
-template <>
-struct handle_traits<mkldnn_engine_t> {
- static constexpr auto destructor = &mkldnn_engine_destroy;
-};
-#endif
-
-/// An execution engine.
-struct engine : public handle<mkldnn_engine_t> {
- friend class primitive;
- // gcc bug??? using handle::handle;
-
- /// Kinds of engines
- enum kind {
- /// An unspecified engine
- any = mkldnn_any_engine,
- /// CPU engine
- cpu = mkldnn_cpu,
- };
-
- /// Returns the number of engines of a certain kind.
- ///
- /// @param akind The kind of engines to count.
-
- static size_t get_count(kind akind) {
- return mkldnn_engine_get_count(convert_to_c(akind));
- }
-
- /// Constructs an engine.
- ///
- /// @param akind The kind of engine to construct.
- /// @param index The index of the engine. Must be less than the value
- /// returned by #get_count() for this particular kind of engine.
-
- engine(kind akind, size_t index) {
- mkldnn_engine_t aengine;
- error::wrap_c_api(
- mkldnn_engine_create(&aengine, convert_to_c(akind), index),
- "could not create an engine");
- reset(aengine);
- }
-
- explicit engine(const mkldnn_engine_t &aengine) : handle(aengine, true) {}
-
- engine(const handle<mkldnn_primitive_desc_t> &pd) {
- mkldnn_engine_t engine_q;
- error::wrap_c_api(
- mkldnn_primitive_desc_query(
- pd.get(), mkldnn::convert_to_c(eengine), 0, &engine_q),
- "could not get engine from primitive_desc");
- reset(engine_q, true);
- }
-
- template <class primitive_desc>
- static engine query(const primitive_desc &pd) {
- mkldnn_engine_t engine_q;
- error::wrap_c_api(
- mkldnn_primitive_desc_query(
- pd.get(), mkldnn::convert_to_c(eengine), 0, &engine_q),
- "could not get engine from primitive_desc");
-
- return engine(engine_q);
- }
-
-private:
- static mkldnn_engine_kind_t convert_to_c(kind akind) {
- return static_cast<mkldnn_engine_kind_t>(akind);
- }
-};
-
-/// @}
-
-/// @addtogroup cpp_api_primitives Primitives
-/// @{
-
-/// @addtogroup cpp_api_memory Memory
-/// @{
-
-/// Memory primitive that describes the data.
-struct memory : public primitive {
-private:
- std::shared_ptr<char> _handle;
-
-public:
- typedef std::vector<std::remove_extent<mkldnn_dims_t>::type> dims;
-
- template <typename T>
- static void validate_dims(std::vector<T> v) {
- if (v.size() > TENSOR_MAX_DIMS)
- throw error(mkldnn_invalid_arguments, "invalid dimensions");
- }
-
- /// Data type specification. See #mkldnn_data_type_t for a detailed
- /// description.
- enum data_type {
- data_undef = mkldnn_data_type_undef,
- f32 = mkldnn_f32,
- s32 = mkldnn_s32,
- s16 = mkldnn_s16,
- s8 = mkldnn_s8,
- u8 = mkldnn_u8,
- };
-
- /// Memory format specification. See #mkldnn_memory_format_t
- /// for a detailed description.
- enum format {
- format_undef = mkldnn_format_undef,
- any = mkldnn_any,
- blocked = mkldnn_blocked,
- x = mkldnn_x,
- nc = mkldnn_nc,
- nchw = mkldnn_nchw,
- nhwc = mkldnn_nhwc,
- chwn = mkldnn_chwn,
- nChw8c = mkldnn_nChw8c,
- nChw16c = mkldnn_nChw16c,
- ncdhw = mkldnn_ncdhw,
- ndhwc = mkldnn_ndhwc,
- nCdhw16c = mkldnn_nCdhw16c,
- oi = mkldnn_oi,
- io = mkldnn_io,
- oihw = mkldnn_oihw,
- ihwo = mkldnn_ihwo,
- hwio = mkldnn_hwio,
- oidhw = mkldnn_oidhw,
- OIdhw16i16o = mkldnn_OIdhw16i16o,
- OIdhw16o16i = mkldnn_OIdhw16o16i,
- Oidhw16o = mkldnn_Oidhw16o,
- Odhwi16o = mkldnn_Odhwi16o,
- oIhw8i = mkldnn_oIhw8i,
- oIhw16i = mkldnn_oIhw16i,
- OIhw8i8o = mkldnn_OIhw8i8o,
- OIhw16i16o = mkldnn_OIhw16i16o,
- OIhw8o8i = mkldnn_OIhw8o8i,
- OIhw16o16i = mkldnn_OIhw16o16i,
- IOhw16o16i = mkldnn_IOhw16o16i,
- OIhw8i16o2i = mkldnn_OIhw8i16o2i,
- OIhw8o16i2o = mkldnn_OIhw8o16i2o,
- OIhw4i16o4i = mkldnn_OIhw4i16o4i,
- Oihw8o = mkldnn_Oihw8o,
- Oihw16o = mkldnn_Oihw16o,
- Ohwi8o = mkldnn_Ohwi8o,
- Ohwi16o = mkldnn_Ohwi16o,
- OhIw16o4i = mkldnn_OhIw16o4i,
- goihw = mkldnn_goihw,
- hwigo = mkldnn_hwigo,
- gOIhw8i8o = mkldnn_gOIhw8i8o,
- gOIhw16i16o = mkldnn_gOIhw16i16o,
- gOIhw8i16o2i = mkldnn_gOIhw8i16o2i,
- gOIhw8o16i2o = mkldnn_gOIhw8o16i2o,
- gOIhw4i16o4i = mkldnn_gOIhw4i16o4i,
- gOihw8o = mkldnn_gOihw8o,
- gOihw16o = mkldnn_gOihw16o,
- gOhwi8o = mkldnn_gOhwi8o,
- gOhwi16o = mkldnn_gOhwi16o,
- Goihw8g = mkldnn_Goihw8g,
- Goihw16g = mkldnn_Goihw16g,
- gOIhw8o8i = mkldnn_gOIhw8o8i,
- gOIhw16o16i = mkldnn_gOIhw16o16i,
- gIOhw16o16i = mkldnn_gIOhw16o16i,
- gOhIw16o4i = mkldnn_gOhIw16o4i,
- goidhw = mkldnn_goidhw,
- gOIdhw16i16o = mkldnn_gOIdhw16i16o,
- gOIdhw16o16i = mkldnn_gOIdhw16o16i,
- gOidhw16o = mkldnn_gOidhw16o,
- gOdhwi16o = mkldnn_gOdhwi16o,
- ntc = mkldnn_ntc,
- tnc = mkldnn_tnc,
- ldsnc = mkldnn_ldsnc,
- ldigo = mkldnn_ldigo,
- ldigo_p = mkldnn_ldigo_p,
- ldgoi = mkldnn_ldgoi,
- ldgoi_p = mkldnn_ldgoi_p,
- ldgo = mkldnn_ldgo,
- wino_fmt = mkldnn_wino_fmt,
- format_last = mkldnn_format_last,
- };
-
- /// A memory descriptor.
- struct desc {
- friend struct memory;
- /// The underlying C API data structure.
- mkldnn_memory_desc_t data;
-
- /// Constructs a memory descriptor.
- ///
- /// @param adims Data dimensions
- /// @param adata_type Data precision/type.
- /// @param aformat Data layout format.
- desc(dims adims, data_type adata_type, format aformat) {
- validate_dims(adims);
- error::wrap_c_api(
- mkldnn_memory_desc_init(&data,
- (int)adims.size(),
- adims.size() == 0 ? nullptr : &adims[0],
- convert_to_c(adata_type),
- convert_to_c(aformat)),
- "could not initialize a memory descriptor");
- }
-
- /// Constructs a memory descriptor from a C API data structure.
- ///
- /// @param adata A C API #mkldnn_memory_desc_t structure.
- desc(const mkldnn_memory_desc_t &adata) : data(adata) {}
- };
-
- /// A memory primitive descriptor.
- struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
- friend struct memory;
-
- // TODO: make private
- primitive_desc() {}
-
- /// Constructs a memory primitive descriptor.
- primitive_desc(const desc &adesc, const engine &aengine) {
- mkldnn_primitive_desc_t result;
- error::wrap_c_api(mkldnn_memory_primitive_desc_create(
- &result, &adesc.data, aengine.get()),
- "could not initialize a memory primitive descriptor");
- reset(result);
- }
-
- /// Returns the memory primitive descriptor.
- memory::desc desc() {
- auto memory_d = mkldnn_primitive_desc_query_memory_d(get());
- return memory::desc(*memory_d);
- }
-
- /// Returns the number of bytes required to allocate the memory described
- /// including the padding area.
- size_t get_size() const {
- return mkldnn_memory_primitive_desc_get_size(get());
- }
-
- bool operator==(const primitive_desc &other) const {
- return mkldnn_memory_primitive_desc_equal(get(), other.get());
- }
-
- bool operator!=(const primitive_desc &other) const {
- return !operator==(other);
- }
-
- engine get_engine() { return engine::query(*this); }
- };
-
- /// Constructs a memory primitive from a generic primitive.
- ///
- /// @param aprimitive The primitive to treat as memory.
- memory(const primitive &aprimitive) : primitive(aprimitive) {}
- /// Constructs a memory primitive.
- ///
- /// @param adesc Memory primitive descriptor.
- memory(const primitive_desc &adesc) {
- mkldnn_primitive_t result;
- error::wrap_c_api(
- mkldnn_primitive_create(&result, adesc.get(), nullptr, nullptr),
- "could not create a memory primitive");
- reset(result);
- auto _malloc = [](size_t size, int alignment) {
- void *ptr;
-#ifdef _WIN32
- ptr = _aligned_malloc(size, alignment);
- int rc = ((ptr) ? 0 : errno);
-#else
- int rc = ::posix_memalign(&ptr, alignment, size);
-#endif /* _WIN32 */
- return (rc == 0) ? (char *)ptr : nullptr;
- };
- auto _free = [](char *p) {
-#ifdef _WIN32
- _aligned_free((void *)p);
-#else
- ::free((void *)p);
-#endif /* _WIN32 */
- };
- _handle.reset(_malloc(adesc.get_size(), 4096), _free);
- set_data_handle(_handle.get());
- }
-
- memory(const primitive_desc &adesc, void *ahandle) {
- mkldnn_primitive_t result;
- error::wrap_c_api(
- mkldnn_primitive_create(&result, adesc.get(), nullptr, nullptr),
- "could not create a memory primitive");
- reset(result);
- set_data_handle(ahandle);
- }
-
- /// Returns the descriptor of the memory primitive.
- primitive_desc get_primitive_desc() const {
- primitive_desc adesc;
- const_mkldnn_primitive_desc_t cdesc;
- error::wrap_c_api(
- mkldnn_primitive_get_primitive_desc(get(), &cdesc),
- "could not get primitive descriptor from a memory primitive");
- /* FIXME: no const_cast should be here */
- adesc.reset(const_cast<mkldnn_primitive_desc_t>(cdesc), true);
- return adesc;
- }
-
- /// Returns a handle of the data contained in the memory primitive. On
- /// the CPU engine, this is a pointer to the allocated memory.
- inline void *get_data_handle() const {
- void *handle;
- error::wrap_c_api(mkldnn_memory_get_data_handle(get(), &handle),
- "could not get native handle");
- return handle;
- }
-
- inline void set_data_handle(void *handle) const {
- error::wrap_c_api(mkldnn_memory_set_data_handle(get(), handle),
- "could not set native handle");
- }
-
- // Must go away or be private:
- static mkldnn_data_type_t convert_to_c(data_type adata_type) {
- return static_cast<mkldnn_data_type_t>(adata_type);
- }
- static mkldnn_memory_format_t convert_to_c(format aformat) {
- return static_cast<mkldnn_memory_format_t>(aformat);
- }
-};
-
-inline memory::desc zero_md() {
- mkldnn_memory_desc_t zero;
- zero.primitive_kind = mkldnn_memory;
- return memory::desc(zero);
-}
-
-inline memory null_memory(engine eng) {
- mkldnn::memory::desc zero = zero_md();
- return memory({zero, eng}, nullptr);
-}
-
-inline bool is_null_memory(const const_mkldnn_primitive_t &aprimitive) {
- const_mkldnn_primitive_desc_t aprimitive_pd;
- mkldnn_primitive_get_primitive_desc(aprimitive, &aprimitive_pd);
- const mkldnn_memory_desc_t *aprimitive_md =
- mkldnn_primitive_desc_query_memory_d(aprimitive_pd);
-
- return ((aprimitive_md != nullptr) && (aprimitive_md->ndims == 0));
-}
-
-inline bool operator==(mkldnn_data_type_t a, memory::data_type b) {
- return a == memory::convert_to_c(b);
-}
-inline bool operator!=(mkldnn_data_type_t a, memory::data_type b) {
- return !(a == b);
-}
-inline bool operator==(memory::data_type a, mkldnn_data_type_t b) {
- return b == a;
-}
-inline bool operator!=(memory::data_type a, mkldnn_data_type_t b) {
- return !(a == b);
-}
-
-inline bool operator==(mkldnn_memory_format_t a, memory::format b) {
- return a == memory::convert_to_c(b);
-}
-inline bool operator!=(mkldnn_memory_format_t a, memory::format b) {
- return !(a == b);
-}
-inline bool operator==(memory::format a, mkldnn_memory_format_t b) {
- return b == a;
-}
-inline bool operator!=(memory::format a, mkldnn_memory_format_t b) {
- return !(a == b);
-}
-
-/// @}
-
-/// @addtogroup cpp_api_reorder Reorder
-/// @{
-
-struct reorder : public primitive {
- struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
- primitive_desc(const memory::primitive_desc &input,
- const memory::primitive_desc &output) {
- mkldnn_primitive_desc_t result;
- error::wrap_c_api(mkldnn_reorder_primitive_desc_create(
- &result, input.get(), output.get()),
- "could not create a reorder primitive descriptor");
- reset(result);
- }
-
- primitive_desc(const memory::primitive_desc &input,
- const memory::primitive_desc &output,
- const primitive_attr &aattr) {
- mkldnn_primitive_desc_t result;
- error::wrap_c_api(mkldnn_reorder_primitive_desc_create_v2(
- &result, input.get(), output.get(), aattr.get()),
- "could not create a reorder primitive descriptor");
- reset(result);
- }
-
- engine get_engine() { return engine::query(*this); }
- };
-
- reorder(const primitive_desc &aprimitive_desc,
- const primitive::at &input,
- const memory &output) {
- mkldnn_primitive_t result;
- mkldnn_primitive_at_t inputs[] = {input.data};
- const_mkldnn_primitive_t outputs[] = {output.get()};
- error::wrap_c_api(mkldnn_primitive_create(
- &result, aprimitive_desc.get(), inputs, outputs),
- "could not create a reorder primitive");
- reset(result);
- }
-
- reorder(const primitive::at &input, const memory &output) {
- auto input_mpd = memory(input).get_primitive_desc();
- auto output_mpd = output.get_primitive_desc();
-
- auto reorder_d = primitive_desc(input_mpd, output_mpd);
-
- mkldnn_primitive_t result;
- mkldnn_primitive_at_t inputs[] = {input.data};
- const_mkldnn_primitive_t outputs[] = {output.get()};
- error::wrap_c_api(
- mkldnn_primitive_create(&result, reorder_d.get(), inputs, outputs),
- "could not create a reorder primitive");
- reset(result);
- }
-};
-
-/// @}
-
-/// @addtogroup cpp_api_view View
-/// @{
-
-struct view : public primitive {
- struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
- primitive_desc(const memory::primitive_desc &input,
- memory::dims dims,
- memory::dims offsets) {
- mkldnn_primitive_desc_t result;
-
- error::wrap_c_api(mkldnn_view_primitive_desc_create(
- &result, input.get(), &dims[0], &offsets[0]),
- "could not create a view primitive descriptor");
- reset(result);
- }
-
- memory::primitive_desc dst_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t cdesc;
- const_mkldnn_primitive_desc_t const_cdesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(dst_pd), 0);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
- "could not clone a dst primitive descriptor");
- adesc.reset(cdesc);
- return adesc;
- }
-
- engine get_engine() { return engine::query(*this); }
- };
-
- view(const primitive_desc &view_pd, primitive::at input) {
- mkldnn_primitive_t result;
- mkldnn_primitive_at_t inputs[] = {input.data};
- error::wrap_c_api(
- mkldnn_primitive_create(&result, view_pd.get(), inputs, nullptr),
- "could not create a view primitive");
- reset(result);
- }
-
- view(memory input, memory::dims dims, memory::dims offsets) {
- mkldnn_primitive_t result;
- primitive_desc view_pd(input.get_primitive_desc(), dims, offsets);
- mkldnn_primitive_at_t inputs[] = {primitive::at(input).data};
- error::wrap_c_api(
- mkldnn_primitive_create(&result, view_pd.get(), inputs, nullptr),
- "could not create a view primitive");
- reset(result);
- }
-};
-
-/// @}
-
-/// @addtogroup cpp_api_concat Concat
-/// @{
-
-struct concat : public primitive {
- struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
- std::vector<const_mkldnn_primitive_desc_t> cpp_to_c(
- std::vector<memory::primitive_desc> inputs) {
- std::vector<const_mkldnn_primitive_desc_t> c_api_inputs;
- c_api_inputs.reserve(inputs.size());
- auto convert_to_c = [](memory::primitive_desc d) { return d.get(); };
- std::transform(inputs.begin(),
- inputs.end(),
- std::back_inserter(c_api_inputs),
- convert_to_c);
- return c_api_inputs;
- }
-
- primitive_desc(const memory::desc &output,
- int concat_dimension,
- std::vector<memory::primitive_desc> inputs) {
- mkldnn_primitive_desc_t result;
-
- auto c_api_inputs = cpp_to_c(inputs);
-
- error::wrap_c_api(
- mkldnn_concat_primitive_desc_create(&result,
- &output.data,
- (int)c_api_inputs.size(),
- concat_dimension,
- &c_api_inputs[0]),
- "could not create a concat primitive descriptor");
- reset(result);
- }
-
- primitive_desc(int concat_dimension,
- std::vector<memory::primitive_desc> inputs) {
- mkldnn_primitive_desc_t result;
-
- auto c_api_inputs = cpp_to_c(inputs);
-
- error::wrap_c_api(
- mkldnn_concat_primitive_desc_create(&result,
- nullptr,
- (int)c_api_inputs.size(),
- concat_dimension,
- &c_api_inputs[0]),
- "could not create a concat primitive descriptor");
- reset(result);
- }
-
- memory::primitive_desc dst_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t cdesc;
- const_mkldnn_primitive_desc_t const_cdesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(dst_pd), 0);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
- "could not clone a dst primitive descriptor");
- adesc.reset(cdesc);
- return adesc;
- }
-
- engine get_engine() { return engine::query(*this); }
- };
-
- concat(const primitive_desc &concat_pd,
- std::vector<primitive::at> &inputs,
- const memory &output) {
- mkldnn_primitive_t result;
-
- std::vector<mkldnn_primitive_at_t> p_inputs;
- for (size_t i = 0; i < inputs.size(); i++)
- p_inputs.push_back(inputs[i].data);
- const_mkldnn_primitive_t outputs[] = {output.get()};
-
- error::wrap_c_api(mkldnn_primitive_create(
- &result, concat_pd.get(), &p_inputs[0], outputs),
- "could not create a concat primitive");
- reset(result);
- }
-};
-
-/// @}
-
-/// @addtogroup cpp_api_sum Sum
-/// @{
-
-struct sum : public primitive {
- struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
- std::vector<const_mkldnn_primitive_desc_t> cpp_to_c(
- std::vector<memory::primitive_desc> inputs) {
- std::vector<const_mkldnn_primitive_desc_t> c_api_inputs;
- c_api_inputs.reserve(inputs.size());
- auto convert_to_c = [](memory::primitive_desc d) { return d.get(); };
- std::transform(inputs.begin(),
- inputs.end(),
- std::back_inserter(c_api_inputs),
- convert_to_c);
- return c_api_inputs;
- }
-
- primitive_desc(const memory::desc &output,
- const std::vector<float> &scales,
- std::vector<memory::primitive_desc> inputs) {
- mkldnn_primitive_desc_t result;
-
- auto c_api_inputs = cpp_to_c(inputs);
-
- error::wrap_c_api(
- mkldnn_sum_primitive_desc_create(&result,
- &output.data,
- (int)c_api_inputs.size(),
- &scales[0],
- &c_api_inputs[0]),
- "could not create a sum primitive descriptor");
- reset(result);
- }
-
- primitive_desc(const std::vector<float> &scales,
- std::vector<memory::primitive_desc> inputs) {
- mkldnn_primitive_desc_t result;
-
- auto c_api_inputs = cpp_to_c(inputs);
-
- error::wrap_c_api(
- mkldnn_sum_primitive_desc_create(&result,
- nullptr,
- (int)c_api_inputs.size(),
- &scales[0],
- &c_api_inputs[0]),
- "could not create a sum primitive descriptor");
- reset(result);
- }
-
- /** @deprecated: api backwards compatibility for double scales type */
- MKLDNN_DEPRECATED
- primitive_desc(const memory::desc &output,
- std::vector<double> scale,
- std::vector<memory::primitive_desc> inputs) {
- mkldnn_primitive_desc_t result;
-
- auto c_api_inputs = cpp_to_c(inputs);
- auto scale_f = scale_to_float(scale);
-
- error::wrap_c_api(
- mkldnn_sum_primitive_desc_create(&result,
- &output.data,
- (int)c_api_inputs.size(),
- &scale_f[0],
- &c_api_inputs[0]),
- "could not create a sum primitive descriptor");
- reset(result);
- }
-
- /** @deprecated: api backwards compatibility for double scales type */
- MKLDNN_DEPRECATED
- primitive_desc(std::vector<double> scale,
- std::vector<memory::primitive_desc> inputs) {
- mkldnn_primitive_desc_t result;
-
- auto c_api_inputs = cpp_to_c(inputs);
- auto scale_f = scale_to_float(scale);
-
- error::wrap_c_api(
- mkldnn_sum_primitive_desc_create(&result,
- nullptr,
- (int)c_api_inputs.size(),
- &scale_f[0],
- &c_api_inputs[0]),
- "could not create a sum primitive descriptor");
- reset(result);
- }
-
- memory::primitive_desc dst_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t cdesc;
- const_mkldnn_primitive_desc_t const_cdesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(dst_pd), 0);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
- "could not clone a dst primitive descriptor");
- adesc.reset(cdesc);
- return adesc;
- }
-
- engine get_engine() { return engine::query(*this); }
- };
-
- sum(const primitive_desc &sum_pd,
- std::vector<primitive::at> &inputs,
- const memory &output) {
- mkldnn_primitive_t result;
-
- std::vector<mkldnn_primitive_at_t> p_inputs;
- for (size_t i = 0; i < inputs.size(); i++)
- p_inputs.push_back(inputs[i].data);
- const_mkldnn_primitive_t outputs[] = {output.get()};
-
- error::wrap_c_api(
- mkldnn_primitive_create(&result, sum_pd.get(), &p_inputs[0], outputs),
- "could not create a sum primitive");
- reset(result);
- }
-
-private:
- static std::vector<float> scale_to_float(const std::vector<double> &vd) {
- std::vector<float> vf(vd.size());
- std::transform(
- vd.begin(), vd.end(), vf.begin(), [=](double x) { return (float)x; });
- return vf;
- }
-};
-
-/// @}
-
-/// @addtogroup cpp_api_convolution Convolution
-/// @{
-
-struct convolution_forward : public primitive {
- struct desc {
- mkldnn_convolution_desc_t data;
- desc(prop_kind aprop_kind,
- algorithm aalgorithm,
- const memory::desc &src_desc,
- const memory::desc &weights_desc,
- const memory::desc &bias_desc,
- const memory::desc &dst_desc,
- const memory::dims strides,
- const memory::dims padding_l,
- const memory::dims padding_r,
- const padding_kind apadding_kind) {
- memory::validate_dims(strides);
- memory::validate_dims(padding_l);
- memory::validate_dims(padding_r);
- error::wrap_c_api(mkldnn_convolution_forward_desc_init(
- &data,
- mkldnn::convert_to_c(aprop_kind),
- convert_to_c(aalgorithm),
- &src_desc.data,
- &weights_desc.data,
- &bias_desc.data,
- &dst_desc.data,
- &strides[0],
- &padding_l[0],
- &padding_r[0],
- mkldnn::convert_to_c(apadding_kind)),
- "could not create a convolution forward descriptor");
- }
- desc(prop_kind aprop_kind,
- algorithm aalgorithm,
- const memory::desc &src_desc,
- const memory::desc &weights_desc,
- const memory::desc &dst_desc,
- const memory::dims strides,
- const memory::dims padding_l,
- const memory::dims padding_r,
- const padding_kind apadding_kind) {
- memory::validate_dims(strides);
- memory::validate_dims(padding_l);
- memory::validate_dims(padding_r);
- error::wrap_c_api(mkldnn_convolution_forward_desc_init(
- &data,
- mkldnn::convert_to_c(aprop_kind),
- convert_to_c(aalgorithm),
- &src_desc.data,
- &weights_desc.data,
- nullptr,
- &dst_desc.data,
- &strides[0],
- &padding_l[0],
- &padding_r[0],
- mkldnn::convert_to_c(apadding_kind)),
- "could not create a convolution forward descriptor");
- }
- desc(prop_kind aprop_kind,
- algorithm aalgorithm,
- const memory::desc &src_desc,
- const memory::desc &weights_desc,
- const memory::desc &bias_desc,
- const memory::desc &dst_desc,
- const memory::dims strides,
- const memory::dims dilates,
- const memory::dims padding_l,
- const memory::dims padding_r,
- const padding_kind apadding_kind) {
- memory::validate_dims(strides);
- memory::validate_dims(dilates);
- memory::validate_dims(padding_l);
- memory::validate_dims(padding_r);
- error::wrap_c_api(
- mkldnn_dilated_convolution_forward_desc_init(
- &data,
- mkldnn::convert_to_c(aprop_kind),
- convert_to_c(aalgorithm),
- &src_desc.data,
- &weights_desc.data,
- &bias_desc.data,
- &dst_desc.data,
- &strides[0],
- &dilates[0],
- &padding_l[0],
- &padding_r[0],
- mkldnn::convert_to_c(apadding_kind)),
- "could not create a dilated convolution forward descriptor");
- }
- desc(prop_kind aprop_kind,
- algorithm aalgorithm,
- const memory::desc &src_desc,
- const memory::desc &weights_desc,
- const memory::desc &dst_desc,
- const memory::dims strides,
- const memory::dims dilates,
- const memory::dims padding_l,
- const memory::dims padding_r,
- const padding_kind apadding_kind) {
- memory::validate_dims(strides);
- memory::validate_dims(dilates);
- memory::validate_dims(padding_l);
- memory::validate_dims(padding_r);
- error::wrap_c_api(
- mkldnn_dilated_convolution_forward_desc_init(
- &data,
- mkldnn::convert_to_c(aprop_kind),
- convert_to_c(aalgorithm),
- &src_desc.data,
- &weights_desc.data,
- nullptr,
- &dst_desc.data,
- &strides[0],
- &dilates[0],
- &padding_l[0],
- &padding_r[0],
- mkldnn::convert_to_c(apadding_kind)),
- "could not create a dilated convolution forward descriptor");
- }
- };
- struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
- primitive_desc(const desc &adesc, const engine &aengine) {
- mkldnn_primitive_desc_t result;
- error::wrap_c_api(
- mkldnn_primitive_desc_create(
- &result, &adesc.data, aengine.get(), nullptr),
- "could not create a convolution forward primitive descriptor");
- reset(result);
- }
-
- primitive_desc(const desc &adesc,
- const primitive_attr &aattr,
- const engine &aengine) {
- mkldnn_primitive_desc_t result;
- error::wrap_c_api(
- mkldnn_primitive_desc_create_v2(
- &result, &adesc.data, aattr.get(), aengine.get(), nullptr),
- "could not create a convolution forward primitive descriptor");
- reset(result);
- }
-
- memory::primitive_desc src_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t cdesc;
- const_mkldnn_primitive_desc_t const_cdesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(src_pd), 0);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
- "could not clone a src primititve descriptor");
- adesc.reset(cdesc);
- return adesc;
- }
-
- memory::primitive_desc weights_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t cdesc;
- const_mkldnn_primitive_desc_t const_cdesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(weights_pd), 0);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
- "could not clone a weights primitive descriptor");
- adesc.reset(cdesc);
- return adesc;
- }
-
- memory::primitive_desc bias_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t cdesc;
- const_mkldnn_primitive_desc_t const_cdesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(weights_pd), 1);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
- "could not clone a bias primitive descriptor");
- adesc.reset(cdesc);
- return adesc;
- }
-
- memory::primitive_desc dst_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t cdesc;
- const_mkldnn_primitive_desc_t const_cdesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(dst_pd), 0);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
- "could not clone a dst primitive descriptor");
- adesc.reset(cdesc);
- return adesc;
- }
-
- engine get_engine() { return engine::query(*this); }
- };
-
- convolution_forward(const primitive_desc &aprimitive_desc,
- const primitive::at &src,
- const primitive::at &weights,
- const primitive::at &bias,
- const memory &dst) {
- mkldnn_primitive_t result;
- mkldnn_primitive_at_t inputs[] = {src.data, weights.data, bias.data};
- const_mkldnn_primitive_t outputs[] = {dst.get()};
- error::wrap_c_api(mkldnn_primitive_create(
- &result, aprimitive_desc.get(), inputs, outputs),
- "could not create a convolution forward bias primitive");
- reset(result);
- }
-
- convolution_forward(const primitive_desc &aprimitive_desc,
- const primitive::at &src,
- const primitive::at &weights,
- const memory &dst) {
- mkldnn_primitive_t result;
- mkldnn_primitive_at_t inputs[] = {src.data, weights.data};
- const_mkldnn_primitive_t outputs[] = {dst.get()};
- error::wrap_c_api(mkldnn_primitive_create(
- &result, aprimitive_desc.get(), inputs, outputs),
- "could not create a convolution forward primitive");
- reset(result);
- }
-};
-
-struct convolution_backward_data : public primitive {
- struct desc {
- mkldnn_convolution_desc_t data;
- desc(algorithm aalgorithm,
- const memory::desc &diff_src_desc,
- const memory::desc &weights_desc,
- const memory::desc &diff_dst_desc,
- const memory::dims strides,
- const memory::dims padding_l,
- const memory::dims padding_r,
- const padding_kind apadding_kind) {
- memory::validate_dims(strides);
- memory::validate_dims(padding_l);
- memory::validate_dims(padding_r);
- error::wrap_c_api(
- mkldnn_convolution_backward_data_desc_init(
- &data,
- convert_to_c(aalgorithm),
- &diff_src_desc.data,
- &weights_desc.data,
- &diff_dst_desc.data,
- &strides[0],
- &padding_l[0],
- &padding_r[0],
- mkldnn::convert_to_c(apadding_kind)),
- "could not create a convolution backward data descriptor");
- }
- desc(algorithm aalgorithm,
- const memory::desc &diff_src_desc,
- const memory::desc &weights_desc,
- const memory::desc &diff_dst_desc,
- const memory::dims strides,
- const memory::dims dilates,
- const memory::dims padding_l,
- const memory::dims padding_r,
- const padding_kind apadding_kind) {
- memory::validate_dims(strides);
- memory::validate_dims(dilates);
- memory::validate_dims(padding_l);
- memory::validate_dims(padding_r);
- error::wrap_c_api(
- mkldnn_dilated_convolution_backward_data_desc_init(
- &data,
- convert_to_c(aalgorithm),
- &diff_src_desc.data,
- &weights_desc.data,
- &diff_dst_desc.data,
- &strides[0],
- &dilates[0],
- &padding_l[0],
- &padding_r[0],
- mkldnn::convert_to_c(apadding_kind)),
- "could not create a convolution backward data descriptor");
- }
- };
- struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
- primitive_desc(
- const desc &adesc,
- const engine &aengine,
- const convolution_forward::primitive_desc &hint_fwd_primitive_desc) {
- mkldnn_primitive_desc_t result;
- error::wrap_c_api(
- mkldnn_primitive_desc_create(&result,
- &adesc.data,
- aengine.get(),
- hint_fwd_primitive_desc.get()),
- "could not create a convolution backward data primitive descriptor");
- reset(result);
- }
- memory::primitive_desc diff_src_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t cdesc;
- const_mkldnn_primitive_desc_t const_cdesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(diff_src_pd), 0);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
- "could not clone a diff_src primititve descriptor");
- adesc.reset(cdesc);
- return adesc;
- }
-
- memory::primitive_desc weights_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t cdesc;
- const_mkldnn_primitive_desc_t const_cdesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(weights_pd), 0);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
- "could not clone a weights primitive descriptor");
- adesc.reset(cdesc);
- return adesc;
- }
-
- memory::primitive_desc diff_dst_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t cdesc;
- const_mkldnn_primitive_desc_t const_cdesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(diff_dst_pd), 0);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
- "could not clone a diff_dst primitive descriptor");
- adesc.reset(cdesc);
- return adesc;
- }
-
- engine get_engine() { return engine::query(*this); }
- };
-
- convolution_backward_data(const primitive_desc &aprimitive_desc,
- const primitive::at &diff_dst,
- const primitive::at &weights,
- const memory &diff_src) {
- mkldnn_primitive_t result;
- mkldnn_primitive_at_t inputs[] = {diff_dst.data, weights.data};
- const_mkldnn_primitive_t outputs[] = {diff_src.get()};
- error::wrap_c_api(mkldnn_primitive_create(
- &result, aprimitive_desc.get(), inputs, outputs),
- "could not create a convolution backward data primitive");
- reset(result);
- }
-};
-
-struct convolution_backward_weights : public primitive {
- struct desc {
- mkldnn_convolution_desc_t data;
- desc(algorithm aalgorithm,
- const memory::desc &src_desc,
- const memory::desc &diff_weights_desc,
- const memory::desc &diff_bias_desc,
- const memory::desc &diff_dst_desc,
- const memory::dims strides,
- const memory::dims padding_l,
- const memory::dims padding_r,
- const padding_kind apadding_kind) {
- memory::validate_dims(strides);
- memory::validate_dims(padding_l);
- memory::validate_dims(padding_r);
- error::wrap_c_api(
- mkldnn_convolution_backward_weights_desc_init(
- &data,
- convert_to_c(aalgorithm),
- &src_desc.data,
- &diff_weights_desc.data,
- &diff_bias_desc.data,
- &diff_dst_desc.data,
- &strides[0],
- &padding_l[0],
- &padding_r[0],
- mkldnn::convert_to_c(apadding_kind)),
- "could not create a convolution backward weights descriptor");
- }
- desc(algorithm aalgorithm,
- const memory::desc &src_desc,
- const memory::desc &diff_weights_desc,
- const memory::desc &diff_dst_desc,
- const memory::dims strides,
- const memory::dims padding_l,
- const memory::dims padding_r,
- const padding_kind apadding_kind) {
- memory::validate_dims(strides);
- memory::validate_dims(padding_l);
- memory::validate_dims(padding_r);
- error::wrap_c_api(
- mkldnn_convolution_backward_weights_desc_init(
- &data,
- convert_to_c(aalgorithm),
- &src_desc.data,
- &diff_weights_desc.data,
- nullptr,
- &diff_dst_desc.data,
- &strides[0],
- &padding_l[0],
- &padding_r[0],
- mkldnn::convert_to_c(apadding_kind)),
- "could not create a convolution backward weights descriptor");
- }
- desc(algorithm aalgorithm,
- const memory::desc &src_desc,
- const memory::desc &diff_weights_desc,
- const memory::desc &diff_bias_desc,
- const memory::desc &diff_dst_desc,
- const memory::dims strides,
- const memory::dims dilates,
- const memory::dims padding_l,
- const memory::dims padding_r,
- const padding_kind apadding_kind) {
- memory::validate_dims(strides);
- memory::validate_dims(dilates);
- memory::validate_dims(padding_l);
- memory::validate_dims(padding_r);
- error::wrap_c_api(
- mkldnn_dilated_convolution_backward_weights_desc_init(
- &data,
- convert_to_c(aalgorithm),
- &src_desc.data,
- &diff_weights_desc.data,
- &diff_bias_desc.data,
- &diff_dst_desc.data,
- &strides[0],
- &dilates[0],
- &padding_l[0],
- &padding_r[0],
- mkldnn::convert_to_c(apadding_kind)),
- "could not create a convolution backward weights descriptor");
- }
- desc(algorithm aalgorithm,
- const memory::desc &src_desc,
- const memory::desc &diff_weights_desc,
- const memory::desc &diff_dst_desc,
- const memory::dims strides,
- const memory::dims dilates,
- const memory::dims padding_l,
- const memory::dims padding_r,
- const padding_kind apadding_kind) {
- memory::validate_dims(strides);
- memory::validate_dims(dilates);
- memory::validate_dims(padding_l);
- memory::validate_dims(padding_r);
- error::wrap_c_api(
- mkldnn_dilated_convolution_backward_weights_desc_init(
- &data,
- convert_to_c(aalgorithm),
- &src_desc.data,
- &diff_weights_desc.data,
- nullptr,
- &diff_dst_desc.data,
- &strides[0],
- &dilates[0],
- &padding_l[0],
- &padding_r[0],
- mkldnn::convert_to_c(apadding_kind)),
- "could not create a convolution backward weights descriptor");
- }
- };
-
- struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
- primitive_desc(
- const desc &adesc,
- const engine &aengine,
- const convolution_forward::primitive_desc &hint_fwd_primitive_desc) {
- mkldnn_primitive_desc_t result;
- error::wrap_c_api(
- mkldnn_primitive_desc_create(&result,
- &adesc.data,
- aengine.get(),
- hint_fwd_primitive_desc.get()),
- "could not create a convolution backward weights primitive "
- "descriptor");
- reset(result);
- }
- memory::primitive_desc src_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t cdesc;
- const_mkldnn_primitive_desc_t const_cdesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(src_pd), 0);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
- "could not clone a src primititve descriptor");
- adesc.reset(cdesc);
- return adesc;
- }
-
- memory::primitive_desc diff_weights_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t cdesc;
- const_mkldnn_primitive_desc_t const_cdesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(diff_weights_pd), 0);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
- "could not clone a diff_weights primitive descriptor");
- adesc.reset(cdesc);
- return adesc;
- }
-
- memory::primitive_desc diff_bias_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t cdesc;
- const_mkldnn_primitive_desc_t const_cdesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(diff_weights_pd), 1);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
- "could not clone a diff_bias primitive descriptor");
- adesc.reset(cdesc);
- return adesc;
- }
-
- memory::primitive_desc diff_dst_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t cdesc;
- const_mkldnn_primitive_desc_t const_cdesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(diff_dst_pd), 0);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
- "could not clone a diff_dst primitive descriptor");
- adesc.reset(cdesc);
- return adesc;
- }
-
- engine get_engine() { return engine::query(*this); }
- };
-
- convolution_backward_weights(const primitive_desc &aprimitive_desc,
- const primitive::at &src,
- const primitive::at &diff_dst,
- const memory &diff_weights,
- const memory &diff_bias) {
- mkldnn_primitive_t result;
- mkldnn_primitive_at_t inputs[] = {src.data, diff_dst.data};
- const_mkldnn_primitive_t outputs[] = {diff_weights.get(), diff_bias.get()};
- error::wrap_c_api(
- mkldnn_primitive_create(
- &result, aprimitive_desc.get(), inputs, outputs),
- "could not create a convolution backward weights primitive");
- reset(result);
- }
- convolution_backward_weights(const primitive_desc &aprimitive_desc,
- const primitive::at &src,
- const primitive::at &diff_dst,
- const memory &diff_weights) {
- mkldnn_primitive_t result;
- mkldnn_primitive_at_t inputs[] = {src.data, diff_dst.data};
- const_mkldnn_primitive_t outputs[] = {diff_weights.get()};
- error::wrap_c_api(
- mkldnn_primitive_create(
- &result, aprimitive_desc.get(), inputs, outputs),
- "could not create a convolution backward weights primitive");
- reset(result);
- }
-};
-
-struct convolution_relu_forward : public primitive {
- struct desc {
- mkldnn_convolution_relu_desc_t data;
- desc(const convolution_forward::desc conv_desc,
- const float negative_slope) {
- error::wrap_c_api(
- mkldnn_convolution_relu_desc_init(
- &data, &conv_desc.data, negative_slope),
- "could not create a convolution_relu_forward descriptor");
- }
- };
-
- struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
- primitive_desc(const desc &adesc, const engine &aengine) {
- mkldnn_primitive_desc_t result;
- error::wrap_c_api(
- mkldnn_primitive_desc_create(
- &result, &adesc.data, aengine.get(), nullptr),
- "could not create a convolution relu forward descriptor");
- reset(result);
- }
-
- engine get_engine() { return engine::query(*this); }
- };
-
- convolution_relu_forward(const primitive_desc &aprimitive_desc,
- const primitive::at &src,
- const primitive::at &weights,
- const primitive::at &bias,
- const memory &dst) {
- mkldnn_primitive_t result;
- mkldnn_primitive_at_t inputs[] = {src.data, weights.data, bias.data};
- const_mkldnn_primitive_t outputs[] = {dst.get()};
- error::wrap_c_api(mkldnn_primitive_create(
- &result, aprimitive_desc.get(), inputs, outputs),
- "could not create a convolution relu forward primitive");
- reset(result);
- }
-
- convolution_relu_forward(const primitive_desc &aprimitive_desc,
- const primitive::at &src,
- const primitive::at &weights,
- const memory &dst) {
- mkldnn_primitive_t result;
- mkldnn_primitive_at_t inputs[] = {src.data, weights.data};
- const_mkldnn_primitive_t outputs[] = {dst.get()};
- error::wrap_c_api(mkldnn_primitive_create(
- &result, aprimitive_desc.get(), inputs, outputs),
- "could not create a convolution relu forward primitive");
- reset(result);
- }
-};
-
-/// @}
-//
-/// @addtogroup cpp_api_deconvolution Deconvolution
-/// @{
-
-struct deconvolution_forward : public primitive {
- struct desc {
- mkldnn_deconvolution_desc_t data;
- desc(prop_kind aprop_kind,
- algorithm aalgorithm,
- const memory::desc &src_desc,
- const memory::desc &weights_desc,
- const memory::desc &bias_desc,
- const memory::desc &dst_desc,
- const memory::dims strides,
- const memory::dims padding_l,
- const memory::dims padding_r,
- const padding_kind apadding_kind) {
- memory::validate_dims(strides);
- memory::validate_dims(padding_l);
- memory::validate_dims(padding_r);
- error::wrap_c_api(mkldnn_deconvolution_forward_desc_init(
- &data,
- mkldnn::convert_to_c(aprop_kind),
- convert_to_c(aalgorithm),
- &src_desc.data,
- &weights_desc.data,
- &bias_desc.data,
- &dst_desc.data,
- &strides[0],
- &padding_l[0],
- &padding_r[0],
- mkldnn::convert_to_c(apadding_kind)),
- "could not create a deconvolution forward descriptor");
- }
- desc(prop_kind aprop_kind,
- algorithm aalgorithm,
- const memory::desc &src_desc,
- const memory::desc &weights_desc,
- const memory::desc &dst_desc,
- const memory::dims strides,
- const memory::dims padding_l,
- const memory::dims padding_r,
- const padding_kind apadding_kind) {
- memory::validate_dims(strides);
- memory::validate_dims(padding_l);
- memory::validate_dims(padding_r);
- error::wrap_c_api(mkldnn_deconvolution_forward_desc_init(
- &data,
- mkldnn::convert_to_c(aprop_kind),
- convert_to_c(aalgorithm),
- &src_desc.data,
- &weights_desc.data,
- nullptr,
- &dst_desc.data,
- &strides[0],
- &padding_l[0],
- &padding_r[0],
- mkldnn::convert_to_c(apadding_kind)),
- "could not create a deconvolution forward descriptor");
- }
- };
- struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
- primitive_desc(const desc &adesc, const engine &aengine) {
- mkldnn_primitive_desc_t result;
- error::wrap_c_api(
- mkldnn_primitive_desc_create(
- &result, &adesc.data, aengine.get(), nullptr),
- "could not create a deconvolution forward primitive descriptor");
- reset(result);
- }
-
- primitive_desc(const desc &adesc,
- const primitive_attr &aattr,
- const engine &aengine) {
- mkldnn_primitive_desc_t result;
- error::wrap_c_api(
- mkldnn_primitive_desc_create_v2(
- &result, &adesc.data, aattr.get(), aengine.get(), nullptr),
- "could not create a deconvolution forward primitive descriptor");
- reset(result);
- }
-
- memory::primitive_desc src_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t cdesc;
- const_mkldnn_primitive_desc_t const_cdesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(src_pd), 0);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
- "could not clone a src primititve descriptor");
- adesc.reset(cdesc);
- return adesc;
- }
-
- memory::primitive_desc weights_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t cdesc;
- const_mkldnn_primitive_desc_t const_cdesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(weights_pd), 0);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
- "could not clone a weights primitive descriptor");
- adesc.reset(cdesc);
- return adesc;
- }
-
- memory::primitive_desc bias_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t cdesc;
- const_mkldnn_primitive_desc_t const_cdesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(weights_pd), 1);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
- "could not clone a bias primitive descriptor");
- adesc.reset(cdesc);
- return adesc;
- }
-
- memory::primitive_desc dst_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t cdesc;
- const_mkldnn_primitive_desc_t const_cdesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(dst_pd), 0);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
- "could not clone a dst primitive descriptor");
- adesc.reset(cdesc);
- return adesc;
- }
-
- engine get_engine() { return engine::query(*this); }
- };
-
- deconvolution_forward(const primitive_desc &aprimitive_desc,
- const primitive::at &src,
- const primitive::at &weights,
- const primitive::at &bias,
- const memory &dst) {
- mkldnn_primitive_t result;
- mkldnn_primitive_at_t inputs[] = {src.data, weights.data, bias.data};
- const_mkldnn_primitive_t outputs[] = {dst.get()};
- error::wrap_c_api(
- mkldnn_primitive_create(
- &result, aprimitive_desc.get(), inputs, outputs),
- "could not create a deconvolution forward bias primitive");
- reset(result);
- }
-
- deconvolution_forward(const primitive_desc &aprimitive_desc,
- const primitive::at &src,
- const primitive::at &weights,
- const memory &dst) {
- mkldnn_primitive_t result;
- mkldnn_primitive_at_t inputs[] = {src.data, weights.data};
- const_mkldnn_primitive_t outputs[] = {dst.get()};
- error::wrap_c_api(mkldnn_primitive_create(
- &result, aprimitive_desc.get(), inputs, outputs),
- "could not create a deconvolution forward primitive");
- reset(result);
- }
-};
-
-struct deconvolution_backward_data : public primitive {
- struct desc {
- mkldnn_deconvolution_desc_t data;
- desc(algorithm aalgorithm,
- const memory::desc &diff_src_desc,
- const memory::desc &weights_desc,
- const memory::desc &diff_dst_desc,
- const memory::dims strides,
- const memory::dims padding_l,
- const memory::dims padding_r,
- const padding_kind apadding_kind) {
- memory::validate_dims(strides);
- memory::validate_dims(padding_l);
- memory::validate_dims(padding_r);
- error::wrap_c_api(
- mkldnn_deconvolution_backward_data_desc_init(
- &data,
- convert_to_c(aalgorithm),
- &diff_src_desc.data,
- &weights_desc.data,
- &diff_dst_desc.data,
- &strides[0],
- &padding_l[0],
- &padding_r[0],
- mkldnn::convert_to_c(apadding_kind)),
- "could not create a deconvolution backward data descriptor");
- }
- };
- struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
- primitive_desc(
- const desc &adesc,
- const engine &aengine,
- const deconvolution_forward::primitive_desc &hint_fwd_primitive_desc) {
- mkldnn_primitive_desc_t result;
- error::wrap_c_api(
- mkldnn_primitive_desc_create(&result,
- &adesc.data,
- aengine.get(),
- hint_fwd_primitive_desc.get()),
- "could not create a deconvolution backward data primitive "
- "descriptor");
- reset(result);
- }
- memory::primitive_desc diff_src_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t cdesc;
- const_mkldnn_primitive_desc_t const_cdesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(diff_src_pd), 0);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
- "could not clone a diff_src primititve descriptor");
- adesc.reset(cdesc);
- return adesc;
- }
-
- memory::primitive_desc weights_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t cdesc;
- const_mkldnn_primitive_desc_t const_cdesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(weights_pd), 0);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
- "could not clone a weights primitive descriptor");
- adesc.reset(cdesc);
- return adesc;
- }
-
- memory::primitive_desc diff_dst_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t cdesc;
- const_mkldnn_primitive_desc_t const_cdesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(diff_dst_pd), 0);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
- "could not clone a diff_dst primitive descriptor");
- adesc.reset(cdesc);
- return adesc;
- }
-
- engine get_engine() { return engine::query(*this); }
- };
-
- deconvolution_backward_data(const primitive_desc &aprimitive_desc,
- const primitive::at &diff_dst,
- const primitive::at &weights,
- const memory &diff_src) {
- mkldnn_primitive_t result;
- mkldnn_primitive_at_t inputs[] = {diff_dst.data, weights.data};
- const_mkldnn_primitive_t outputs[] = {diff_src.get()};
- error::wrap_c_api(
- mkldnn_primitive_create(
- &result, aprimitive_desc.get(), inputs, outputs),
- "could not create a deconvolution backward data primitive");
- reset(result);
- }
-};
-
-struct deconvolution_backward_weights : public primitive {
- struct desc {
- mkldnn_deconvolution_desc_t data;
- desc(algorithm aalgorithm,
- const memory::desc &src_desc,
- const memory::desc &diff_weights_desc,
- const memory::desc &diff_bias_desc,
- const memory::desc &diff_dst_desc,
- const memory::dims strides,
- const memory::dims padding_l,
- const memory::dims padding_r,
- const padding_kind apadding_kind) {
- memory::validate_dims(strides);
- memory::validate_dims(padding_l);
- memory::validate_dims(padding_r);
- error::wrap_c_api(
- mkldnn_deconvolution_backward_weights_desc_init(
- &data,
- convert_to_c(aalgorithm),
- &src_desc.data,
- &diff_weights_desc.data,
- &diff_bias_desc.data,
- &diff_dst_desc.data,
- &strides[0],
- &padding_l[0],
- &padding_r[0],
- mkldnn::convert_to_c(apadding_kind)),
- "could not create a deconvolution backward weights descriptor");
- }
- desc(algorithm aalgorithm,
- const memory::desc &src_desc,
- const memory::desc &diff_weights_desc,
- const memory::desc &diff_dst_desc,
- const memory::dims strides,
- const memory::dims padding_l,
- const memory::dims padding_r,
- const padding_kind apadding_kind) {
- memory::validate_dims(strides);
- memory::validate_dims(padding_l);
- memory::validate_dims(padding_r);
- error::wrap_c_api(
- mkldnn_deconvolution_backward_weights_desc_init(
- &data,
- convert_to_c(aalgorithm),
- &src_desc.data,
- &diff_weights_desc.data,
- nullptr,
- &diff_dst_desc.data,
- &strides[0],
- &padding_l[0],
- &padding_r[0],
- mkldnn::convert_to_c(apadding_kind)),
- "could not create a deconvolution backward weights descriptor");
- }
- };
-
- struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
- primitive_desc(
- const desc &adesc,
- const engine &aengine,
- const deconvolution_forward::primitive_desc &hint_fwd_primitive_desc) {
- mkldnn_primitive_desc_t result;
- error::wrap_c_api(
- mkldnn_primitive_desc_create(&result,
- &adesc.data,
- aengine.get(),
- hint_fwd_primitive_desc.get()),
- "could not create a deconvolution backward weights primitive "
- "descriptor");
- reset(result);
- }
- memory::primitive_desc src_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t cdesc;
- const_mkldnn_primitive_desc_t const_cdesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(src_pd), 0);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
- "could not clone a src primititve descriptor");
- adesc.reset(cdesc);
- return adesc;
- }
-
- memory::primitive_desc diff_weights_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t cdesc;
- const_mkldnn_primitive_desc_t const_cdesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(diff_weights_pd), 0);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
- "could not clone a diff_weights primitive descriptor");
- adesc.reset(cdesc);
- return adesc;
- }
-
- memory::primitive_desc diff_bias_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t cdesc;
- const_mkldnn_primitive_desc_t const_cdesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(diff_weights_pd), 1);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
- "could not clone a diff_bias primitive descriptor");
- adesc.reset(cdesc);
- return adesc;
- }
-
- memory::primitive_desc diff_dst_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t cdesc;
- const_mkldnn_primitive_desc_t const_cdesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(diff_dst_pd), 0);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
- "could not clone a diff_dst primitive descriptor");
- adesc.reset(cdesc);
- return adesc;
- }
-
- engine get_engine() { return engine::query(*this); }
- };
-
- deconvolution_backward_weights(const primitive_desc &aprimitive_desc,
- const primitive::at &src,
- const primitive::at &diff_dst,
- const memory &diff_weights,
- const memory &diff_bias) {
- mkldnn_primitive_t result;
- mkldnn_primitive_at_t inputs[] = {src.data, diff_dst.data};
- const_mkldnn_primitive_t outputs[] = {diff_weights.get(), diff_bias.get()};
- error::wrap_c_api(
- mkldnn_primitive_create(
- &result, aprimitive_desc.get(), inputs, outputs),
- "could not create a deconvolution backward weights primitive");
- reset(result);
- }
- deconvolution_backward_weights(const primitive_desc &aprimitive_desc,
- const primitive::at &src,
- const primitive::at &diff_dst,
- const memory &diff_weights) {
- mkldnn_primitive_t result;
- mkldnn_primitive_at_t inputs[] = {src.data, diff_dst.data};
- const_mkldnn_primitive_t outputs[] = {diff_weights.get()};
- error::wrap_c_api(
- mkldnn_primitive_create(
- &result, aprimitive_desc.get(), inputs, outputs),
- "could not create a deconvolution backward weights primitive");
- reset(result);
- }
-};
-
-/// @}
-
-/// @addtogroup cpp_api_lrn LRN
-/// @{
-
-struct lrn_forward : public primitive {
- struct desc {
- mkldnn_lrn_desc_t data;
- desc(prop_kind aprop_kind,
- algorithm aalgorithm,
- const memory::desc &src_desc,
- int local_size,
- float alpha,
- float beta,
- float k) {
- error::wrap_c_api(
- mkldnn_lrn_forward_desc_init(&data,
- mkldnn::convert_to_c(aprop_kind),
- convert_to_c(aalgorithm),
- &src_desc.data,
- local_size,
- alpha,
- beta,
- k),
- "could not create a lrn forward descriptor");
- }
- desc(prop_kind aprop_kind,
- algorithm aalgorithm,
- const memory::desc &src_desc,
- int local_size,
- float alpha,
- float beta) {
- error::wrap_c_api(
- mkldnn_lrn_forward_desc_init(&data,
- mkldnn::convert_to_c(aprop_kind),
- convert_to_c(aalgorithm),
- &src_desc.data,
- local_size,
- alpha,
- beta,
- float(1.0)),
- "could not create a lrn forward descriptor");
- }
- };
-
- struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
- primitive_desc(const desc &adesc, const engine &aengine) {
- mkldnn_primitive_desc_t result;
- error::wrap_c_api(mkldnn_primitive_desc_create(
- &result, &adesc.data, aengine.get(), nullptr),
- "could not create a lrn forward primitive descriptor");
- reset(result);
- }
-
- memory::primitive_desc src_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t cdesc;
- const_mkldnn_primitive_desc_t const_cdesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(src_pd), 0);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
- "could not clone a src primitive descriptor");
- adesc.reset(cdesc);
- return adesc;
- }
-
- memory::primitive_desc workspace_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t ldesc;
- const_mkldnn_primitive_desc_t const_ldesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(workspace_pd), 0);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&ldesc, const_ldesc),
- "could not clone a workspace primitive descriptor");
- adesc.reset(ldesc);
- return adesc;
- }
-
- memory::primitive_desc dst_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t cdesc;
- const_mkldnn_primitive_desc_t const_cdesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(dst_pd), 0);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
- "could not clone a dst primitive descriptor");
- adesc.reset(cdesc);
- return adesc;
- }
-
- engine get_engine() { return engine::query(*this); }
- };
-
- lrn_forward(const primitive_desc &aprimitive_desc,
- const primitive::at &src,
- const memory &workspace,
- const memory &dst) {
- mkldnn_primitive_t result;
- mkldnn_primitive_at_t inputs[] = {src.data};
- const_mkldnn_primitive_t outputs[] = {dst.get(), workspace.get()};
- error::wrap_c_api(mkldnn_primitive_create(
- &result, aprimitive_desc.get(), inputs, outputs),
- "could not create a lrn forward primitive");
- reset(result);
- }
-
- lrn_forward(const primitive_desc &aprimitive_desc,
- const primitive::at &src,
- const memory &dst) {
- mkldnn_primitive_t result;
- mkldnn_primitive_at_t inputs[] = {src.data};
- const_mkldnn_primitive_t outputs[] = {dst.get()};
- error::wrap_c_api(mkldnn_primitive_create(
- &result, aprimitive_desc.get(), inputs, outputs),
- "could not create a lrn forward primitive");
- reset(result);
- }
-};
-
-struct lrn_backward : public primitive {
- struct desc {
- mkldnn_lrn_desc_t data;
- desc(algorithm aalgorithm,
- const memory::desc &data_desc,
- const memory::desc &diff_data_desc,
- int local_size,
- float alpha,
- float beta,
- float k) {
- error::wrap_c_api(mkldnn_lrn_backward_desc_init(&data,
- convert_to_c(aalgorithm),
- &diff_data_desc.data,
- &data_desc.data,
- local_size,
- alpha,
- beta,
- k),
- "could not create a lrn backward descriptor");
- }
- desc(algorithm aalgorithm,
- const memory::desc &data_desc,
- const memory::desc &diff_data_desc,
- int local_size,
- float alpha,
- float beta) {
- error::wrap_c_api(mkldnn_lrn_backward_desc_init(&data,
- convert_to_c(aalgorithm),
- &diff_data_desc.data,
- &data_desc.data,
- local_size,
- alpha,
- beta,
- float(1.0)),
- "could not create a lrn backward descriptor");
- }
- };
-
- struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
- primitive_desc(const desc &adesc,
- const engine &aengine,
- const lrn_forward::primitive_desc &hint_fwd_primitive_desc) {
- mkldnn_primitive_desc_t result;
- error::wrap_c_api(
- mkldnn_primitive_desc_create(&result,
- &adesc.data,
- aengine.get(),
- hint_fwd_primitive_desc.get()),
- "could not create a backward lrn primitive descriptor");
- reset(result);
- }
-
- memory::primitive_desc diff_src_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t cdesc;
- const_mkldnn_primitive_desc_t const_cdesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(diff_src_pd), 0);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
- "could not clone a diff_src primitive descriptor");
- adesc.reset(cdesc);
- return adesc;
- }
-
- memory::primitive_desc workspace_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t ldesc;
- const_mkldnn_primitive_desc_t const_ldesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(workspace_pd), 0);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&ldesc, const_ldesc),
- "could not clone a workspace primitive descriptor");
- adesc.reset(ldesc);
- return adesc;
- }
-
- memory::primitive_desc diff_dst_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t cdesc;
- const_mkldnn_primitive_desc_t const_cdesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(diff_dst_pd), 0);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
- "could not clone a diff_dst primitive descriptor");
- adesc.reset(cdesc);
- return adesc;
- }
-
- engine get_engine() { return engine::query(*this); }
- };
-
- lrn_backward(const primitive_desc &aprimitive_desc,
- const primitive::at &src,
- const primitive::at &diff_dst,
- const primitive::at &workspace,
- const memory &diff_src) {
- mkldnn_primitive_t result;
- mkldnn_primitive_at_t inputs[] = {src.data, diff_dst.data, workspace.data};
- const_mkldnn_primitive_t outputs[] = {diff_src.get()};
- error::wrap_c_api(mkldnn_primitive_create(
- &result, aprimitive_desc.get(), inputs, outputs),
- "could not create a lrn backward primitive");
- reset(result);
- }
-
- lrn_backward(const primitive_desc &aprimitive_desc,
- const primitive::at &src,
- const primitive::at &diff_dst,
- const memory &diff_src) {
- mkldnn_primitive_t result;
- mkldnn_primitive_at_t inputs[] = {src.data, diff_dst.data};
- const_mkldnn_primitive_t outputs[] = {diff_src.get()};
- error::wrap_c_api(mkldnn_primitive_create(
- &result, aprimitive_desc.get(), inputs, outputs),
- "could not create a lrn backward primitive");
- reset(result);
- }
-};
-
-/// @}
-
-/// @addtogroup cpp_api_pooling Pooling
-/// @{
-
-struct pooling_forward : public primitive {
- struct desc {
- mkldnn_pooling_desc_t data;
- desc(prop_kind aprop_kind,
- algorithm aalgorithm,
- const memory::desc &src_desc,
- const memory::desc &dst_desc,
- const memory::dims strides,
- const memory::dims kernel,
- const memory::dims padding_l,
- const memory::dims padding_r,
- const padding_kind apadding_kind) {
- memory::validate_dims(strides);
- memory::validate_dims(kernel);
- memory::validate_dims(padding_l);
- memory::validate_dims(padding_r);
- error::wrap_c_api(
- mkldnn_pooling_forward_desc_init(&data,
- mkldnn::convert_to_c(aprop_kind),
- convert_to_c(aalgorithm),
- &src_desc.data,
- &dst_desc.data,
- &strides[0],
- &kernel[0],
- &padding_l[0],
- &padding_r[0],
- mkldnn::convert_to_c(apadding_kind)),
- "could not init a forward pooling descriptor");
- }
- };
-
- struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
- primitive_desc(const desc &adesc, const engine &aengine) {
- mkldnn_primitive_desc_t result;
- error::wrap_c_api(
- mkldnn_primitive_desc_create(
- &result, &adesc.data, aengine.get(), nullptr),
- "could not create a forward pooling primitive descriptor");
- reset(result);
- }
-
- memory::primitive_desc workspace_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t cdesc;
- const_mkldnn_primitive_desc_t const_cdesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(workspace_pd), 0);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
- "could not clone a workspace primititve descriptor");
- adesc.reset(cdesc);
- return adesc;
- }
-
- memory::primitive_desc dst_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t cdesc;
- const_mkldnn_primitive_desc_t const_cdesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(dst_pd), 0);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
- "could not clone a dst primitive descriptor");
- adesc.reset(cdesc);
- return adesc;
- }
-
- engine get_engine() { return engine::query(*this); }
- };
-
- pooling_forward(const primitive_desc &aprimitive_desc,
- const primitive::at &src,
- const memory &dst) {
- mkldnn_primitive_t result;
- mkldnn_primitive_at_t inputs[] = {src.data};
- const_mkldnn_primitive_t outputs[] = {dst.get(), nullptr};
- error::wrap_c_api(mkldnn_primitive_create(
- &result, aprimitive_desc.get(), inputs, outputs),
- "could not create a pooling forward primitive");
- reset(result);
- }
-
- pooling_forward(const primitive_desc &aprimitive_desc,
- const primitive::at &src,
- const memory &dst,
- const memory &workspace) {
- mkldnn_primitive_t result;
- mkldnn_primitive_at_t inputs[] = {src.data};
- const_mkldnn_primitive_t outputs[] = {dst.get(), workspace.get()};
- error::wrap_c_api(mkldnn_primitive_create(
- &result, aprimitive_desc.get(), inputs, outputs),
- "could not create a pooling forward primitive");
- reset(result);
- }
-};
-
-struct pooling_backward : public primitive {
- struct desc {
- mkldnn_pooling_desc_t data;
- desc(algorithm aalgorithm,
- const memory::desc &diff_src_desc,
- const memory::desc &diff_dst_desc,
- const memory::dims &strides,
- const memory::dims &kernel,
- const memory::dims &padding_l,
- const memory::dims &padding_r,
- const padding_kind apadding_kind) {
- memory::validate_dims(strides);
- memory::validate_dims(kernel);
- memory::validate_dims(padding_l);
- memory::validate_dims(padding_r);
- error::wrap_c_api(mkldnn_pooling_backward_desc_init(
- &data,
- convert_to_c(aalgorithm),
- &diff_src_desc.data,
- &diff_dst_desc.data,
- &strides[0],
- &kernel[0],
- &padding_l[0],
- &padding_r[0],
- mkldnn::convert_to_c(apadding_kind)),
- "could not init a backward pooling descriptor");
- }
- };
-
- struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
- primitive_desc(
- const desc &adesc,
- const engine &aengine,
- const pooling_forward::primitive_desc &hint_fwd_primitive_desc) {
- mkldnn_primitive_desc_t result;
- error::wrap_c_api(
- mkldnn_primitive_desc_create(&result,
- &adesc.data,
- aengine.get(),
- hint_fwd_primitive_desc.get()),
- "could not create a backward pooling primitive descriptor");
- reset(result);
- }
-
- memory::primitive_desc diff_src_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t cdesc;
- const_mkldnn_primitive_desc_t const_cdesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(diff_src_pd), 0);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
- "could not clone a diff src primitive descriptor");
- adesc.reset(cdesc);
- return adesc;
- }
-
- engine get_engine() { return engine::query(*this); }
- };
-
- pooling_backward(const primitive_desc &aprimitive_desc,
- const primitive::at &diff_dst,
- const memory &diff_src) {
- mkldnn_primitive_t result;
- mkldnn_primitive_at_t inputs[] = {diff_dst.data};
- const_mkldnn_primitive_t outputs[] = {diff_src.get()};
- error::wrap_c_api(mkldnn_primitive_create(
- &result, aprimitive_desc.get(), inputs, outputs),
- "could not create a pooling backward primitive");
- reset(result);
- }
-
- pooling_backward(const primitive_desc &aprimitive_desc,
- const primitive::at &diff_dst,
- const primitive::at &workspace,
- const memory &diff_src) {
- mkldnn_primitive_t result;
- mkldnn_primitive_at_t inputs[] = {diff_dst.data, workspace.data};
- const_mkldnn_primitive_t outputs[] = {diff_src.get()};
- error::wrap_c_api(mkldnn_primitive_create(
- &result, aprimitive_desc.get(), inputs, outputs),
- "could not create a pooling backward primitive");
- reset(result);
- }
-};
-
-/// @}
-
-/// @addtogroup cpp_api_eltwise Eltwise
-/// @{
-
-struct eltwise_forward : public primitive {
- struct desc {
- mkldnn_eltwise_desc_t data;
- template <typename T>
- desc(prop_kind aprop_kind,
- algorithm alg_kind,
- const memory::desc &src_desc,
- T alpha = 0,
- T beta = 0) {
- error::wrap_c_api(
- mkldnn_eltwise_forward_desc_init(&data,
- mkldnn::convert_to_c(aprop_kind),
- mkldnn::convert_to_c(alg_kind),
- &src_desc.data,
- static_cast<float>(alpha),
- static_cast<float>(beta)),
- "could not create a eltwise forward descriptor");
- }
-
- /** @deprecated: api backward compatibility for relu */
- template <typename T>
- MKLDNN_DEPRECATED desc(prop_kind aprop_kind,
- const memory::desc &src_desc,
- T negative_slope)
- : desc(aprop_kind, eltwise_relu, src_desc, negative_slope) {}
- };
-
- struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
- primitive_desc(const desc &adesc, const engine &aengine) {
- mkldnn_primitive_desc_t result;
- error::wrap_c_api(
- mkldnn_primitive_desc_create(
- &result, &adesc.data, aengine.get(), nullptr),
- "could not create a eltwise forward primitive descriptor");
- reset(result);
- }
-
- memory::primitive_desc dst_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t cdesc;
- const_mkldnn_primitive_desc_t const_cdesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(dst_pd), 0);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
- "could not clone a dst primitive descriptor");
- adesc.reset(cdesc);
- return adesc;
- }
-
- engine get_engine() { return engine::query(*this); }
- };
-
- eltwise_forward(const primitive_desc &aprimitive_desc,
- const primitive::at &src,
- const memory &dst) {
- mkldnn_primitive_t result;
- mkldnn_primitive_at_t inputs[] = {src.data};
- const_mkldnn_primitive_t outputs[] = {dst.get()};
- error::wrap_c_api(mkldnn_primitive_create(
- &result, aprimitive_desc.get(), inputs, outputs),
- "could not create a eltwise forward primitive");
- reset(result);
- }
-};
-
-typedef eltwise_forward relu_forward;
-
-struct eltwise_backward : public primitive {
- struct desc {
- mkldnn_eltwise_desc_t data;
-
- template <typename T>
- desc(algorithm alg_kind,
- const memory::desc &diff_data_desc,
- const memory::desc &data_desc,
- T alpha = 0,
- T beta = 0) {
- error::wrap_c_api(
- mkldnn_eltwise_backward_desc_init(&data,
- mkldnn::convert_to_c(alg_kind),
- &diff_data_desc.data,
- &data_desc.data,
- static_cast<float>(alpha),
- static_cast<float>(beta)),
- "could not create a eltwise backward descriptor");
- }
-
- /** @deprecated: api backward compatibility for relu */
- template <typename T>
- MKLDNN_DEPRECATED desc(const memory::desc &diff_data_desc,
- const memory::desc &data_desc,
- T negative_slope)
- : desc(eltwise_relu, diff_data_desc, data_desc, negative_slope) {}
- };
-
- struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
- primitive_desc(
- const desc &adesc,
- const engine &aengine,
- const eltwise_forward::primitive_desc &hint_fwd_primitive_desc) {
- mkldnn_primitive_desc_t result;
- error::wrap_c_api(
- mkldnn_primitive_desc_create(&result,
- &adesc.data,
- aengine.get(),
- hint_fwd_primitive_desc.get()),
- "could not create a eltwise backward primitive descriptor");
- reset(result);
- }
-
- memory::primitive_desc diff_src_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t cdesc;
- const_mkldnn_primitive_desc_t const_cdesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(diff_src_pd), 0);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
- "could not clone a diff src primitive descriptor");
- adesc.reset(cdesc);
- return adesc;
- }
-
- engine get_engine() { return engine::query(*this); }
- };
-
- eltwise_backward(const primitive_desc &aprimitive_desc,
- const primitive::at &src,
- const primitive::at &diff_dst,
- const memory &diff_src) {
- mkldnn_primitive_t result;
- mkldnn_primitive_at_t inputs[] = {src.data, diff_dst.data};
- const_mkldnn_primitive_t outputs[] = {diff_src.get()};
- error::wrap_c_api(mkldnn_primitive_create(
- &result, aprimitive_desc.get(), inputs, outputs),
- "could not create a eltwise backward primitive");
- reset(result);
- }
-};
-
-typedef eltwise_backward relu_backward;
-
-/// @}
-
-/// @addtogroup cpp_api_softmax Softmax
-/// @{
-
-struct softmax_forward : public primitive {
- struct desc {
- mkldnn_softmax_desc_t data;
- desc(prop_kind aprop_kind,
- const memory::desc &data_desc,
- int softmax_axis) {
- error::wrap_c_api(
- mkldnn_softmax_forward_desc_init(&data,
- mkldnn::convert_to_c(aprop_kind),
- &data_desc.data,
- softmax_axis),
- "could not create a softmax forward descriptor");
- }
- };
-
- struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
- primitive_desc(const desc &adesc, const engine &aengine) {
- mkldnn_primitive_desc_t result;
- error::wrap_c_api(
- mkldnn_primitive_desc_create(
- &result, &adesc.data, aengine.get(), nullptr),
- "could not create a softmax forward primitive descriptor");
- reset(result);
- }
-
- engine get_engine() { return engine::query(*this); }
- };
-
- softmax_forward(const primitive_desc &aprimitive_desc,
- const primitive::at &src,
- const memory &dst) {
- mkldnn_primitive_t result;
- mkldnn_primitive_at_t inputs[] = {src.data};
- const_mkldnn_primitive_t outputs[] = {dst.get()};
- error::wrap_c_api(mkldnn_primitive_create(
- &result, aprimitive_desc.get(), inputs, outputs),
- "could not create a softmax forward primitive");
- reset(result);
- }
-};
-
-/// @}
-
-/// @addtogroup cpp_api_batch_norm Batch normalization
-/// @{
-
-struct batch_normalization_forward : public primitive {
- struct desc {
- mkldnn_batch_normalization_desc_t data;
- template <typename T>
- desc(prop_kind aprop_kind,
- const memory::desc &src_desc,
- T epsilon,
- unsigned flags) {
- error::wrap_c_api(
- mkldnn_batch_normalization_forward_desc_init(
- &data,
- mkldnn::convert_to_c(aprop_kind),
- &src_desc.data,
- static_cast<float>(epsilon),
- flags),
- "could not create a batch normalization forward descriptor");
- }
- };
-
- struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
- primitive_desc(const desc &adesc, const engine &aengine) {
- mkldnn_primitive_desc_t result;
- error::wrap_c_api(mkldnn_primitive_desc_create(
- &result, &adesc.data, aengine.get(), nullptr),
- "could not create a batch normalization forward "
- "primitive descriptor");
- reset(result);
- }
-
- primitive_desc(const desc &adesc,
- const primitive_attr &aattr,
- const engine &aengine) {
- mkldnn_primitive_desc_t result;
- error::wrap_c_api(
- mkldnn_primitive_desc_create_v2(
- &result, &adesc.data, aattr.get(), aengine.get(), nullptr),
- "could not create a batch normalization forward "
- "primitive descriptor");
- reset(result);
- }
-
- memory::primitive_desc weights_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t bndesc;
- const_mkldnn_primitive_desc_t const_bndesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(weights_pd), 0);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&bndesc, const_bndesc),
- "could not clone a weights primitive descriptor");
- adesc.reset(bndesc);
- return adesc;
- }
-
- memory::primitive_desc mean_primitive_desc() const {
- memory::primitive_desc aprimitive_desc;
- mkldnn_primitive_desc_t bndesc;
- mkldnn_batch_normalization_desc_t *p;
- error::wrap_c_api(
- mkldnn_primitive_desc_query(
- get(), mkldnn::convert_to_c(batch_normalization_d), 0, &p),
- "could not get a batch-normalization descriptor");
- const_mkldnn_primitive_desc_t const_bndesc =
- (p->flags & use_global_stats)
- ? mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(src_pd), 1)
- : mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(dst_pd), 1);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&bndesc, const_bndesc),
- "could not clone a mean primitive descriptor");
- aprimitive_desc.reset(bndesc);
- return aprimitive_desc;
- }
-
- memory::primitive_desc variance_primitive_desc() const {
- memory::primitive_desc aprimitive_desc;
- mkldnn_primitive_desc_t bndesc;
- mkldnn_batch_normalization_desc_t *p;
- error::wrap_c_api(
- mkldnn_primitive_desc_query(
- get(), mkldnn::convert_to_c(batch_normalization_d), 0, &p),
- "could not get a batch-normalization descriptor");
- const_mkldnn_primitive_desc_t const_bndesc =
- (p->flags & use_global_stats)
- ? mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(src_pd), 2)
- : mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(dst_pd), 2);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&bndesc, const_bndesc),
- "could not clone a variance primitive descriptor");
- aprimitive_desc.reset(bndesc);
- return aprimitive_desc;
- }
-
- memory::primitive_desc workspace_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t cdesc;
- const_mkldnn_primitive_desc_t const_cdesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(workspace_pd), 0);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
- "could not clone a workspace primitive descriptor");
- adesc.reset(cdesc);
- return adesc;
- }
-
- memory::primitive_desc dst_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t cdesc;
- const_mkldnn_primitive_desc_t const_cdesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(dst_pd), 0);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
- "could not clone a dst primitive descriptor");
- adesc.reset(cdesc);
- return adesc;
- }
-
- engine get_engine() { return engine::query(*this); }
- };
-
- batch_normalization_forward(const primitive_desc &aprimitive_desc,
- const primitive::at &src,
- const primitive::at &mean,
- const primitive::at &variance,
- const primitive::at &weights,
- const memory &dst) {
- mkldnn_primitive_t result;
- mkldnn_primitive_at_t inputs[] = {
- src.data, mean.data, variance.data, weights.data};
- const_mkldnn_primitive_t outputs[] = {dst.get()};
- error::wrap_c_api(
- mkldnn_primitive_create(
- &result, aprimitive_desc.get(), inputs, outputs),
- "could not create a batch normalization forward primitive");
- reset(result);
- }
-
- batch_normalization_forward(const primitive_desc &aprimitive_desc,
- const primitive::at &src,
- const primitive::at &mean,
- const primitive::at &variance,
- const memory &dst) {
- mkldnn_primitive_t result;
- mkldnn_primitive_at_t inputs[] = {src.data, mean.data, variance.data};
- const_mkldnn_primitive_t outputs[] = {dst.get()};
- error::wrap_c_api(
- mkldnn_primitive_create(
- &result, aprimitive_desc.get(), inputs, outputs),
- "could not create a batch normalization forward primitive");
- reset(result);
- }
-
- /// @warning batch_normalization_forward has 2 constructors with very
- /// similar signatures:
- /// - (pd, src, weights, dst, mean, variance) // 2 in, 3 out
- /// - (pd, src, dst, mean, variance, workspace) // 1 in, 4 out
- /// The only way to distinguish between those is to explicitly
- /// cast all input parameters to their type, i.e. to
- /// const primitive:at &.
- batch_normalization_forward(const primitive_desc &aprimitive_desc,
- const primitive::at &src,
- const primitive::at &weights,
- const memory &dst,
- const memory &mean,
- const memory &variance) {
- mkldnn_primitive_t result;
- mkldnn_primitive_at_t inputs[] = {src.data, weights.data};
- const_mkldnn_primitive_t outputs[] = {
- dst.get(), mean.get(), variance.get()};
- error::wrap_c_api(
- mkldnn_primitive_create(
- &result, aprimitive_desc.get(), inputs, outputs),
- "could not create a batch normalization forward primitive");
- reset(result);
- }
-
- batch_normalization_forward(const primitive_desc &aprimitive_desc,
- const primitive::at &src,
- const primitive::at &weights,
- const memory &dst,
- const memory &mean,
- const memory &variance,
- const memory &workspace) {
- mkldnn_primitive_t result;
- mkldnn_primitive_at_t inputs[] = {src.data, weights.data};
- const_mkldnn_primitive_t outputs[] = {
- dst.get(), mean.get(), variance.get(), workspace.get()};
- error::wrap_c_api(
- mkldnn_primitive_create(
- &result, aprimitive_desc.get(), inputs, outputs),
- "could not create a batch normalization forward primitive");
- reset(result);
- }
-
- batch_normalization_forward(const primitive_desc &aprimitive_desc,
- const primitive::at &src,
- const memory &dst,
- const memory &mean,
- const memory &variance) {
- mkldnn_primitive_t result;
- mkldnn_primitive_at_t inputs[] = {src.data};
- const_mkldnn_primitive_t outputs[] = {
- dst.get(), mean.get(), variance.get()};
- error::wrap_c_api(
- mkldnn_primitive_create(
- &result, aprimitive_desc.get(), inputs, outputs),
- "could not create a batch normalization forward primitive");
- reset(result);
- }
-
- /// @warning batch_normalization_forward has 2 constructors with very
- /// similar signatures:
- /// - (pd, src, weights, dst, mean, variance) // 2 in, 3 out
- /// - (pd, src, dst, mean, variance, workspace) // 1 in, 4 out
- /// The only way to distinguish between those is to explicitly
- /// cast all input parameters to their type, i.e. to
- /// const primitive:at &.
- /// @note to make users' experience a little bit better this constructor
- /// checks if whether parameters match corresponding primitive
- /// descriptor, and if they are not -- call the other (proper)
- /// constructor. Yeah, this is still very ugly...
- batch_normalization_forward(const primitive_desc &aprimitive_desc,
- const primitive::at &src,
- const memory &dst,
- const memory &mean,
- const memory &variance,
- const memory &workspace) {
- mkldnn_primitive_t result;
- mkldnn_primitive_at_t inputs[2] = {src.data};
- const_mkldnn_primitive_t outputs[4] = {
- dst.get(), mean.get(), variance.get(), workspace.get()};
-
- if (1) { // check whether this is the `wrong` constructor
- const int n_inputs_expected = mkldnn_primitive_desc_query_s32(
- aprimitive_desc.get(), mkldnn_query_num_of_inputs_s32, 0);
- const int n_outputs_expected = mkldnn_primitive_desc_query_s32(
- aprimitive_desc.get(), mkldnn_query_num_of_outputs_s32, 0);
- if (n_inputs_expected == 2 && n_outputs_expected == 3) {
- // shift parameters, get rid of workspace, and add weights...
- auto _weights = dst;
- inputs[1] = {_weights.get(), 0};
-
- auto _dst = mean, _mean = variance, _variance = workspace;
- outputs[0] = _dst.get();
- outputs[1] = _mean.get();
- outputs[2] = _variance.get();
- outputs[3] = nullptr;
- }
- }
- error::wrap_c_api(
- mkldnn_primitive_create(
- &result, aprimitive_desc.get(), inputs, outputs),
- "could not create a batch normalization forward primitive");
- reset(result);
- }
-
- batch_normalization_forward(const primitive_desc &aprimitive_desc,
- const primitive::at &src,
- const primitive::at &weights,
- const memory &dst) {
- mkldnn_primitive_t result;
- mkldnn_primitive_at_t inputs[] = {src.data, weights.data};
- const_mkldnn_primitive_t outputs[] = {dst.get()};
- error::wrap_c_api(
- mkldnn_primitive_create(
- &result, aprimitive_desc.get(), inputs, outputs),
- "could not create a batch normalization forward primitive");
- reset(result);
- }
-
- batch_normalization_forward(const primitive_desc &aprimitive_desc,
- const primitive::at &src,
- const memory &dst) {
- mkldnn_primitive_t result;
- mkldnn_primitive_at_t inputs[] = {src.data};
- const_mkldnn_primitive_t outputs[] = {dst.get()};
- error::wrap_c_api(
- mkldnn_primitive_create(
- &result, aprimitive_desc.get(), inputs, outputs),
- "could not create a batch normalization forward primitive");
- reset(result);
- }
-};
-
-struct batch_normalization_backward : public primitive {
- struct desc {
- mkldnn_batch_normalization_desc_t data;
- template <typename T>
- desc(prop_kind aprop_kind,
- const memory::desc &diff_data_desc,
- const memory::desc &data_desc,
- T epsilon,
- unsigned flags) {
- error::wrap_c_api(
- mkldnn_batch_normalization_backward_desc_init(
- &data,
- mkldnn::convert_to_c(aprop_kind),
- &diff_data_desc.data,
- &data_desc.data,
- static_cast<float>(epsilon),
- flags),
- "could not create a batch normalization backward descriptor");
- }
- };
-
- struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
- primitive_desc(const desc &adesc,
- const engine &aengine,
- const batch_normalization_forward::primitive_desc
- &hint_fwd_primitive_desc) {
- mkldnn_primitive_desc_t result;
- error::wrap_c_api(
- mkldnn_primitive_desc_create(&result,
- &adesc.data,
- aengine.get(),
- hint_fwd_primitive_desc.get()),
- "could not create a batch normalization backward primitive "
- "descriptor");
- reset(result);
- }
-
- memory::primitive_desc weights_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t bndesc;
- const_mkldnn_primitive_desc_t const_bndesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(weights_pd), 0);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&bndesc, const_bndesc),
- "could not clone a weights primitive descriptor");
- adesc.reset(bndesc);
- return adesc;
- }
-
- memory::primitive_desc diff_weights_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t bndesc;
- const_mkldnn_primitive_desc_t const_bndesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(diff_weights_pd), 0);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&bndesc, const_bndesc),
- "could not clone a diff_weights primitive descriptor");
- adesc.reset(bndesc);
- return adesc;
- }
-
- memory::primitive_desc mean_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t bndesc;
- const_mkldnn_primitive_desc_t const_bndesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(src_pd), 1);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&bndesc, const_bndesc),
- "could not clone a mean primitive descriptor");
- adesc.reset(bndesc);
- return adesc;
- }
-
- memory::primitive_desc variance_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t bndesc;
- const_mkldnn_primitive_desc_t const_bndesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(src_pd), 2);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&bndesc, const_bndesc),
- "could not clone a variance primitive descriptor");
- adesc.reset(bndesc);
- return adesc;
- }
-
- memory::primitive_desc workspace_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t cdesc;
- const_mkldnn_primitive_desc_t const_cdesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(workspace_pd), 0);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
- "could not clone a workspace primitive descriptor");
- adesc.reset(cdesc);
- return adesc;
- }
-
- memory::primitive_desc dst_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t cdesc;
- const_mkldnn_primitive_desc_t const_cdesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(dst_pd), 0);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
- "could not clone a dst primitive descriptor");
- adesc.reset(cdesc);
- return adesc;
- }
-
- engine get_engine() { return engine::query(*this); }
- };
-
- // Prop_kind == backward
- batch_normalization_backward(const primitive_desc &aprimitive_desc,
- const primitive::at &src,
- const primitive::at &mean,
- const primitive::at &variance,
- const primitive::at &diff_dst,
- const primitive::at &weights,
- const memory &diff_src,
- const memory &diff_weights) {
- mkldnn_primitive_t result;
- mkldnn_primitive_at_t inputs[] = {
- src.data, mean.data, variance.data, diff_dst.data, weights.data};
- const_mkldnn_primitive_t outputs[] = {diff_src.get(), diff_weights.get()};
- error::wrap_c_api(
- mkldnn_primitive_create(
- &result, aprimitive_desc.get(), inputs, outputs),
- "could not create a batch normalization backward primitive");
- reset(result);
- }
-
- // Prop_kind == backward (+ws)
- batch_normalization_backward(const primitive_desc &aprimitive_desc,
- const primitive::at &src,
- const primitive::at &mean,
- const primitive::at &variance,
- const primitive::at &diff_dst,
- const primitive::at &weights,
- const primitive::at &workspace,
- const memory &diff_src,
- const memory &diff_weights) {
- mkldnn_primitive_t result;
- mkldnn_primitive_at_t inputs[] = {src.data,
- mean.data,
- variance.data,
- diff_dst.data,
- weights.data,
- workspace.data};
- const_mkldnn_primitive_t outputs[] = {diff_src.get(), diff_weights.get()};
- error::wrap_c_api(
- mkldnn_primitive_create(
- &result, aprimitive_desc.get(), inputs, outputs),
- "could not create a batch normalization backward primitive");
- reset(result);
- }
-
- // Prop_kind == backward_data (+ws or +weights)
- /// @warning This constructor works for backward_data propagation
- /// - w/ weights but w/o workspace, or
- /// - w/ workspace but w/o weights
- batch_normalization_backward(const primitive_desc &aprimitive_desc,
- const primitive::at &src,
- const primitive::at &mean,
- const primitive::at &variance,
- const primitive::at &diff_dst,
- const primitive::at &weights_or_workspace,
- const memory &diff_src) {
- mkldnn_primitive_t result;
- mkldnn_primitive_at_t inputs[] = {src.data,
- mean.data,
- variance.data,
- diff_dst.data,
- weights_or_workspace.data};
- const_mkldnn_primitive_t outputs[] = {diff_src.get()};
- error::wrap_c_api(
- mkldnn_primitive_create(
- &result, aprimitive_desc.get(), inputs, outputs),
- "could not create a batch normalization backward primitive");
- reset(result);
- }
-
- // Prop_kind == backward_data
- batch_normalization_backward(const primitive_desc &aprimitive_desc,
- const primitive::at &src,
- const primitive::at &mean,
- const primitive::at &variance,
- const primitive::at &diff_dst,
- const memory &diff_src) {
- mkldnn_primitive_t result;
- mkldnn_primitive_at_t inputs[] = {
- src.data, mean.data, variance.data, diff_dst.data};
- const_mkldnn_primitive_t outputs[] = {diff_src.get()};
- error::wrap_c_api(
- mkldnn_primitive_create(
- &result, aprimitive_desc.get(), inputs, outputs),
- "could not create a batch normalization backward primitive");
- reset(result);
- }
-};
-
-/// @}
-
-/// @addtogroup cpp_api_inner_product Inner Product
-/// @{
-
-struct inner_product_forward : public primitive {
- struct desc {
- mkldnn_inner_product_desc_t data;
- desc(prop_kind aprop_kind,
- const memory::desc &src_desc,
- const memory::desc &weights_desc,
- const memory::desc &bias_desc,
- const memory::desc &dst_desc) {
- error::wrap_c_api(mkldnn_inner_product_forward_desc_init(
- &data,
- mkldnn::convert_to_c(aprop_kind),
- &src_desc.data,
- &weights_desc.data,
- &bias_desc.data,
- &dst_desc.data),
- "could not create a inner product forward descriptor");
- }
-
- desc(prop_kind aprop_kind,
- const memory::desc &src_desc,
- const memory::desc &weights_desc,
- const memory::desc &dst_desc) {
- error::wrap_c_api(mkldnn_inner_product_forward_desc_init(
- &data,
- mkldnn::convert_to_c(aprop_kind),
- &src_desc.data,
- &weights_desc.data,
- nullptr,
- &dst_desc.data),
- "could not create a inner product forward descriptor");
- }
- };
-
- struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
- primitive_desc(const desc &adesc, const engine &aengine) {
- mkldnn_primitive_desc_t result;
- error::wrap_c_api(
- mkldnn_primitive_desc_create(
- &result, &adesc.data, aengine.get(), nullptr),
- "could not create a inner product forward primitive descriptor");
- reset(result);
- }
-
- primitive_desc(const desc &adesc,
- const primitive_attr &aattr,
- const engine &aengine) {
- mkldnn_primitive_desc_t result;
- error::wrap_c_api(
- mkldnn_primitive_desc_create_v2(
- &result, &adesc.data, aattr.get(), aengine.get(), nullptr),
- "could not create a inner product "
- "forward primitive descriptor");
- reset(result);
- }
-
- memory::primitive_desc src_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t cdesc;
- const_mkldnn_primitive_desc_t const_cdesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(src_pd), 0);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
- "could not clone a src primitive descriptor");
- adesc.reset(cdesc);
- return adesc;
- }
-
- memory::primitive_desc weights_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t cdesc;
- const_mkldnn_primitive_desc_t const_cdesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(weights_pd), 0);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
- "could not clone a weights primitive descriptor");
- adesc.reset(cdesc);
- return adesc;
- }
-
- memory::primitive_desc bias_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t cdesc;
- const_mkldnn_primitive_desc_t const_cdesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(weights_pd), 1);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
- "could not clone a bias primitive descriptor");
- adesc.reset(cdesc);
- return adesc;
- }
-
- memory::primitive_desc dst_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t cdesc;
- const_mkldnn_primitive_desc_t const_cdesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(dst_pd), 0);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
- "could not clone a dst primitive descriptor");
- adesc.reset(cdesc);
- return adesc;
- }
-
- engine get_engine() { return engine::query(*this); }
- };
-
- inner_product_forward(const primitive_desc &aprimitive_desc,
- const primitive::at &src,
- const primitive::at weights,
- const primitive::at &bias,
- const memory &dst) {
- mkldnn_primitive_t result;
- mkldnn_primitive_at_t inputs[] = {src.data, weights.data, bias.data};
- const_mkldnn_primitive_t outputs[] = {dst.get()};
- error::wrap_c_api(mkldnn_primitive_create(
- &result, aprimitive_desc.get(), inputs, outputs),
- "could not create a inner product forward primitive");
- reset(result);
- }
-
- inner_product_forward(const primitive_desc &aprimitive_desc,
- const primitive::at &src,
- const primitive::at weights,
- const memory &dst) {
- mkldnn_primitive_t result;
- mkldnn_primitive_at_t inputs[] = {src.data, weights.data};
- const_mkldnn_primitive_t outputs[] = {dst.get()};
- error::wrap_c_api(mkldnn_primitive_create(
- &result, aprimitive_desc.get(), inputs, outputs),
- "could not create a inner product forward primitive");
- reset(result);
- }
-};
-
-struct inner_product_backward_data : public primitive {
- struct desc {
- mkldnn_inner_product_desc_t data;
- desc(const memory::desc &diff_src_desc,
- const memory::desc &weights_desc,
- const memory::desc &diff_dst_desc) {
- error::wrap_c_api(
- mkldnn_inner_product_backward_data_desc_init(&data,
- &diff_src_desc.data,
- &weights_desc.data,
- &diff_dst_desc.data),
- "could not create a inner product backward data descriptor");
- }
- };
-
- struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
- primitive_desc(
- const desc &adesc,
- const engine &aengine,
- const inner_product_forward::primitive_desc &hint_fwd_primitive_desc) {
- mkldnn_primitive_desc_t result;
- error::wrap_c_api(
- mkldnn_primitive_desc_create(&result,
- &adesc.data,
- aengine.get(),
- hint_fwd_primitive_desc.get()),
- "could not create a inner product backward data primitive "
- "descriptor");
- reset(result);
- }
-
- memory::primitive_desc diff_dst_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t cdesc;
- const_mkldnn_primitive_desc_t const_cdesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(diff_dst_pd), 0);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
- "could not clone a diff dst primititve descriptor");
- adesc.reset(cdesc);
- return adesc;
- }
-
- memory::primitive_desc weights_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t cdesc;
- const_mkldnn_primitive_desc_t const_cdesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(weights_pd), 0);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
- "could not clone a weights primitive descriptor");
- adesc.reset(cdesc);
- return adesc;
- }
-
- memory::primitive_desc diff_src_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t cdesc;
- const_mkldnn_primitive_desc_t const_cdesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(diff_src_pd), 0);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
- "could not clone a diff src primitive descriptor");
- adesc.reset(cdesc);
- return adesc;
- }
-
- engine get_engine() { return engine::query(*this); }
- };
-
- inner_product_backward_data(const primitive_desc &aprimitive_desc,
- const primitive::at &diff_dst,
- const primitive::at weights,
- const memory &diff_src) {
- mkldnn_primitive_t result;
- mkldnn_primitive_at_t inputs[] = {diff_dst.data, weights.data};
- const_mkldnn_primitive_t outputs[] = {diff_src.get()};
- error::wrap_c_api(
- mkldnn_primitive_create(
- &result, aprimitive_desc.get(), inputs, outputs),
- "could not create a inner product backward data primitive");
- reset(result);
- }
-};
-
-struct inner_product_backward_weights : public primitive {
- struct desc {
- mkldnn_inner_product_desc_t data;
- desc(const memory::desc &src_desc,
- const memory::desc &diff_weights_desc,
- const memory::desc &diff_bias_desc,
- const memory::desc &diff_dst_desc) {
- error::wrap_c_api(
- mkldnn_inner_product_backward_weights_desc_init(
- &data,
- &src_desc.data,
- &diff_weights_desc.data,
- &diff_bias_desc.data,
- &diff_dst_desc.data),
- "could not create a inner product backward weights descriptor");
- }
- desc(const memory::desc &src_desc,
- const memory::desc &diff_weights_desc,
- const memory::desc &diff_dst_desc) {
- error::wrap_c_api(
- mkldnn_inner_product_backward_weights_desc_init(
- &data,
- &src_desc.data,
- &diff_weights_desc.data,
- nullptr,
- &diff_dst_desc.data),
- "could not create a inner product backward weights descriptor");
- }
- };
-
- struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
- primitive_desc(
- const desc &adesc,
- const engine &aengine,
- const inner_product_forward::primitive_desc &hint_fwd_primitive_desc) {
- mkldnn_primitive_desc_t result;
- error::wrap_c_api(
- mkldnn_primitive_desc_create(&result,
- &adesc.data,
- aengine.get(),
- hint_fwd_primitive_desc.get()),
- "could not create a inner product backward weights primitive "
- "descriptor");
- reset(result);
- }
-
- memory::primitive_desc diff_dst_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t cdesc;
- const_mkldnn_primitive_desc_t const_cdesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(diff_dst_pd), 0);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
- "could not clone a diff dst primititve descriptor");
- adesc.reset(cdesc);
- return adesc;
- }
-
- memory::primitive_desc diff_weights_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t cdesc;
- const_mkldnn_primitive_desc_t const_cdesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(diff_weights_pd), 0);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
- "could not clone a diff weights primitive descriptor");
- adesc.reset(cdesc);
- return adesc;
- }
-
- memory::primitive_desc diff_bias_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t cdesc;
- const_mkldnn_primitive_desc_t const_cdesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(diff_weights_pd), 1);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
- "could not clone a diff bias primitive descriptor");
- adesc.reset(cdesc);
- return adesc;
- }
-
- memory::primitive_desc src_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t cdesc;
- const_mkldnn_primitive_desc_t const_cdesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(src_pd), 0);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
- "could not clone a src primitive descriptor");
- adesc.reset(cdesc);
- return adesc;
- }
-
- engine get_engine() { return engine::query(*this); }
- };
-
- inner_product_backward_weights(const primitive_desc &aprimitive_desc,
- const primitive::at &src,
- const primitive::at diff_dst,
- const memory &diff_weights) {
- mkldnn_primitive_t result;
- mkldnn_primitive_at_t inputs[] = {src.data, diff_dst.data};
- const_mkldnn_primitive_t outputs[] = {diff_weights.get()};
- error::wrap_c_api(
- mkldnn_primitive_create(
- &result, aprimitive_desc.get(), inputs, outputs),
- "could not create a inner product backward weights primitive");
- reset(result);
- }
-
- inner_product_backward_weights(const primitive_desc &aprimitive_desc,
- const primitive::at &src,
- const primitive::at diff_dst,
- const memory &diff_weights,
- const memory &diff_bias) {
- mkldnn_primitive_t result;
- mkldnn_primitive_at_t inputs[] = {src.data, diff_dst.data};
- const_mkldnn_primitive_t outputs[] = {diff_weights.get(), diff_bias.get()};
- error::wrap_c_api(
- mkldnn_primitive_create(
- &result, aprimitive_desc.get(), inputs, outputs),
- "could not create a inner product backward weights primitive");
- reset(result);
- }
-};
-
-/// @}
-
-/// @addtogroup cpp_api_rnn RNN
-/// @{
-
-struct rnn_cell {
- struct desc {
- mkldnn_rnn_cell_desc_t c_rnn_cell_;
-
- desc(algorithm kind, algorithm activation_f) {
- error::wrap_c_api(
- mkldnn_rnn_cell_desc_init(&c_rnn_cell_,
- mkldnn::convert_to_c(kind),
- mkldnn::convert_to_c(activation_f),
- 0U,
- 0,
- 0),
- "could not init an rnn cell descriptor");
- }
- desc(algorithm kind) : desc(kind, algorithm::algorithm_undef) {}
-
- operator const mkldnn_rnn_cell_desc_t *() const { return &c_rnn_cell_; }
-
- algorithm get_cell_kind() const { return algorithm(c_rnn_cell_.cell_kind); }
- algorithm get_activation() const {
- return algorithm(c_rnn_cell_.activation_kind);
- }
-
- float get_alpha() const { return c_rnn_cell_.alpha; }
- void set_alpha(float alpha) {
- c_rnn_cell_.flags |= mkldnn_rnn_cell_with_relu;
- c_rnn_cell_.alpha = alpha;
- }
-
- float get_clipping() const { return c_rnn_cell_.clipping; }
- void set_clipping(float clipping) {
- c_rnn_cell_.flags |= mkldnn_rnn_cell_with_clipping;
- c_rnn_cell_.clipping = clipping;
- }
-
- int get_gates_count() const {
- return mkldnn_rnn_cell_get_gates_count(&c_rnn_cell_);
- }
- int get_state_count() const {
- return mkldnn_rnn_cell_get_states_count(&c_rnn_cell_);
- }
- };
-};
-
-struct rnn_forward : public primitive {
- struct desc {
- mkldnn_rnn_desc_t data;
- desc(prop_kind aprop_kind,
- rnn_cell::desc cell,
- const rnn_direction direction,
- const memory::desc &src_layer_desc,
- const memory::desc &src_iter_desc,
- const memory::desc &weights_layer_desc,
- const memory::desc &weights_iter_desc,
- const memory::desc &bias_desc,
- const memory::desc &dst_layer_desc,
- const memory::desc &dst_iter_desc) {
- error::wrap_c_api(
- mkldnn_rnn_forward_desc_init(&data,
- mkldnn::convert_to_c(aprop_kind),
- cell,
- mkldnn::convert_to_c(direction),
- &src_layer_desc.data,
- &src_iter_desc.data,
- &weights_layer_desc.data,
- &weights_iter_desc.data,
- &bias_desc.data,
- &dst_layer_desc.data,
- &dst_iter_desc.data),
- "could not create an RNN forward descriptor");
- }
- };
- struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
- primitive_desc(const desc &adesc, const engine &aengine) {
- mkldnn_primitive_desc_t result;
- error::wrap_c_api(mkldnn_primitive_desc_create(
- &result, &adesc.data, aengine.get(), nullptr),
- "could not create an RNN forward primitive descriptor");
- reset(result);
- }
-
- memory::primitive_desc src_layer_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t cdesc;
- const_mkldnn_primitive_desc_t const_cdesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(src_pd), 0);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
- "could not clone an src layer primitive descriptor");
- adesc.reset(cdesc);
- return adesc;
- }
-
- memory::primitive_desc src_iter_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t cdesc;
- const_mkldnn_primitive_desc_t const_cdesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(src_pd), 1);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
- "could not clone a src iter primitive descriptor");
- adesc.reset(cdesc);
- return adesc;
- }
-
- memory::primitive_desc weights_layer_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t cdesc;
- const_mkldnn_primitive_desc_t const_cdesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(weights_pd), 0);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
- "could not clone a weights primitive descriptor");
- adesc.reset(cdesc);
- return adesc;
- }
-
- memory::primitive_desc weights_src_iter_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t cdesc;
- const_mkldnn_primitive_desc_t const_cdesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(weights_pd), 1);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
- "could not clone a weights primitive descriptor");
- adesc.reset(cdesc);
- return adesc;
- }
-
- memory::primitive_desc bias_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t cdesc;
- const_mkldnn_primitive_desc_t const_cdesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(weights_pd), 2);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
- "could not clone a bias primitive descriptor");
- adesc.reset(cdesc);
- return adesc;
- }
-
- memory::primitive_desc workspace_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t ldesc;
- const_mkldnn_primitive_desc_t const_ldesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(workspace_pd), 0);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&ldesc, const_ldesc),
- "could not clone a workspace primitive descriptor");
- adesc.reset(ldesc);
- return adesc;
- }
-
- memory::primitive_desc dst_layer_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t cdesc;
- const_mkldnn_primitive_desc_t const_cdesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(dst_pd), 0);
- error::wrap_c_api(
- mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
- "could not clone a dst last layer primitive descriptor");
- adesc.reset(cdesc);
- return adesc;
- }
-
- memory::primitive_desc dst_iter_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t cdesc;
- const_mkldnn_primitive_desc_t const_cdesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(dst_pd), 1);
- error::wrap_c_api(
- mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
- "could not clone a dst last iteration primitive descriptor");
- adesc.reset(cdesc);
- return adesc;
- }
-
- engine get_engine() { return engine::query(*this); }
- };
-
- rnn_forward(const primitive_desc &aprimitive_desc,
- const primitive::at &src_layer,
- const primitive::at &src_iter,
- const primitive::at &weights_layer,
- const primitive::at &weights_iter,
- const primitive::at &bias,
- const memory &dst_layer,
- const memory &dst_iter,
- const memory &workspace) {
- mkldnn_primitive_t result;
- mkldnn_primitive_at_t inputs[5];
- const_mkldnn_primitive_t outputs[3];
- int idx = 0;
- inputs[idx++] = src_layer.data;
- if (!is_null_memory(src_iter.data.primitive)) inputs[idx++] = src_iter.data;
- inputs[idx++] = weights_layer.data;
- inputs[idx++] = weights_iter.data;
- if (!is_null_memory(bias.data.primitive)) inputs[idx++] = bias.data;
-
- idx = 0;
- outputs[idx++] = dst_layer.get();
- if (!is_null_memory(dst_iter.get())) outputs[idx++] = dst_iter.get();
- if (!is_null_memory(workspace.get())) outputs[idx++] = workspace.get();
-
- error::wrap_c_api(mkldnn_primitive_create(
- &result, aprimitive_desc.get(), inputs, outputs),
- "could not create an RNN forward primitive");
- reset(result);
- }
-};
-
-struct rnn_backward : public primitive {
- struct desc {
- mkldnn_rnn_desc_t data;
- desc(prop_kind aprop_kind,
- rnn_cell::desc cell,
- const rnn_direction direction,
- const memory::desc &src_layer_desc,
- const memory::desc &src_iter_desc,
- const memory::desc &weights_layer_desc,
- const memory::desc &weights_iter_desc,
- const memory::desc &bias_desc,
- const memory::desc &dst_layer_desc,
- const memory::desc &dst_iter_desc,
- const memory::desc &diff_src_layer_desc,
- const memory::desc &diff_src_iter_desc,
- const memory::desc &diff_weights_layer_desc,
- const memory::desc &diff_weights_iter_desc,
- const memory::desc &diff_bias_desc,
- const memory::desc &diff_dst_layer_desc,
- const memory::desc &diff_dst_iter_desc) {
- error::wrap_c_api(
- mkldnn_rnn_backward_desc_init(&data,
- mkldnn::convert_to_c(aprop_kind),
- cell,
- mkldnn::convert_to_c(direction),
- &src_layer_desc.data,
- &src_iter_desc.data,
- &weights_layer_desc.data,
- &weights_iter_desc.data,
- &bias_desc.data,
- &dst_layer_desc.data,
- &dst_iter_desc.data,
- &diff_src_layer_desc.data,
- &diff_src_iter_desc.data,
- &diff_weights_layer_desc.data,
- &diff_weights_iter_desc.data,
- &diff_bias_desc.data,
- &diff_dst_layer_desc.data,
- &diff_dst_iter_desc.data),
- "could not create an RNN backward descriptor");
- }
- };
- struct primitive_desc : public handle<mkldnn_primitive_desc_t> {
- primitive_desc(const desc &adesc, const engine &aengine) {
- mkldnn_primitive_desc_t result;
- error::wrap_c_api(
- mkldnn_primitive_desc_create(
- &result, &adesc.data, aengine.get(), nullptr),
- "could not create an RNN backward primitive descriptor");
- reset(result);
- }
-
- memory::primitive_desc src_layer_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t cdesc;
- const_mkldnn_primitive_desc_t const_cdesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(src_pd), 0);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
- "could not clone an src layer primitive descriptor");
- adesc.reset(cdesc);
- return adesc;
- }
-
- memory::primitive_desc src_iter_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t cdesc;
- const_mkldnn_primitive_desc_t const_cdesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(src_pd), 1);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
- "could not clone a src iter primitive descriptor");
- adesc.reset(cdesc);
- return adesc;
- }
-
- memory::primitive_desc weights_layer_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t cdesc;
- const_mkldnn_primitive_desc_t const_cdesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(weights_pd), 0);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
- "could not clone a weights primitive descriptor");
- adesc.reset(cdesc);
- return adesc;
- }
-
- memory::primitive_desc weights_iter_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t cdesc;
- const_mkldnn_primitive_desc_t const_cdesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(weights_pd), 1);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
- "could not clone a weights primitive descriptor");
- adesc.reset(cdesc);
- return adesc;
- }
-
- memory::primitive_desc bias_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t cdesc;
- const_mkldnn_primitive_desc_t const_cdesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(weights_pd), 2);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
- "could not clone a bias primitive descriptor");
- adesc.reset(cdesc);
- return adesc;
- }
-
- memory::primitive_desc dst_layer_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t cdesc;
- const_mkldnn_primitive_desc_t const_cdesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(dst_pd), 0);
- error::wrap_c_api(
- mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
- "could not clone a dst last layer primitive descriptor");
- adesc.reset(cdesc);
- return adesc;
- }
-
- memory::primitive_desc dst_iter_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t cdesc;
- const_mkldnn_primitive_desc_t const_cdesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(dst_pd), 1);
- error::wrap_c_api(
- mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
- "could not clone a dst last iteration primitive descriptor");
- adesc.reset(cdesc);
- return adesc;
- }
-
- memory::primitive_desc diff_src_layer_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t cdesc;
- const_mkldnn_primitive_desc_t const_cdesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(diff_src_pd), 0);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
- "could not clone an src_layer primitive descriptor");
- adesc.reset(cdesc);
- return adesc;
- }
-
- memory::primitive_desc diff_src_iter_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t cdesc;
- const_mkldnn_primitive_desc_t const_cdesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(diff_src_pd), 1);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
- "could not clone a src iter primitive descriptor");
- adesc.reset(cdesc);
- return adesc;
- }
-
- memory::primitive_desc diff_weights_layer_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t cdesc;
- const_mkldnn_primitive_desc_t const_cdesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(diff_weights_pd), 0);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
- "could not clone a weights primitive descriptor");
- adesc.reset(cdesc);
- return adesc;
- }
-
- memory::primitive_desc diff_weights_iter_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t cdesc;
- const_mkldnn_primitive_desc_t const_cdesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(diff_weights_pd), 1);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
- "could not clone a weights primitive descriptor");
- adesc.reset(cdesc);
- return adesc;
- }
-
- memory::primitive_desc diff_bias_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t cdesc;
- const_mkldnn_primitive_desc_t const_cdesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(diff_weights_pd), 2);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
- "could not clone a bias primitive descriptor");
- adesc.reset(cdesc);
- return adesc;
- }
-
- memory::primitive_desc diff_dst_layer_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t cdesc;
- const_mkldnn_primitive_desc_t const_cdesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(diff_dst_pd), 0);
- error::wrap_c_api(
- mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
- "could not clone a dst last layer primitive descriptor");
- adesc.reset(cdesc);
- return adesc;
- }
-
- memory::primitive_desc diff_dst_iter_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t cdesc;
- const_mkldnn_primitive_desc_t const_cdesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(diff_dst_pd), 1);
- error::wrap_c_api(
- mkldnn_primitive_desc_clone(&cdesc, const_cdesc),
- "could not clone a dst last iteration primitive descriptor");
- adesc.reset(cdesc);
- return adesc;
- }
-
- memory::primitive_desc workspace_primitive_desc() const {
- memory::primitive_desc adesc;
- mkldnn_primitive_desc_t ldesc;
- const_mkldnn_primitive_desc_t const_ldesc =
- mkldnn_primitive_desc_query_pd(
- get(), mkldnn::convert_to_c(workspace_pd), 0);
- error::wrap_c_api(mkldnn_primitive_desc_clone(&ldesc, const_ldesc),
- "could not clone a workspace primitive descriptor");
- adesc.reset(ldesc);
- return adesc;
- }
-
- engine get_engine() { return engine::query(*this); }
- };
- // With last iteration (with and without input src_iter)
- rnn_backward(const primitive_desc &aprimitive_desc,
- const primitive::at &src_layer,
- const primitive::at &src_iter,
- const primitive::at &weights_layer,
- const primitive::at &weights_iter,
- const primitive::at &bias,
- const primitive::at &dst_layer,
- const primitive::at &dst_iter,
- const memory &diff_src_layer,
- const memory &diff_src_iter,
- const memory &diff_weights_layer,
- const memory &diff_weights_iter,
- const memory &diff_bias,
- const primitive::at &diff_dst_layer,
- const primitive::at &diff_dst_iter,
- const primitive::at &workspace) {
- mkldnn_primitive_t result;
- mkldnn_primitive_at_t inputs[10];
- const_mkldnn_primitive_t outputs[5];
- int idx = 0;
- inputs[idx] = src_layer.data;
- if (!is_null_memory(src_iter.data.primitive)) inputs[idx++] = src_iter.data;
- inputs[idx++] = weights_layer.data;
- inputs[idx++] = weights_iter.data;
- if (!is_null_memory(bias.data.primitive)) inputs[idx++] = bias.data;
- inputs[idx] = dst_layer.data;
- if (!is_null_memory(dst_iter.data.primitive)) inputs[idx++] = dst_iter.data;
- inputs[idx] = diff_dst_layer.data;
- if (!is_null_memory(diff_dst_iter.data.primitive))
- inputs[idx++] = diff_dst_iter.data;
- inputs[idx] = workspace.data;
-
- idx = 0;
- outputs[idx] = diff_src_layer.get();
- if (!is_null_memory(diff_src_iter.get()))
- outputs[idx++] = diff_src_iter.get();
- outputs[idx] = diff_weights_layer.get();
- outputs[idx] = diff_weights_iter.get();
- if (!is_null_memory(diff_bias.get())) outputs[idx] = diff_bias.get();
- error::wrap_c_api(mkldnn_primitive_create(
- &result, aprimitive_desc.get(), inputs, outputs),
- "could not create an RNN backward primitive");
- reset(result);
- }
-};
-
-/// @}
-/// @} Primitives
-
-/// @addtogroup cpp_api_stream Stream
-/// @{
-
-#ifndef DOXYGEN_SHOULD_SKIP_THIS
-template <>
-struct handle_traits<mkldnn_stream_t> {
- static constexpr auto destructor = &mkldnn_stream_destroy;
-};
-#endif
-
-struct stream : public handle<mkldnn_stream_t> {
- using handle::handle;
-
- enum kind {
- any = mkldnn_stream_kind_t::mkldnn_any_stream,
- eager = mkldnn_stream_kind_t::mkldnn_eager,
- lazy = mkldnn_stream_kind_t::mkldnn_lazy
- };
-
- static mkldnn_stream_kind_t convert_to_c(kind akind) {
- return static_cast<mkldnn_stream_kind_t>(akind);
- }
- /// Constructs a stream.
- stream(kind akind) {
- mkldnn_stream_t astream;
- error::wrap_c_api(mkldnn_stream_create(&astream, convert_to_c(akind)),
- "could not create a stream");
- reset(astream);
- }
-
- /// Submits a vector of primitives to a stream for computations.
- ///
- /// @param primitives The vector of primitives to submit.
- /// @returns The stream.
- stream &submit(std::vector<primitive> primitives) {
- // TODO: find a proper way to convert vector<primitive> to
- // vector<mkldnn_primitive_t>
- if (primitives.size() == 0) return *this;
- std::vector<mkldnn_primitive_t> c_api_primitives;
- c_api_primitives.reserve(primitives.size());
- auto convert_to_c = [](primitive p) { return p.get(); };
- std::transform(primitives.begin(),
- primitives.end(),
- std::back_inserter(c_api_primitives),
- convert_to_c);
-
- mkldnn_primitive_t c_api_error_primitive;
- error::wrap_c_api(mkldnn_stream_submit(get(),
- c_api_primitives.size(),
- &c_api_primitives[0],
- &c_api_error_primitive),
- "could not submit primitives to a stream",
- &c_api_error_primitive);
-
- return *this;
- }
-
- /// Waits for all computations submitted to the stream to complete.
- ///
- /// @param block Specifies whether the operation should wait indefinitely or
- /// return
- /// immediately.
- /// @returns @c true if all computations completed.
- /// @returns @c false if not all computations completed.
- bool wait(bool block = true) {
- mkldnn_primitive_t c_api_error_primitive;
- mkldnn_status_t status =
- mkldnn_stream_wait(get(), block, &c_api_error_primitive);
- if (status != mkldnn_success && status != mkldnn_try_again)
- error::wrap_c_api(
- status, "could not wait on a stream", &c_api_error_primitive);
- return (status == mkldnn_success);
- }
-
- stream &rerun() {
- mkldnn_primitive_t c_api_error_primitive;
- error::wrap_c_api(mkldnn_stream_rerun(get(), &c_api_error_primitive),
- "could not rerun a stream",
- &c_api_error_primitive);
- return *this;
- }
-};
-
-/// @}
-
-/// @} C++ API
-
-} // namespace mkldnn
-
-#endif
From 2a636529c9d69a9d3f17dc9f566b44212bf9b1f3 Mon Sep 17 00:00:00 2001
From: Wu Yi <typhoonzero1986@gmail.com>
Date: Thu, 17 May 2018 13:37:40 +0800
Subject: [PATCH 156/195] fix cmake error (#10729)
* fix cmake error
* update fix
---
paddle/fluid/operators/CMakeLists.txt | 12 +++++++-----
1 file changed, 7 insertions(+), 5 deletions(-)
diff --git a/paddle/fluid/operators/CMakeLists.txt b/paddle/fluid/operators/CMakeLists.txt
index d38a9ce587..eb559114e9 100644
--- a/paddle/fluid/operators/CMakeLists.txt
+++ b/paddle/fluid/operators/CMakeLists.txt
@@ -186,11 +186,7 @@ endif()
add_subdirectory(detail)
if(WITH_DISTRIBUTE)
- if(WITH_GPU)
- op_library(gen_nccl_id_op DEPS nccl_common)
- else()
- set(DEPS_OPS ${DEPS_OPS} gen_nccl_id_op)
- endif()
+
set(DISTRIBUTE_DEPS sendrecvop_grpc grpc++_unsecure grpc_unsecure gpr cares zlib protobuf)
set(DISTRIBUTE_COMPILE_FLAGS "-Wno-non-virtual-dtor -Wno-error=non-virtual-dtor -Wno-error=delete-non-virtual-dtor")
op_library(send_op DEPS ${DISTRIBUTE_DEPS})
@@ -208,6 +204,12 @@ if(WITH_DISTRIBUTE)
set_source_files_properties(send_recv_op_test.cc PROPERTIES COMPILE_FLAGS ${DISTRIBUTE_COMPILE_FLAGS})
cc_test(test_send_recv SRCS send_recv_op_test.cc DEPS prefetch_op send_op listen_and_serv_op sum_op executor)
cc_test(test_send_nccl_id SRCS test_send_nccl_id.cc DEPS send_op listen_and_serv_op executor)
+ if(WITH_GPU)
+ op_library(gen_nccl_id_op DEPS nccl_common sendrecvop_grpc)
+ set_source_files_properties(gen_nccl_id_op.cc PROPERTIES COMPILE_FLAGS ${DISTRIBUTE_COMPILE_FLAGS})
+ else()
+ set(DEPS_OPS ${DEPS_OPS} gen_nccl_id_op)
+ endif()
else()
set(DEPS_OPS ${DEPS_OPS} send_op prefetch_op recv_op listen_and_serv_op send_vars_op send_barrier_op gen_nccl_id_op)
endif()
From 3d1953d855787f56e88406b69f6d6e90eb2bc533 Mon Sep 17 00:00:00 2001
From: chengduoZH <zhaochengduo@163.com>
Date: Thu, 17 May 2018 13:43:13 +0800
Subject: [PATCH 157/195] fix timeline
---
tools/timeline.py | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/tools/timeline.py b/tools/timeline.py
index 8cd6353d46..b413bb6fe0 100644
--- a/tools/timeline.py
+++ b/tools/timeline.py
@@ -171,7 +171,7 @@ if args.timeline_path:
profile_paths = profile_path.split(',')
profile_dict = dict()
-if len(profile_path) == 1:
+if len(profile_paths) == 1:
with open(profile_path, 'r') as f:
profile_s = f.read()
profile_pb = profiler_pb2.Profile()
From bbd7580e04f984cb4885c1512fc87387c95d42a5 Mon Sep 17 00:00:00 2001
From: Kexin Zhao <kexin.zhao.paddle@gmail.com>
Date: Wed, 16 May 2018 23:40:13 -0700
Subject: [PATCH 158/195] simplify recognize digits example code (#10722)
---
.../recognize_digits/test_recognize_digits_conv.py | 14 ++++----------
.../recognize_digits/test_recognize_digits_mlp.py | 14 ++++----------
2 files changed, 8 insertions(+), 20 deletions(-)
diff --git a/python/paddle/fluid/tests/book/high-level-api/recognize_digits/test_recognize_digits_conv.py b/python/paddle/fluid/tests/book/high-level-api/recognize_digits/test_recognize_digits_conv.py
index f252a7e2b9..2aac70463c 100644
--- a/python/paddle/fluid/tests/book/high-level-api/recognize_digits/test_recognize_digits_conv.py
+++ b/python/paddle/fluid/tests/book/high-level-api/recognize_digits/test_recognize_digits_conv.py
@@ -71,24 +71,18 @@ def train(use_cuda, train_program, save_dirname):
if isinstance(event, fluid.EndEpochEvent):
test_reader = paddle.batch(
paddle.dataset.mnist.test(), batch_size=BATCH_SIZE)
- test_metrics = trainer.test(
+ avg_cost, acc = trainer.test(
reader=test_reader, feed_order=['img', 'label'])
- avg_cost_set = test_metrics[0]
- acc_set = test_metrics[1]
-
- # get test acc and loss
- acc = numpy.array(acc_set).mean()
- avg_cost = numpy.array(avg_cost_set).mean()
print("avg_cost: %s" % avg_cost)
print("acc : %s" % acc)
- if float(acc) > 0.2: # Smaller value to increase CI speed
+ if acc > 0.2: # Smaller value to increase CI speed
trainer.save_params(save_dirname)
else:
print('BatchID {0}, Test Loss {1:0.2}, Acc {2:0.2}'.format(
- event.epoch + 1, float(avg_cost), float(acc)))
- if math.isnan(float(avg_cost)):
+ event.epoch + 1, avg_cost, acc))
+ if math.isnan(avg_cost):
sys.exit("got NaN loss, training failed.")
elif isinstance(event, fluid.EndStepEvent):
print("Step {0}, Epoch {1} Metrics {2}".format(
diff --git a/python/paddle/fluid/tests/book/high-level-api/recognize_digits/test_recognize_digits_mlp.py b/python/paddle/fluid/tests/book/high-level-api/recognize_digits/test_recognize_digits_mlp.py
index 9427a772f5..3265315799 100644
--- a/python/paddle/fluid/tests/book/high-level-api/recognize_digits/test_recognize_digits_mlp.py
+++ b/python/paddle/fluid/tests/book/high-level-api/recognize_digits/test_recognize_digits_mlp.py
@@ -55,24 +55,18 @@ def train(use_cuda, train_program, save_dirname):
if isinstance(event, fluid.EndEpochEvent):
test_reader = paddle.batch(
paddle.dataset.mnist.test(), batch_size=BATCH_SIZE)
- test_metrics = trainer.test(
+ avg_cost, acc = trainer.test(
reader=test_reader, feed_order=['img', 'label'])
- avg_cost_set = test_metrics[0]
- acc_set = test_metrics[1]
-
- # get test acc and loss
- acc = numpy.array(acc_set).mean()
- avg_cost = numpy.array(avg_cost_set).mean()
print("avg_cost: %s" % avg_cost)
print("acc : %s" % acc)
- if float(acc) > 0.2: # Smaller value to increase CI speed
+ if acc > 0.2: # Smaller value to increase CI speed
trainer.save_params(save_dirname)
else:
print('BatchID {0}, Test Loss {1:0.2}, Acc {2:0.2}'.format(
- event.epoch + 1, float(avg_cost), float(acc)))
- if math.isnan(float(avg_cost)):
+ event.epoch + 1, avg_cost, acc))
+ if math.isnan(avg_cost):
sys.exit("got NaN loss, training failed.")
train_reader = paddle.batch(
From e8d24aa144b1f68436e98f4b343aa9d975e67717 Mon Sep 17 00:00:00 2001
From: qiaolongfei <qiaolongfei@baidu.com>
Date: Thu, 17 May 2018 15:13:17 +0800
Subject: [PATCH 159/195] Inferencer support parallel_executor
---
python/paddle/fluid/inferencer.py | 12 ++++++++++--
python/paddle/fluid/trainer.py | 12 ++++++------
2 files changed, 16 insertions(+), 8 deletions(-)
diff --git a/python/paddle/fluid/inferencer.py b/python/paddle/fluid/inferencer.py
index 56c008d1af..8c6dbd3b5a 100644
--- a/python/paddle/fluid/inferencer.py
+++ b/python/paddle/fluid/inferencer.py
@@ -17,6 +17,7 @@ import core
import executor
import framework
import io
+import parallel_executor
import unique_name
from trainer import check_and_get_place
@@ -24,7 +25,7 @@ __all__ = ['Inferencer', ]
class Inferencer(object):
- def __init__(self, infer_func, param_path, place=None):
+ def __init__(self, infer_func, param_path, place=None, parallel=False):
"""
:param infer_func: a function that will return predict Variable
:param param_path: the path where the inference model is saved by fluid.io.save_params
@@ -32,13 +33,20 @@ class Inferencer(object):
"""
self.param_path = param_path
self.scope = core.Scope()
+ self.parallel = parallel
+ self.place = check_and_get_place(place)
self.inference_program = framework.Program()
with framework.program_guard(self.inference_program):
with unique_name.guard():
self.predict_var = infer_func()
- self.exe = executor.Executor(check_and_get_place(place))
+ if parallel:
+ self.exe = parallel_executor.ParallelExecutor(
+ use_cuda=isinstance(self.place, core.CUDAPlace),
+ loss_name=self.predict_var.name)
+ else:
+ self.exe = executor.Executor(self.place)
with executor.scope_guard(self.scope):
# load params from param_path into scope
io.load_params(self.exe, param_path, self.inference_program)
diff --git a/python/paddle/fluid/trainer.py b/python/paddle/fluid/trainer.py
index d158d58632..f4292208c9 100644
--- a/python/paddle/fluid/trainer.py
+++ b/python/paddle/fluid/trainer.py
@@ -12,18 +12,18 @@
# See the License for the specific language governing permissions and
# limitations under the License.
+import contextlib
import os
+
import core
-import framework
-import executor
+
import data_feeder
-import contextlib
+import executor
+import framework
import io
-import unique_name
-import parallel_executor
-
# optimizer is same as the parameter of Trainer.__init__. Rename it to opt_module
import optimizer as opt_module
+import parallel_executor
from transpiler import distribute_transpiler
__all__ = [
From 57734901d91532248e1c1f87e1d4585c9719cbc7 Mon Sep 17 00:00:00 2001
From: Yancey1989 <yancey1989@gmail.com>
Date: Thu, 17 May 2018 16:48:54 +0800
Subject: [PATCH 160/195] use cdn to speed up thirdparty package download
---
cmake/external/boost.cmake | 2 +-
cmake/external/mklml.cmake | 2 +-
paddle/scripts/paddle_build.sh | 1 -
3 files changed, 2 insertions(+), 3 deletions(-)
diff --git a/cmake/external/boost.cmake b/cmake/external/boost.cmake
index 10662fc967..499682f644 100644
--- a/cmake/external/boost.cmake
+++ b/cmake/external/boost.cmake
@@ -24,7 +24,7 @@ set(BOOST_PROJECT "extern_boost")
# So we use 1.41.0 here.
set(BOOST_VER "1.41.0")
set(BOOST_TAR "boost_1_41_0")
-set(BOOST_URL "http://paddlepaddledeps.bj.bcebos.com/${BOOST_TAR}.tar.gz")
+set(BOOST_URL "http://paddlepaddledeps.cdn.bcebos.com/${BOOST_TAR}.tar.gz")
set(BOOST_SOURCES_DIR ${THIRD_PARTY_PATH}/boost)
set(BOOST_DOWNLOAD_DIR "${BOOST_SOURCES_DIR}/src/${BOOST_PROJECT}")
set(BOOST_INCLUDE_DIR "${BOOST_DOWNLOAD_DIR}/${BOOST_TAR}" CACHE PATH "boost include directory." FORCE)
diff --git a/cmake/external/mklml.cmake b/cmake/external/mklml.cmake
index cebde27504..e9a37b52e6 100644
--- a/cmake/external/mklml.cmake
+++ b/cmake/external/mklml.cmake
@@ -28,7 +28,7 @@ INCLUDE(ExternalProject)
SET(MKLML_PROJECT "extern_mklml")
SET(MKLML_VER "mklml_lnx_2018.0.3.20180406")
-SET(MKLML_URL "http://paddlepaddledeps.bj.bcebos.com/${MKLML_VER}.tgz")
+SET(MKLML_URL "http://paddlepaddledeps.cdn.bcebos.com/${MKLML_VER}.tgz")
SET(MKLML_SOURCE_DIR "${THIRD_PARTY_PATH}/mklml")
SET(MKLML_DOWNLOAD_DIR "${MKLML_SOURCE_DIR}/src/${MKLML_PROJECT}")
SET(MKLML_DST_DIR "mklml")
diff --git a/paddle/scripts/paddle_build.sh b/paddle/scripts/paddle_build.sh
index 58a30ab3e5..e5af42ed57 100755
--- a/paddle/scripts/paddle_build.sh
+++ b/paddle/scripts/paddle_build.sh
@@ -95,7 +95,6 @@ function cmake_gen() {
-DWITH_AVX=${WITH_AVX:-OFF}
-DWITH_GOLANG=${WITH_GOLANG:-OFF}
-DCUDA_ARCH_NAME=${CUDA_ARCH_NAME:-All}
- -DWITH_SWIG_PY=ON
-DWITH_C_API=${WITH_C_API:-OFF}
-DWITH_PYTHON=${WITH_PYTHON:-ON}
-DWITH_SWIG_PY=${WITH_SWIG_PY:-ON}
From 5f1333058cad70fb242eb32c115c540f4480ea4b Mon Sep 17 00:00:00 2001
From: Jacek Czaja <jacek.czaja@intel.com>
Date: Mon, 14 May 2018 16:57:33 +0200
Subject: [PATCH 161/195] - Draft of reuse of pooling mkldnn operator
- Finished draft of pooling reusing of operators
- Using gethash in PoolGrad added
- Removed diagnostic
- Added pool mkldnn grad reusing of primitives
- Added diagnostic
- Removed diagnostic
- added dependency to mkldnn data type for pooling mkldnn
- Added mkldnn memory data type determining based on template type of op
- Compilation warning fix
- codying style fixes
---
paddle/fluid/operators/pool_mkldnn_op.cc | 229 +++++++++++++++--------
paddle/fluid/platform/mkldnn_helper.h | 10 +
2 files changed, 163 insertions(+), 76 deletions(-)
diff --git a/paddle/fluid/operators/pool_mkldnn_op.cc b/paddle/fluid/operators/pool_mkldnn_op.cc
index 63eaaedcd5..60e936298d 100644
--- a/paddle/fluid/operators/pool_mkldnn_op.cc
+++ b/paddle/fluid/operators/pool_mkldnn_op.cc
@@ -18,6 +18,26 @@ limitations under the License. */
namespace paddle {
namespace operators {
+using mkldnn::memory; // Note: paddle has also "memory" namespace
+using mkldnn::pooling_forward;
+using mkldnn::pooling_backward;
+
+// Generate keys for storing/retriving primitives for this operator
+// TODO(jczaja): Make hashing function more optimial
+static std::string gethash(memory::dims& input_dims, std::string& pooling_type,
+ std::vector<int>& ksize, std::vector<int>& strides,
+ std::vector<int>& paddings, std::string suffix) {
+ auto dims2str = [](memory::dims& operand_dims) {
+ std::string dstr = "";
+ for (size_t i = 0; i < operand_dims.size(); ++i) {
+ dstr += std::to_string(operand_dims[i]) + "-";
+ }
+ return dstr;
+ };
+ return dims2str(input_dims) + dims2str(ksize) + dims2str(strides) +
+ dims2str(paddings) + pooling_type + suffix;
+}
+
template <typename T>
class PoolMKLDNNOpKernel : public paddle::framework::OpKernel<T> {
public:
@@ -34,10 +54,6 @@ class PoolMKLDNNOpKernel : public paddle::framework::OpKernel<T> {
// Get an unique name from "argument" name of "Out" variable
// This name will be used as key when saving info into device context
- const std::string key = ctx.op().Output("Out");
- const std::string key_pool_pd = key + "@pool_pd";
- const std::string key_pool_workspace_memory =
- key + "@pool_workspace_memory";
std::string pooling_type = ctx.Attr<std::string>("pooling_type");
std::vector<int> ksize = ctx.Attr<std::vector<int>>("ksize");
@@ -63,37 +79,71 @@ class PoolMKLDNNOpKernel : public paddle::framework::OpKernel<T> {
std::vector<int> src_tz = paddle::framework::vectorize2int(input->dims());
std::vector<int> dst_tz = paddle::framework::vectorize2int(output->dims());
- // TODO(pzelazko-intel): support more formats
- auto src_md = platform::MKLDNNMemDesc(src_tz, mkldnn::memory::f32,
- mkldnn::memory::format::nchw);
- auto dst_md = platform::MKLDNNMemDesc(dst_tz, mkldnn::memory::f32,
- mkldnn::memory::format::nchw);
-
- std::shared_ptr<mkldnn::pooling_forward::primitive_desc> pool_pd =
- CreatePrimitiveDesc(src_md, dst_md, strides, paddings, ksize,
- pooling_type, mkldnn_engine);
-
- // save pool_pd into global device context to be referred in backward path
- dev_ctx.SetBlob(key_pool_pd, pool_pd);
-
- std::shared_ptr<mkldnn::memory> workspace_memory =
- CreateWorkspaceMemory(pool_pd, pooling_type, mkldnn_engine);
-
- // save pool_workspace_memory to be referred in backward path
- dev_ctx.SetBlob(key_pool_workspace_memory, workspace_memory);
-
- auto src_memory =
- mkldnn::memory({src_md, mkldnn_engine},
- static_cast<void*>(const_cast<T*>(input_data)));
- auto dst_memory =
- mkldnn::memory({dst_md, mkldnn_engine},
- static_cast<void*>(const_cast<T*>(output_data)));
+ const std::string key = gethash(src_tz, pooling_type, ksize, strides,
+ paddings, ctx.op().Output("Out"));
+ const std::string key_pool_p = key + "@pool_p";
+ const std::string key_pool_pd = key + "@pool_pd";
+ const std::string key_pool_src_mem_p = key + "@pool_src_mem_p";
+ const std::string key_pool_dst_mem_p = key + "@pool_dst_mem_p";
+ const std::string key_pool_workspace_memory =
+ key + "@pool_workspace_memory";
- auto pool_prim = mkldnn::pooling_forward(*pool_pd, src_memory, dst_memory,
- *workspace_memory);
+ auto pool_p =
+ std::static_pointer_cast<pooling_forward>(dev_ctx.GetBlob(key_pool_p));
+ if (pool_p == nullptr) {
+ // TODO(pzelazko-intel): support more formats
+
+ auto src_md =
+ platform::MKLDNNMemDesc(src_tz, platform::MKLDNNGetDataType<T>(),
+ mkldnn::memory::format::nchw);
+ auto dst_md =
+ platform::MKLDNNMemDesc(dst_tz, platform::MKLDNNGetDataType<T>(),
+ mkldnn::memory::format::nchw);
+
+ std::shared_ptr<pooling_forward::primitive_desc> pool_pd =
+ CreatePrimitiveDesc(src_md, dst_md, strides, paddings, ksize,
+ pooling_type, mkldnn_engine);
+
+ // save pool_pd into global device context to be referred in backward path
+ dev_ctx.SetBlob(key_pool_pd, pool_pd);
+
+ std::shared_ptr<mkldnn::memory> workspace_memory =
+ CreateWorkspaceMemory(pool_pd, pooling_type, mkldnn_engine);
+
+ // save pool_workspace_memory to be referred in backward path
+ dev_ctx.SetBlob(key_pool_workspace_memory, workspace_memory);
+
+ auto pool_src_memory_p = std::make_shared<memory>(
+ memory::primitive_desc{src_md, mkldnn_engine},
+ static_cast<void*>(const_cast<T*>(input_data)));
+ dev_ctx.SetBlob(key_pool_src_mem_p, pool_src_memory_p);
+
+ auto pool_dst_memory_p = std::make_shared<memory>(
+ memory::primitive_desc{dst_md, mkldnn_engine},
+ static_cast<void*>(output_data));
+ dev_ctx.SetBlob(key_pool_dst_mem_p, pool_dst_memory_p);
+
+ pool_p = std::make_shared<pooling_forward>(
+ *pool_pd, *(pool_src_memory_p.get()), *(pool_dst_memory_p.get()),
+ *workspace_memory);
+ dev_ctx.SetBlob(key_pool_p, pool_p);
+ } else {
+ // Primitives already exist
+ auto pool_src_memory_p =
+ std::static_pointer_cast<memory>(dev_ctx.GetBlob(key_pool_src_mem_p));
+ PADDLE_ENFORCE(pool_src_memory_p != nullptr,
+ "Fail to find pooling src mem_p in device context");
+ auto pool_dst_memory_p =
+ std::static_pointer_cast<memory>(dev_ctx.GetBlob(key_pool_dst_mem_p));
+ PADDLE_ENFORCE(pool_dst_memory_p != nullptr,
+ "Fail to find pooling dst mem_p in device context");
+ pool_src_memory_p->set_data_handle(
+ reinterpret_cast<void*>(const_cast<T*>(input_data)));
+ pool_dst_memory_p->set_data_handle(output_data);
+ }
// push primitive to stream and wait until it's executed
- std::vector<mkldnn::primitive> pipeline{pool_prim};
+ std::vector<mkldnn::primitive> pipeline{*(pool_p.get())};
mkldnn::stream(mkldnn::stream::kind::eager).submit(pipeline).wait();
}
@@ -120,9 +170,10 @@ class PoolMKLDNNOpKernel : public paddle::framework::OpKernel<T> {
mkldnn::memory::primitive_desc workspace_md =
pooling_type == "max"
? pool_pd->workspace_primitive_desc()
- : mkldnn::memory::primitive_desc(
- {{}, mkldnn::memory::f32, mkldnn::memory::format::nchw},
- engine);
+ : mkldnn::memory::primitive_desc({{},
+ platform::MKLDNNGetDataType<T>(),
+ mkldnn::memory::format::nchw},
+ engine);
auto p_workspace_memory = new mkldnn::memory(workspace_md);
return std::unique_ptr<mkldnn::memory>(p_workspace_memory);
@@ -140,13 +191,6 @@ class PoolMKLDNNGradOpKernel : public paddle::framework::OpKernel<T> {
const Tensor* out_grad = ctx.Input<Tensor>(framework::GradVarName("Out"));
Tensor* in_x_grad = ctx.Output<Tensor>(framework::GradVarName("X"));
- // Get an unique name from "argument" name of "Out" variable
- // This name will be used as key when referring info from device context
- const std::string key = ctx.op().Input("Out");
- const std::string key_pool_pd = key + "@pool_pd";
- const std::string key_pool_workspace_memory =
- key + "@pool_workspace_memory";
-
std::string pooling_type = ctx.Attr<std::string>("pooling_type");
std::vector<int> ksize = ctx.Attr<std::vector<int>>("ksize");
std::vector<int> strides = ctx.Attr<std::vector<int>>("strides");
@@ -171,43 +215,76 @@ class PoolMKLDNNGradOpKernel : public paddle::framework::OpKernel<T> {
std::vector<int> diff_dst_tz =
paddle::framework::vectorize2int(out_grad->dims());
- auto diff_src_md = platform::MKLDNNMemDesc(diff_src_tz, mkldnn::memory::f32,
- mkldnn::memory::format::nchw);
- auto diff_dst_md = platform::MKLDNNMemDesc(diff_dst_tz, mkldnn::memory::f32,
- mkldnn::memory::format::nchw);
-
- // Retrieve pool_pd/pool_workspace_memory from device context
- auto pool_pd =
- std::static_pointer_cast<mkldnn::pooling_forward::primitive_desc>(
- dev_ctx.GetBlob(key_pool_pd));
- PADDLE_ENFORCE(pool_pd != nullptr,
- "Fail to find pool_pd in device context");
-
- auto workspace_memory = std::static_pointer_cast<mkldnn::memory>(
- dev_ctx.GetBlob(key_pool_workspace_memory));
- PADDLE_ENFORCE(workspace_memory != nullptr,
- "Fail to find workspace_memory in device context");
-
- auto pool_bwd_desc = mkldnn::pooling_backward::desc(
- pooling_type == "max" ? mkldnn::algorithm::pooling_max
- : mkldnn::algorithm::pooling_avg,
- diff_src_md, diff_dst_md, strides, ksize, paddings, paddings,
- mkldnn::padding_kind::zero);
- auto pool_bwd_pd = mkldnn::pooling_backward::primitive_desc(
- pool_bwd_desc, mkldnn_engine, *pool_pd);
-
- auto diff_src_memory =
- mkldnn::memory({diff_src_md, mkldnn_engine},
- static_cast<void*>(const_cast<T*>(in_x_grad_data)));
- auto diff_dst_memory =
- mkldnn::memory({diff_dst_md, mkldnn_engine},
- static_cast<void*>(const_cast<T*>(out_grad_data)));
+ // Get an unique name from "argument" name of "Out" variable
+ // This name will be used as key when referring info from device context
+ const std::string key = gethash(diff_src_tz, pooling_type, ksize, strides,
+ paddings, ctx.op().Input("Out"));
+ const std::string key_pool_bwd_p = key + "@pool_bwd_p";
+ const std::string key_pool_diff_src_mem_p = key + "@pool_diff_src_mem_p";
+ const std::string key_pool_diff_dst_mem_p = key + "@pool_diff_dst_mem_p";
+ const std::string key_pool_pd = key + "@pool_pd";
+ const std::string key_pool_workspace_memory =
+ key + "@pool_workspace_memory";
- auto bwd_prim = mkldnn::pooling_backward(
- pool_bwd_pd, diff_dst_memory, *workspace_memory, diff_src_memory);
+ auto pool_bwd_p = std::static_pointer_cast<pooling_backward>(
+ dev_ctx.GetBlob(key_pool_bwd_p));
+ if (pool_bwd_p == nullptr) {
+ auto diff_src_md =
+ platform::MKLDNNMemDesc(diff_src_tz, platform::MKLDNNGetDataType<T>(),
+ mkldnn::memory::format::nchw);
+ auto diff_dst_md =
+ platform::MKLDNNMemDesc(diff_dst_tz, platform::MKLDNNGetDataType<T>(),
+ mkldnn::memory::format::nchw);
+ // Retrieve pool_pd/pool_workspace_memory from device context
+ auto pool_pd =
+ std::static_pointer_cast<mkldnn::pooling_forward::primitive_desc>(
+ dev_ctx.GetBlob(key_pool_pd));
+ PADDLE_ENFORCE(pool_pd != nullptr,
+ "Fail to find pool_pd in device context");
+
+ auto workspace_memory = std::static_pointer_cast<mkldnn::memory>(
+ dev_ctx.GetBlob(key_pool_workspace_memory));
+ PADDLE_ENFORCE(workspace_memory != nullptr,
+ "Fail to find workspace_memory in device context");
+
+ auto pool_diff_src_memory_p = std::make_shared<memory>(memory(
+ {diff_src_md, mkldnn_engine}, static_cast<void*>(in_x_grad_data)));
+ dev_ctx.SetBlob(key_pool_diff_src_mem_p, pool_diff_src_memory_p);
+
+ auto pool_diff_dst_memory_p = std::make_shared<memory>(
+ memory({diff_dst_md, mkldnn_engine},
+ static_cast<void*>(const_cast<T*>(out_grad_data))));
+ dev_ctx.SetBlob(key_pool_diff_dst_mem_p, pool_diff_dst_memory_p);
+
+ auto pool_bwd_desc = mkldnn::pooling_backward::desc(
+ pooling_type == "max" ? mkldnn::algorithm::pooling_max
+ : mkldnn::algorithm::pooling_avg,
+ diff_src_md, diff_dst_md, strides, ksize, paddings, paddings,
+ mkldnn::padding_kind::zero);
+ auto pool_bwd_pd = mkldnn::pooling_backward::primitive_desc(
+ pool_bwd_desc, mkldnn_engine, *pool_pd);
+
+ pool_bwd_p = std::make_shared<pooling_backward>(
+ pool_bwd_pd, *(pool_diff_dst_memory_p.get()), *workspace_memory,
+ *(pool_diff_src_memory_p));
+ dev_ctx.SetBlob(key_pool_bwd_p, pool_bwd_p);
+ } else {
+ // Primitives already exist
+ auto pool_diff_src_memory_p = std::static_pointer_cast<memory>(
+ dev_ctx.GetBlob(key_pool_diff_src_mem_p));
+ PADDLE_ENFORCE(pool_diff_src_memory_p != nullptr,
+ "Fail to find pooling src mem_p in device context");
+ auto pool_diff_dst_memory_p = std::static_pointer_cast<memory>(
+ dev_ctx.GetBlob(key_pool_diff_dst_mem_p));
+ PADDLE_ENFORCE(pool_diff_dst_memory_p != nullptr,
+ "Fail to find pooling dst mem_p in device context");
+ pool_diff_src_memory_p->set_data_handle(
+ reinterpret_cast<void*>(in_x_grad_data));
+ pool_diff_dst_memory_p->set_data_handle(const_cast<T*>(out_grad_data));
+ }
// push primitive to stream and wait until it's executed
- std::vector<mkldnn::primitive> pipeline{bwd_prim};
+ std::vector<mkldnn::primitive> pipeline{*(pool_bwd_p.get())};
mkldnn::stream(mkldnn::stream::kind::eager).submit(pipeline).wait();
} // Compute()
};
diff --git a/paddle/fluid/platform/mkldnn_helper.h b/paddle/fluid/platform/mkldnn_helper.h
index 23f1d615da..56ed5912a1 100644
--- a/paddle/fluid/platform/mkldnn_helper.h
+++ b/paddle/fluid/platform/mkldnn_helper.h
@@ -71,5 +71,15 @@ inline bool CanMKLDNNBeUsed(const framework::ExecutionContext& ctx) {
return use_mkldnn && platform::is_cpu_place(ctx.GetPlace());
}
+template <typename Type>
+mkldnn::memory::data_type MKLDNNGetDataType() {
+ return mkldnn::memory::data_undef;
+}
+
+template <>
+inline mkldnn::memory::data_type MKLDNNGetDataType<float>() {
+ return mkldnn::memory::f32;
+}
+
} // namespace platform
} // namespace paddle
From feed94e20f614373986bd749da536caff38fdb5d Mon Sep 17 00:00:00 2001
From: qiaolongfei <qiaolongfei@baidu.com>
Date: Thu, 17 May 2018 19:50:51 +0800
Subject: [PATCH 162/195] should load parameter before create parallel_executor
---
python/paddle/fluid/inferencer.py | 33 +++++++++++--------
.../fit_a_line/test_fit_a_line.py | 2 +-
.../test_recognize_digits_conv.py | 2 +-
.../test_recognize_digits_mlp.py | 2 +-
.../word2vec/no_test_word2vec_new_api.py | 14 ++++----
5 files changed, 29 insertions(+), 24 deletions(-)
diff --git a/python/paddle/fluid/inferencer.py b/python/paddle/fluid/inferencer.py
index 8c6dbd3b5a..0c2620d692 100644
--- a/python/paddle/fluid/inferencer.py
+++ b/python/paddle/fluid/inferencer.py
@@ -12,6 +12,8 @@
# See the License for the specific language governing permissions and
# limitations under the License.
+import contextlib
+
import core
import executor
@@ -41,31 +43,36 @@ class Inferencer(object):
with unique_name.guard():
self.predict_var = infer_func()
+ with self._prog_and_scope_guard():
+ # load params from param_path into scope
+ io.load_params(executor.Executor(self.place), param_path)
+
if parallel:
- self.exe = parallel_executor.ParallelExecutor(
- use_cuda=isinstance(self.place, core.CUDAPlace),
- loss_name=self.predict_var.name)
+ with self._prog_and_scope_guard():
+ self.exe = parallel_executor.ParallelExecutor(
+ use_cuda=isinstance(self.place, core.CUDAPlace),
+ loss_name=self.predict_var.name)
else:
self.exe = executor.Executor(self.place)
- with executor.scope_guard(self.scope):
- # load params from param_path into scope
- io.load_params(self.exe, param_path, self.inference_program)
- def infer(self, inputs, return_numpy=True):
+ def infer(self, inputs):
"""
:param inputs: a map of {"input_name": input_var} that will be feed into the inference program
to get the predict value
- :param return_numpy: if return numpy value for row tensor
:return: the predict value of the inference model
"""
if not isinstance(inputs, dict):
raise ValueError(
"inputs should be a map of {'input_name': input_var}")
- with executor.scope_guard(self.scope):
- results = self.exe.run(self.inference_program,
- feed=inputs,
- fetch_list=[self.predict_var],
- return_numpy=return_numpy)
+ with self._prog_and_scope_guard():
+ results = self.exe.run(feed=inputs,
+ fetch_list=[self.predict_var.name])
return results
+
+ @contextlib.contextmanager
+ def _prog_and_scope_guard(self):
+ with framework.program_guard(main_program=self.inference_program):
+ with executor.scope_guard(self.scope):
+ yield
diff --git a/python/paddle/fluid/tests/book/high-level-api/fit_a_line/test_fit_a_line.py b/python/paddle/fluid/tests/book/high-level-api/fit_a_line/test_fit_a_line.py
index fbcf2a282f..973142ccdf 100644
--- a/python/paddle/fluid/tests/book/high-level-api/fit_a_line/test_fit_a_line.py
+++ b/python/paddle/fluid/tests/book/high-level-api/fit_a_line/test_fit_a_line.py
@@ -94,7 +94,7 @@ def infer(use_cuda, inference_program, save_dirname=None):
tensor_x = numpy.random.uniform(0, 10, [batch_size, 13]).astype("float32")
results = inferencer.infer({'x': tensor_x})
- print("infer results: ", results[0])
+ print("infer results: ", numpy.array(results[0]))
def main(use_cuda):
diff --git a/python/paddle/fluid/tests/book/high-level-api/recognize_digits/test_recognize_digits_conv.py b/python/paddle/fluid/tests/book/high-level-api/recognize_digits/test_recognize_digits_conv.py
index f252a7e2b9..c1bae77ec4 100644
--- a/python/paddle/fluid/tests/book/high-level-api/recognize_digits/test_recognize_digits_conv.py
+++ b/python/paddle/fluid/tests/book/high-level-api/recognize_digits/test_recognize_digits_conv.py
@@ -118,7 +118,7 @@ def infer(use_cuda, inference_program, save_dirname=None):
results = inferencer.infer({'img': tensor_img})
- print("infer results: ", results[0])
+ print("infer results: ", numpy.array(results[0]))
def main(use_cuda):
diff --git a/python/paddle/fluid/tests/book/high-level-api/recognize_digits/test_recognize_digits_mlp.py b/python/paddle/fluid/tests/book/high-level-api/recognize_digits/test_recognize_digits_mlp.py
index 9427a772f5..ae915b8458 100644
--- a/python/paddle/fluid/tests/book/high-level-api/recognize_digits/test_recognize_digits_mlp.py
+++ b/python/paddle/fluid/tests/book/high-level-api/recognize_digits/test_recognize_digits_mlp.py
@@ -99,7 +99,7 @@ def infer(use_cuda, inference_program, save_dirname=None):
results = inferencer.infer({'img': tensor_img})
- print("infer results: ", results[0])
+ print("infer results: ", numpy.array(results[0]))
def main(use_cuda):
diff --git a/python/paddle/fluid/tests/book/high-level-api/word2vec/no_test_word2vec_new_api.py b/python/paddle/fluid/tests/book/high-level-api/word2vec/no_test_word2vec_new_api.py
index 4f861e5aae..6d7495e4dd 100644
--- a/python/paddle/fluid/tests/book/high-level-api/word2vec/no_test_word2vec_new_api.py
+++ b/python/paddle/fluid/tests/book/high-level-api/word2vec/no_test_word2vec_new_api.py
@@ -127,14 +127,12 @@ def infer(use_cuda, inference_program, save_path):
third_word = create_random_lodtensor(lod, place, low=0, high=dict_size - 1)
fourth_word = create_random_lodtensor(lod, place, low=0, high=dict_size - 1)
- result = inferencer.infer(
- {
- 'firstw': first_word,
- 'secondw': second_word,
- 'thirdw': third_word,
- 'forthw': fourth_word
- },
- return_numpy=False)
+ result = inferencer.infer({
+ 'firstw': first_word,
+ 'secondw': second_word,
+ 'thirdw': third_word,
+ 'forthw': fourth_word
+ })
print(np.array(result[0]))
From 8023bc766b8d1c39f280295abaeac7a374face72 Mon Sep 17 00:00:00 2001
From: baiyfbupt <baiyfbupt@gmail.com>
Date: Thu, 17 May 2018 14:58:44 +0000
Subject: [PATCH 163/195] fix index
---
paddle/fluid/operators/roi_pool_op.cu | 14 +++++++-------
1 file changed, 7 insertions(+), 7 deletions(-)
diff --git a/paddle/fluid/operators/roi_pool_op.cu b/paddle/fluid/operators/roi_pool_op.cu
index a699d21542..972dc36c11 100644
--- a/paddle/fluid/operators/roi_pool_op.cu
+++ b/paddle/fluid/operators/roi_pool_op.cu
@@ -38,10 +38,10 @@ __global__ void GPUROIPoolForward(
int index = blockIdx.x * blockDim.x + threadIdx.x;
int offset = blockDim.x * gridDim.x;
for (size_t i = index; i < nthreads; i += offset) {
- int pw = index % pooled_width;
- int ph = (index / pooled_width) % pooled_height;
- int c = (index / pooled_width / pooled_height) % channels;
- int n = index / pooled_width / pooled_height / channels;
+ int pw = i % pooled_width;
+ int ph = (i / pooled_width) % pooled_height;
+ int c = (i / pooled_width / pooled_height) % channels;
+ int n = i / pooled_width / pooled_height / channels;
const int64_t* offset_input_rois = input_rois + n * kROISize;
int roi_batch_ind = roi_batch_id_data[n];
@@ -65,7 +65,6 @@ __global__ void GPUROIPoolForward(
int wend = static_cast<int>(ceil(static_cast<double>(pw + 1) *
static_cast<double>(roi_width) /
static_cast<double>(pooled_width)));
-
hstart = min(max(hstart + roi_start_h, 0), height);
hend = min(max(hend + roi_start_h, 0), height);
wstart = min(max(wstart + roi_start_w, 0), width);
@@ -85,9 +84,9 @@ __global__ void GPUROIPoolForward(
}
}
}
- output_data[index] = maxval;
+ output_data[i] = maxval;
if (argmax_data) {
- argmax_data[index] = maxidx;
+ argmax_data[i] = maxidx;
}
}
}
@@ -144,6 +143,7 @@ class GPUROIPoolOpKernel : public framework::OpKernel<T> {
int width = in_dims[3];
int rois_num = rois->dims()[0];
+
if (rois_num == 0) return;
int output_size = out->numel();
From 93c470034a96b4963b3b0740105ef5f92ac70f96 Mon Sep 17 00:00:00 2001
From: chengduo <zhaochengduo@baidu.com>
Date: Fri, 18 May 2018 02:46:38 +0800
Subject: [PATCH 164/195] fix DataTransFunc (#10752)
---
paddle/fluid/framework/data_device_transform.cc | 6 ++++--
1 file changed, 4 insertions(+), 2 deletions(-)
diff --git a/paddle/fluid/framework/data_device_transform.cc b/paddle/fluid/framework/data_device_transform.cc
index 85dbb39e6f..a876725ac0 100644
--- a/paddle/fluid/framework/data_device_transform.cc
+++ b/paddle/fluid/framework/data_device_transform.cc
@@ -36,9 +36,11 @@ void TransDataDevice(const Tensor& in, const platform::Place& dst_place,
VLOG(3) << "DeviceTransform in, src_place " << in.place()
<< " dst_place: " << dst_place;
auto* dev_ctx = GetDeviceContext(in.place(), dst_place);
- dev_ctx->Wait();
+
TensorCopy(in, dst_place, *dev_ctx, out);
- dev_ctx->Wait();
+ if (platform::is_gpu_place(in.place()) && platform::is_cpu_place(dst_place)) {
+ dev_ctx->Wait();
+ }
}
} // namespace framework
From 868bdc97713169f3525a014f71a4dd3e52e85008 Mon Sep 17 00:00:00 2001
From: Lei Wang <bestwanglei@gmail.com>
Date: Thu, 17 May 2018 16:46:53 -0700
Subject: [PATCH 165/195] Build: fix build error when WITH_FLUID_ONLY and
WITH_GPU both set as OFF. (#10756)
---
paddle/fluid/operators/CMakeLists.txt | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/paddle/fluid/operators/CMakeLists.txt b/paddle/fluid/operators/CMakeLists.txt
index eb559114e9..ac1f3f44ae 100644
--- a/paddle/fluid/operators/CMakeLists.txt
+++ b/paddle/fluid/operators/CMakeLists.txt
@@ -203,8 +203,8 @@ if(WITH_DISTRIBUTE)
set_source_files_properties(send_barrier_op.cc PROPERTIES COMPILE_FLAGS ${DISTRIBUTE_COMPILE_FLAGS})
set_source_files_properties(send_recv_op_test.cc PROPERTIES COMPILE_FLAGS ${DISTRIBUTE_COMPILE_FLAGS})
cc_test(test_send_recv SRCS send_recv_op_test.cc DEPS prefetch_op send_op listen_and_serv_op sum_op executor)
- cc_test(test_send_nccl_id SRCS test_send_nccl_id.cc DEPS send_op listen_and_serv_op executor)
if(WITH_GPU)
+ cc_test(test_send_nccl_id SRCS test_send_nccl_id.cc DEPS send_op listen_and_serv_op executor)
op_library(gen_nccl_id_op DEPS nccl_common sendrecvop_grpc)
set_source_files_properties(gen_nccl_id_op.cc PROPERTIES COMPILE_FLAGS ${DISTRIBUTE_COMPILE_FLAGS})
else()
From d2d671e34107e1193fa4e30314178bb73a6a8c3e Mon Sep 17 00:00:00 2001
From: qiaolongfei <qiaolongfei@baidu.com>
Date: Fri, 18 May 2018 09:48:46 +0800
Subject: [PATCH 166/195] add comment
---
python/paddle/fluid/inferencer.py | 1 +
1 file changed, 1 insertion(+)
diff --git a/python/paddle/fluid/inferencer.py b/python/paddle/fluid/inferencer.py
index 0c2620d692..894f6dbfad 100644
--- a/python/paddle/fluid/inferencer.py
+++ b/python/paddle/fluid/inferencer.py
@@ -32,6 +32,7 @@ class Inferencer(object):
:param infer_func: a function that will return predict Variable
:param param_path: the path where the inference model is saved by fluid.io.save_params
:param place: place to do the inference
+ :param parallel: use parallel_executor to run the inference, it will use multi CPU/GPU.
"""
self.param_path = param_path
self.scope = core.Scope()
From 1d7f91e867b598bc4cde7dd5f0ef0410ca569bd5 Mon Sep 17 00:00:00 2001
From: baiyfbupt <baiyfbupt@gmail.com>
Date: Fri, 18 May 2018 02:14:09 +0000
Subject: [PATCH 167/195] fix roi_pool gpu_backward kernel
---
paddle/fluid/operators/roi_pool_op.cu | 8 ++++----
1 file changed, 4 insertions(+), 4 deletions(-)
diff --git a/paddle/fluid/operators/roi_pool_op.cu b/paddle/fluid/operators/roi_pool_op.cu
index 972dc36c11..50450b62f7 100644
--- a/paddle/fluid/operators/roi_pool_op.cu
+++ b/paddle/fluid/operators/roi_pool_op.cu
@@ -101,10 +101,10 @@ __global__ void GPUROIPoolBackward(
int index = blockIdx.x * blockDim.x + threadIdx.x;
int offset = blockDim.x * gridDim.x;
for (int i = index; i < nthreads; i += offset) {
- int pw = index % pooled_width;
- int ph = (index / pooled_width) % pooled_height;
- int c = (index / pooled_width / pooled_height) % channels;
- int n = index / pooled_width / pooled_height / channels;
+ int pw = i % pooled_width;
+ int ph = (i / pooled_width) % pooled_height;
+ int c = (i / pooled_width / pooled_height) % channels;
+ int n = i / pooled_width / pooled_height / channels;
int roi_batch_ind = roi_batch_id_data[n];
int input_offset = (roi_batch_ind * channels + c) * height * width;
From ebc7303990a74ca8de91af4d68543614825d25f2 Mon Sep 17 00:00:00 2001
From: Wu Yi <typhoonzero1986@gmail.com>
Date: Fri, 18 May 2018 10:21:30 +0800
Subject: [PATCH 168/195] listen_and_serv use local scope (#10663)
* listen_and_serv use localscope
* fix ut
---
paddle/fluid/framework/executor.cc | 15 +++++++++------
paddle/fluid/framework/executor.h | 3 ++-
paddle/fluid/inference/tests/test_helper.h | 4 ++--
paddle/fluid/operators/detail/grpc_server.cc | 2 +-
paddle/fluid/operators/listen_and_serv_op.cc | 7 +++----
paddle/fluid/operators/send_recv_op_test.cc | 9 +++++++--
.../fluid/tests/unittests/test_dist_train.py | 9 ++++++---
7 files changed, 30 insertions(+), 19 deletions(-)
diff --git a/paddle/fluid/framework/executor.cc b/paddle/fluid/framework/executor.cc
index ce91d7a826..4e431561f8 100644
--- a/paddle/fluid/framework/executor.cc
+++ b/paddle/fluid/framework/executor.cc
@@ -228,7 +228,8 @@ static bool has_fetch_operators(
void Executor::Run(const ProgramDesc& program, Scope* scope,
std::map<std::string, const LoDTensor*>* feed_targets,
std::map<std::string, LoDTensor*>* fetch_targets,
- bool create_vars, const std::string& feed_holder_name,
+ bool create_local_scope, bool create_vars,
+ const std::string& feed_holder_name,
const std::string& fetch_holder_name) {
platform::RecordBlock b(kProgramId);
bool has_feed_ops =
@@ -290,8 +291,9 @@ void Executor::Run(const ProgramDesc& program, Scope* scope,
}
auto ctx = Prepare(*copy_program, 0);
- RunPreparedContext(ctx.get(), scope, feed_targets, fetch_targets, create_vars,
- feed_holder_name, fetch_holder_name);
+ RunPreparedContext(ctx.get(), scope, feed_targets, fetch_targets,
+ create_local_scope, create_vars, feed_holder_name,
+ fetch_holder_name);
}
std::unique_ptr<ExecutorPrepareContext> Executor::Prepare(
@@ -366,8 +368,9 @@ void Executor::RunPreparedContext(ExecutorPrepareContext* ctx, Scope* scope,
void Executor::RunPreparedContext(
ExecutorPrepareContext* ctx, Scope* scope,
std::map<std::string, const LoDTensor*>* feed_targets,
- std::map<std::string, LoDTensor*>* fetch_targets, bool create_vars,
- const std::string& feed_holder_name, const std::string& fetch_holder_name) {
+ std::map<std::string, LoDTensor*>* fetch_targets, bool create_local_scope,
+ bool create_vars, const std::string& feed_holder_name,
+ const std::string& fetch_holder_name) {
auto& global_block = ctx->prog_.Block(ctx->block_id_);
PADDLE_ENFORCE(
@@ -387,7 +390,7 @@ void Executor::RunPreparedContext(
}
}
- RunPreparedContext(ctx, scope, create_vars, create_vars);
+ RunPreparedContext(ctx, scope, create_local_scope, create_vars);
// obtain the data of fetch_targets from fetch_holder
for (auto* op : global_block.AllOps()) {
diff --git a/paddle/fluid/framework/executor.h b/paddle/fluid/framework/executor.h
index 4a3d637e2d..0c3c23611d 100644
--- a/paddle/fluid/framework/executor.h
+++ b/paddle/fluid/framework/executor.h
@@ -57,7 +57,7 @@ class Executor {
void Run(const ProgramDesc& program, Scope* scope,
std::map<std::string, const LoDTensor*>* feed_targets,
std::map<std::string, LoDTensor*>* fetch_targets,
- bool create_vars = true,
+ bool create_local_scope = true, bool create_vars = true,
const std::string& feed_holder_name = "feed",
const std::string& fetch_holder_name = "fetch");
@@ -76,6 +76,7 @@ class Executor {
void RunPreparedContext(ExecutorPrepareContext* ctx, Scope* scope,
std::map<std::string, const LoDTensor*>* feed_targets,
std::map<std::string, LoDTensor*>* fetch_targets,
+ bool create_local_scope = true,
bool create_vars = true,
const std::string& feed_holder_name = "feed",
const std::string& fetch_holder_name = "fetch");
diff --git a/paddle/fluid/inference/tests/test_helper.h b/paddle/fluid/inference/tests/test_helper.h
index b02e5c99f0..e33eb7f170 100644
--- a/paddle/fluid/inference/tests/test_helper.h
+++ b/paddle/fluid/inference/tests/test_helper.h
@@ -208,10 +208,10 @@ void TestInference(const std::string& dirname,
if (PrepareContext) {
ctx = executor.Prepare(*inference_program, 0);
executor.RunPreparedContext(ctx.get(), scope, &feed_targets,
- &fetch_targets, CreateVars);
+ &fetch_targets, true, CreateVars);
} else {
executor.Run(*inference_program, scope, &feed_targets, &fetch_targets,
- CreateVars);
+ true, CreateVars);
}
// Enable the profiler
diff --git a/paddle/fluid/operators/detail/grpc_server.cc b/paddle/fluid/operators/detail/grpc_server.cc
index d09f8479b7..eb114a47d9 100644
--- a/paddle/fluid/operators/detail/grpc_server.cc
+++ b/paddle/fluid/operators/detail/grpc_server.cc
@@ -184,7 +184,7 @@ class RequestPrefetch final : public RequestBase {
framework::Scope* local_scope = &scope_->NewScope();
auto* var = local_scope->FindVar(var_name);
InitializeVariable(var, var_desc->GetType());
- executor_->RunPreparedContext(prefetch_ctx_, scope_, false, false);
+ executor_->RunPreparedContext(prefetch_ctx_, scope_);
SerializeToByteBuffer(var_name, var, *dev_ctx_, &reply);
diff --git a/paddle/fluid/operators/listen_and_serv_op.cc b/paddle/fluid/operators/listen_and_serv_op.cc
index abc88d3eb1..57eb5d9a0e 100644
--- a/paddle/fluid/operators/listen_and_serv_op.cc
+++ b/paddle/fluid/operators/listen_and_serv_op.cc
@@ -57,8 +57,7 @@ static void ParallelExecuteBlocks(
framework::Async([&executor, &prepared, &program, &scope, idx]() {
int run_block = idx; // thread local
try {
- executor->RunPreparedContext(prepared[run_block].get(), scope,
- false, false);
+ executor->RunPreparedContext(prepared[run_block].get(), scope);
} catch (std::exception &e) {
LOG(ERROR) << "run sub program error " << e.what();
}
@@ -211,8 +210,8 @@ static void AsyncUpdateThread(
}
auto fs = framework::Async([var_name, &executor, &v, prepared] {
try {
- executor->RunPreparedContext(prepared, v.second->GetMutableLocalScope(),
- false, false);
+ executor->RunPreparedContext(prepared,
+ v.second->GetMutableLocalScope());
} catch (std::exception &e) {
LOG(ERROR) << "run sub program error " << e.what();
}
diff --git a/paddle/fluid/operators/send_recv_op_test.cc b/paddle/fluid/operators/send_recv_op_test.cc
index eb51f301bf..d5303eaf50 100644
--- a/paddle/fluid/operators/send_recv_op_test.cc
+++ b/paddle/fluid/operators/send_recv_op_test.cc
@@ -92,12 +92,16 @@ void InitSelectedRowsInScope(const p::CPUPlace &place, f::Scope *scope) {
void AddOp(const std::string &type, const f::VariableNameMap &inputs,
const f::VariableNameMap &outputs, f::AttributeMap attrs,
- f::BlockDesc *block) {
+ f::BlockDesc *block, bool is_sparse) {
// insert output
for (auto kv : outputs) {
for (auto v : kv.second) {
auto var = block->Var(v);
var->SetDataType(f::proto::VarType::FP32);
+ var->SetPersistable(true);
+ if (is_sparse) {
+ var->SetType(f::proto::VarType::SELECTED_ROWS);
+ }
}
}
@@ -128,7 +132,8 @@ void StartServerNet(bool is_sparse, std::atomic<bool> *initialized) {
auto *optimize_block = program.AppendBlock(root_block);
auto *prefetch_block = program.AppendBlock(root_block);
// X for server side tensors, RX for received tensors, must be of same shape.
- AddOp("sum", {{"X", {"x0", "x1"}}}, {{"Out", {"Out"}}}, {}, optimize_block);
+ AddOp("sum", {{"X", {"x0", "x1"}}}, {{"Out", {"Out"}}}, {}, optimize_block,
+ is_sparse);
f::AttributeMap attrs;
attrs.insert({"endpoint", std::string("127.0.0.1:0")});
attrs.insert({"Fanin", 1});
diff --git a/python/paddle/fluid/tests/unittests/test_dist_train.py b/python/paddle/fluid/tests/unittests/test_dist_train.py
index 77e9a8f7e7..c2393a288c 100644
--- a/python/paddle/fluid/tests/unittests/test_dist_train.py
+++ b/python/paddle/fluid/tests/unittests/test_dist_train.py
@@ -52,15 +52,18 @@ class TestSendOp(unittest.TestCase):
serv = layers.ListenAndServ(
"127.0.0.1:0", ["X"], optimizer_mode=False)
with serv.do():
+ out_var = main.global_block().create_var(
+ name="scale_0.tmp_0",
+ psersistable=True,
+ dtype="float32",
+ shape=[32, 32])
x = layers.data(
shape=[32, 32],
dtype='float32',
name="X",
append_batch_size=False)
fluid.initializer.Constant(value=1.0)(x, main.global_block())
- o = layers.scale(x=x, scale=10.0)
- main.global_block().create_var(
- name=o.name, psersistable=False, dtype=o.dtype, shape=o.shape)
+ layers.scale(x=x, scale=10.0, out=out_var)
self.server_exe = fluid.Executor(place)
self.server_exe.run(main)
From eb7d87545e14112fea1ef82d4d0eb60d3faa4a10 Mon Sep 17 00:00:00 2001
From: Qiao Longfei <qiaolongfei@baidu.com>
Date: Fri, 18 May 2018 13:06:34 +0800
Subject: [PATCH 169/195] add trainer.stop and fix a bug for
train_by_parallel_executor (#10762)
---
.../fit_a_line/test_fit_a_line.py | 26 +++++++++----------
python/paddle/fluid/trainer.py | 13 +++++++---
2 files changed, 22 insertions(+), 17 deletions(-)
diff --git a/python/paddle/fluid/tests/book/high-level-api/fit_a_line/test_fit_a_line.py b/python/paddle/fluid/tests/book/high-level-api/fit_a_line/test_fit_a_line.py
index 973142ccdf..4c8505acf3 100644
--- a/python/paddle/fluid/tests/book/high-level-api/fit_a_line/test_fit_a_line.py
+++ b/python/paddle/fluid/tests/book/high-level-api/fit_a_line/test_fit_a_line.py
@@ -57,22 +57,20 @@ def train(use_cuda, train_program, save_dirname):
optimizer=fluid.optimizer.SGD(learning_rate=0.001))
def event_handler(event):
- if isinstance(event, fluid.EndEpochEvent):
- test_metrics = trainer.test(
- reader=test_reader, feed_order=['x', 'y'])
- print test_metrics
- '''
-
- ...
- ['25.768919467926025']
- ['15.343549569447836']
- ...
-
- '''
- if float(test_metrics[0]) < 20.0:
+ if isinstance(event, fluid.EndStepEvent):
+ if event.step == 10:
+ test_metrics = trainer.test(
+ reader=test_reader, feed_order=['x', 'y'])
+ print test_metrics
+ '''
+ ...
+ ['25.768919467926025']
+ ['15.343549569447836']
+ ...
+ '''
if save_dirname is not None:
trainer.save_params(save_dirname)
- return
+ trainer.stop()
trainer.train(
reader=train_reader,
diff --git a/python/paddle/fluid/trainer.py b/python/paddle/fluid/trainer.py
index f4292208c9..7da123dd92 100644
--- a/python/paddle/fluid/trainer.py
+++ b/python/paddle/fluid/trainer.py
@@ -100,6 +100,7 @@ class Trainer(object):
param_path=None,
place=None,
parallel=False):
+ self.__stop = False
self.parallel = parallel
# 1. we need to generate a framework.Program by calling
# program_func. Reference: fluid.program_guard in
@@ -210,6 +211,12 @@ class Trainer(object):
'TRAINING_ROLE environment variable must be either TRAINER or PSERVER'
)
+ def stop(self):
+ """
+ stop training
+ """
+ self.__stop = True
+
def train(self, num_epochs, event_handler, reader=None, feed_order=None):
"""
Train the model.
@@ -289,6 +296,8 @@ class Trainer(object):
for epoch_id in range(num_epochs):
event_handler(BeginEpochEvent(epoch_id))
for step_id, data in enumerate(reader()):
+ if self.__stop:
+ return
begin_event = BeginStepEvent(epoch_id, step_id)
event_handler(begin_event)
if begin_event.fetch_metrics:
@@ -327,9 +336,7 @@ class Trainer(object):
feeder = data_feeder.DataFeeder(
feed_list=feed_var_list, place=self.place)
reader = feeder.decorate_reader(reader, multi_devices=True)
- for epoch_id in range(num_epochs):
- self._train_by_any_executor(event_handler, pe, num_epochs,
- reader)
+ self._train_by_any_executor(event_handler, pe, num_epochs, reader)
def _get_parallel_executor(self):
return getattr(self, 'parallel_executor', None)
From 871bc43064421a2b1c92f1638cef6792c25aa663 Mon Sep 17 00:00:00 2001
From: Xin Pan <panxin.grad@gmail.com>
Date: Fri, 18 May 2018 17:16:07 +0800
Subject: [PATCH 170/195] Fix a compile error
---
paddle/fluid/operators/CMakeLists.txt | 1 +
1 file changed, 1 insertion(+)
diff --git a/paddle/fluid/operators/CMakeLists.txt b/paddle/fluid/operators/CMakeLists.txt
index ac1f3f44ae..7fce138e3f 100644
--- a/paddle/fluid/operators/CMakeLists.txt
+++ b/paddle/fluid/operators/CMakeLists.txt
@@ -204,6 +204,7 @@ if(WITH_DISTRIBUTE)
set_source_files_properties(send_recv_op_test.cc PROPERTIES COMPILE_FLAGS ${DISTRIBUTE_COMPILE_FLAGS})
cc_test(test_send_recv SRCS send_recv_op_test.cc DEPS prefetch_op send_op listen_and_serv_op sum_op executor)
if(WITH_GPU)
+ set_source_files_properties(test_send_nccl_id.cc PROPERTIES COMPILE_FLAGS ${DISTRIBUTE_COMPILE_FLAGS})
cc_test(test_send_nccl_id SRCS test_send_nccl_id.cc DEPS send_op listen_and_serv_op executor)
op_library(gen_nccl_id_op DEPS nccl_common sendrecvop_grpc)
set_source_files_properties(gen_nccl_id_op.cc PROPERTIES COMPILE_FLAGS ${DISTRIBUTE_COMPILE_FLAGS})
From 17f503726b3829476431d18fc11209a95d3f5909 Mon Sep 17 00:00:00 2001
From: Yancey <yanxu05@baidu.com>
Date: Fri, 18 May 2018 17:32:25 +0800
Subject: [PATCH 171/195] use latest pip version in dev and production Docker
image (#10760)
* use latest pip version
* fix ci
* update by comment
---
Dockerfile | 2 +-
paddle/scripts/docker/build.sh | 2 +-
paddle/scripts/paddle_build.sh | 2 +-
3 files changed, 3 insertions(+), 3 deletions(-)
diff --git a/Dockerfile b/Dockerfile
index 164fe84904..ea39efd00b 100644
--- a/Dockerfile
+++ b/Dockerfile
@@ -70,7 +70,7 @@ RUN localedef -i en_US -f UTF-8 en_US.UTF-8
# specify sphinx version as 1.5.6 and remove -U option for [pip install -U
# sphinx-rtd-theme] since -U option will cause sphinx being updated to newest
# version(1.7.1 for now), which causes building documentation failed.
-RUN pip install --upgrade pip==9.0.3 && \
+RUN easy_install -U pip && \
pip install -U wheel && \
pip install -U docopt PyYAML sphinx==1.5.6 && \
pip install sphinx-rtd-theme==0.1.9 recommonmark
diff --git a/paddle/scripts/docker/build.sh b/paddle/scripts/docker/build.sh
index 7e00bd3848..92b8b90880 100755
--- a/paddle/scripts/docker/build.sh
+++ b/paddle/scripts/docker/build.sh
@@ -198,7 +198,7 @@ EOF
# run paddle version to install python packages first
RUN apt-get update &&\
${NCCL_DEPS}\
- apt-get install -y wget python-pip dmidecode python-tk && pip install -U pip==9.0.3 && \
+ apt-get install -y wget python-pip dmidecode python-tk && easy_install -U pip && \
pip install /*.whl; apt-get install -f -y && \
apt-get clean -y && \
rm -f /*.whl && \
diff --git a/paddle/scripts/paddle_build.sh b/paddle/scripts/paddle_build.sh
index e5af42ed57..3efca04a5c 100755
--- a/paddle/scripts/paddle_build.sh
+++ b/paddle/scripts/paddle_build.sh
@@ -449,7 +449,7 @@ EOF
# run paddle version to install python packages first
RUN apt-get update &&\
${NCCL_DEPS}\
- apt-get install -y wget python-pip dmidecode python-tk && pip install -U pip==9.0.3 && \
+ apt-get install -y wget python-pip dmidecode python-tk && easy_install -U pip && \
pip install /*.whl; apt-get install -f -y && \
apt-get clean -y && \
rm -f /*.whl && \
From 8282d3e0120b22a7c2d5ec4427595322626a13ac Mon Sep 17 00:00:00 2001
From: Xin Pan <panxin.grad@gmail.com>
Date: Fri, 18 May 2018 04:05:04 -0700
Subject: [PATCH 172/195] fix cpp lint
---
paddle/fluid/inference/tests/test_helper.h | 3 +--
1 file changed, 1 insertion(+), 2 deletions(-)
diff --git a/paddle/fluid/inference/tests/test_helper.h b/paddle/fluid/inference/tests/test_helper.h
index 1adbf57d0b..cc1589514a 100644
--- a/paddle/fluid/inference/tests/test_helper.h
+++ b/paddle/fluid/inference/tests/test_helper.h
@@ -236,8 +236,7 @@ void TestInference(const std::string& dirname,
// Disable the profiler and print the timing information
paddle::platform::DisableProfiler(
- paddle::platform::EventSortingKey::kDefault,
- "run_inference_profiler");
+ paddle::platform::EventSortingKey::kDefault, "run_inference_profiler");
paddle::platform::ResetProfiler();
}
From 11b6473c2693e1b965bf4abcdf16a576ef65523b Mon Sep 17 00:00:00 2001
From: daminglu <daming-lu@users.noreply.github.com>
Date: Fri, 18 May 2018 12:02:57 -0700
Subject: [PATCH 173/195] Image classification & word2vec (#10738)
---
.../tests/book/high-level-api/CMakeLists.txt | 1 +
.../image_classification/CMakeLists.txt | 7 ++
.../cifar10_small_test_set.py | 82 +++++++++++++++++++
...py => test_image_classification_resnet.py} | 51 +++++++-----
...gg.py => test_image_classification_vgg.py} | 53 +++++++-----
5 files changed, 152 insertions(+), 42 deletions(-)
create mode 100644 python/paddle/fluid/tests/book/high-level-api/image_classification/CMakeLists.txt
create mode 100644 python/paddle/fluid/tests/book/high-level-api/image_classification/cifar10_small_test_set.py
rename python/paddle/fluid/tests/book/high-level-api/image_classification/{notest_image_classification_resnet.py => test_image_classification_resnet.py} (77%)
rename python/paddle/fluid/tests/book/high-level-api/image_classification/{notest_image_classification_vgg.py => test_image_classification_vgg.py} (72%)
diff --git a/python/paddle/fluid/tests/book/high-level-api/CMakeLists.txt b/python/paddle/fluid/tests/book/high-level-api/CMakeLists.txt
index c2a15bdb3b..da76747f82 100644
--- a/python/paddle/fluid/tests/book/high-level-api/CMakeLists.txt
+++ b/python/paddle/fluid/tests/book/high-level-api/CMakeLists.txt
@@ -8,3 +8,4 @@ endforeach()
add_subdirectory(fit_a_line)
add_subdirectory(recognize_digits)
+add_subdirectory(image_classification)
diff --git a/python/paddle/fluid/tests/book/high-level-api/image_classification/CMakeLists.txt b/python/paddle/fluid/tests/book/high-level-api/image_classification/CMakeLists.txt
new file mode 100644
index 0000000000..673c965b66
--- /dev/null
+++ b/python/paddle/fluid/tests/book/high-level-api/image_classification/CMakeLists.txt
@@ -0,0 +1,7 @@
+file(GLOB TEST_OPS RELATIVE "${CMAKE_CURRENT_SOURCE_DIR}" "test_*.py")
+string(REPLACE ".py" "" TEST_OPS "${TEST_OPS}")
+
+# default test
+foreach(src ${TEST_OPS})
+ py_test(${src} SRCS ${src}.py)
+endforeach()
diff --git a/python/paddle/fluid/tests/book/high-level-api/image_classification/cifar10_small_test_set.py b/python/paddle/fluid/tests/book/high-level-api/image_classification/cifar10_small_test_set.py
new file mode 100644
index 0000000000..7fed6d914f
--- /dev/null
+++ b/python/paddle/fluid/tests/book/high-level-api/image_classification/cifar10_small_test_set.py
@@ -0,0 +1,82 @@
+# Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+"""
+CIFAR dataset.
+
+This module will download dataset from
+https://www.cs.toronto.edu/~kriz/cifar.html and parse train/test set into
+paddle reader creators.
+
+The CIFAR-10 dataset consists of 60000 32x32 colour images in 10 classes,
+with 6000 images per class. There are 50000 training images and 10000 test
+images.
+
+The CIFAR-100 dataset is just like the CIFAR-10, except it has 100 classes
+containing 600 images each. There are 500 training images and 100 testing
+images per class.
+
+"""
+
+import cPickle
+import itertools
+import numpy
+import paddle.v2.dataset.common
+import tarfile
+
+__all__ = ['train10']
+
+URL_PREFIX = 'https://www.cs.toronto.edu/~kriz/'
+CIFAR10_URL = URL_PREFIX + 'cifar-10-python.tar.gz'
+CIFAR10_MD5 = 'c58f30108f718f92721af3b95e74349a'
+
+
+def reader_creator(filename, sub_name, batch_size=None):
+ def read_batch(batch):
+ data = batch['data']
+ labels = batch.get('labels', batch.get('fine_labels', None))
+ assert labels is not None
+ for sample, label in itertools.izip(data, labels):
+ yield (sample / 255.0).astype(numpy.float32), int(label)
+
+ def reader():
+ with tarfile.open(filename, mode='r') as f:
+ names = (each_item.name for each_item in f
+ if sub_name in each_item.name)
+
+ batch_count = 0
+ for name in names:
+ batch = cPickle.load(f.extractfile(name))
+ for item in read_batch(batch):
+ if isinstance(batch_size, int) and batch_count > batch_size:
+ break
+ batch_count += 1
+ yield item
+
+ return reader
+
+
+def train10(batch_size=None):
+ """
+ CIFAR-10 training set creator.
+
+ It returns a reader creator, each sample in the reader is image pixels in
+ [0, 1] and label in [0, 9].
+
+ :return: Training reader creator
+ :rtype: callable
+ """
+ return reader_creator(
+ paddle.v2.dataset.common.download(CIFAR10_URL, 'cifar', CIFAR10_MD5),
+ 'data_batch',
+ batch_size=batch_size)
diff --git a/python/paddle/fluid/tests/book/high-level-api/image_classification/notest_image_classification_resnet.py b/python/paddle/fluid/tests/book/high-level-api/image_classification/test_image_classification_resnet.py
similarity index 77%
rename from python/paddle/fluid/tests/book/high-level-api/image_classification/notest_image_classification_resnet.py
rename to python/paddle/fluid/tests/book/high-level-api/image_classification/test_image_classification_resnet.py
index 17db38797c..1160e500db 100644
--- a/python/paddle/fluid/tests/book/high-level-api/image_classification/notest_image_classification_resnet.py
+++ b/python/paddle/fluid/tests/book/high-level-api/image_classification/test_image_classification_resnet.py
@@ -17,6 +17,7 @@ from __future__ import print_function
import paddle
import paddle.fluid as fluid
import numpy
+import cifar10_small_test_set
def resnet_cifar10(input, depth=32):
@@ -81,46 +82,50 @@ def train_network():
cost = fluid.layers.cross_entropy(input=predict, label=label)
avg_cost = fluid.layers.mean(cost)
accuracy = fluid.layers.accuracy(input=predict, label=label)
- return avg_cost, accuracy
+ return [avg_cost, accuracy]
-def train(use_cuda, save_path):
+def train(use_cuda, train_program, save_dirname):
BATCH_SIZE = 128
EPOCH_NUM = 1
train_reader = paddle.batch(
paddle.reader.shuffle(
- paddle.dataset.cifar.train10(), buf_size=128 * 10),
+ cifar10_small_test_set.train10(batch_size=10), buf_size=128 * 10),
batch_size=BATCH_SIZE)
test_reader = paddle.batch(
paddle.dataset.cifar.test10(), batch_size=BATCH_SIZE)
def event_handler(event):
- if isinstance(event, fluid.EndIteration):
- if (event.batch_id % 10) == 0:
- avg_cost, accuracy = trainer.test(reader=test_reader)
+ if isinstance(event, fluid.EndStepEvent):
+ avg_cost, accuracy = trainer.test(
+ reader=test_reader, feed_order=['pixel', 'label'])
- print('BatchID {1:04}, Loss {2:2.2}, Acc {3:2.2}'.format(
- event.batch_id + 1, avg_cost, accuracy))
+ print('Loss {0:2.2}, Acc {1:2.2}'.format(avg_cost, accuracy))
- if accuracy > 0.01: # Low threshold for speeding up CI
- trainer.params.save(save_path)
- return
+ if accuracy > 0.01: # Low threshold for speeding up CI
+ if save_dirname is not None:
+ trainer.save_params(save_dirname)
+ return
place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
trainer = fluid.Trainer(
- train_network,
+ train_func=train_program,
optimizer=fluid.optimizer.Adam(learning_rate=0.001),
- place=place,
- event_handler=event_handler)
- trainer.train(train_reader, EPOCH_NUM, event_handler=event_handler)
+ place=place)
+ trainer.train(
+ reader=train_reader,
+ num_epochs=EPOCH_NUM,
+ event_handler=event_handler,
+ feed_order=['pixel', 'label'])
-def infer(use_cuda, save_path):
- params = fluid.Params(save_path)
+
+def infer(use_cuda, inference_program, save_dirname=None):
place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
- inferencer = fluid.Inferencer(inference_network, params, place=place)
+ inferencer = fluid.Inferencer(
+ infer_func=inference_program, param_path=save_dirname, place=place)
# The input's dimension of conv should be 4-D or 5-D.
# Use normilized image pixels as input data, which should be in the range
@@ -135,8 +140,14 @@ def main(use_cuda):
if use_cuda and not fluid.core.is_compiled_with_cuda():
return
save_path = "image_classification_resnet.inference.model"
- train(use_cuda, save_path)
- infer(use_cuda, save_path)
+
+ train(
+ use_cuda=use_cuda, train_program=train_network, save_dirname=save_path)
+
+ infer(
+ use_cuda=use_cuda,
+ inference_program=inference_network,
+ save_dirname=save_path)
if __name__ == '__main__':
diff --git a/python/paddle/fluid/tests/book/high-level-api/image_classification/notest_image_classification_vgg.py b/python/paddle/fluid/tests/book/high-level-api/image_classification/test_image_classification_vgg.py
similarity index 72%
rename from python/paddle/fluid/tests/book/high-level-api/image_classification/notest_image_classification_vgg.py
rename to python/paddle/fluid/tests/book/high-level-api/image_classification/test_image_classification_vgg.py
index e83afeed2f..1e3e955ba0 100644
--- a/python/paddle/fluid/tests/book/high-level-api/image_classification/notest_image_classification_vgg.py
+++ b/python/paddle/fluid/tests/book/high-level-api/image_classification/test_image_classification_vgg.py
@@ -17,6 +17,7 @@ from __future__ import print_function
import paddle
import paddle.fluid as fluid
import numpy
+import cifar10_small_test_set
def vgg16_bn_drop(input):
@@ -60,46 +61,48 @@ def train_network():
cost = fluid.layers.cross_entropy(input=predict, label=label)
avg_cost = fluid.layers.mean(cost)
accuracy = fluid.layers.accuracy(input=predict, label=label)
- return avg_cost, accuracy
+ return [avg_cost, accuracy]
-def train(use_cuda, save_path):
+def train(use_cuda, train_program, save_dirname):
BATCH_SIZE = 128
- EPOCH_NUM = 1
-
train_reader = paddle.batch(
paddle.reader.shuffle(
- paddle.dataset.cifar.train10(), buf_size=128 * 10),
+ cifar10_small_test_set.train10(batch_size=10), buf_size=128 * 10),
batch_size=BATCH_SIZE)
test_reader = paddle.batch(
paddle.dataset.cifar.test10(), batch_size=BATCH_SIZE)
def event_handler(event):
- if isinstance(event, fluid.EndIteration):
- if (event.batch_id % 10) == 0:
- avg_cost, accuracy = trainer.test(reader=test_reader)
+ if isinstance(event, fluid.EndStepEvent):
+ avg_cost, accuracy = trainer.test(
+ reader=test_reader, feed_order=['pixel', 'label'])
- print('BatchID {1:04}, Loss {2:2.2}, Acc {3:2.2}'.format(
- event.batch_id + 1, avg_cost, accuracy))
+ print('Loss {0:2.2}, Acc {1:2.2}'.format(avg_cost, accuracy))
- if accuracy > 0.01: # Low threshold for speeding up CI
- trainer.params.save(save_path)
- return
+ if accuracy > 0.01: # Low threshold for speeding up CI
+ if save_dirname is not None:
+ trainer.save_params(save_dirname)
+ return
place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
trainer = fluid.Trainer(
- train_network,
- optimizer=fluid.optimizer.Adam(learning_rate=0.001),
+ train_func=train_program,
place=place,
- event_handler=event_handler)
- trainer.train(train_reader, EPOCH_NUM, event_handler=event_handler)
+ optimizer=fluid.optimizer.Adam(learning_rate=0.001))
+
+ trainer.train(
+ reader=train_reader,
+ num_epochs=1,
+ event_handler=event_handler,
+ feed_order=['pixel', 'label'])
-def infer(use_cuda, save_path):
- params = fluid.Params(save_path)
+def infer(use_cuda, inference_program, save_dirname=None):
place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
- inferencer = fluid.Inferencer(inference_network, params, place=place)
+ inferencer = fluid.Inferencer(
+ infer_func=inference_program, param_path=save_dirname, place=place)
# The input's dimension of conv should be 4-D or 5-D.
# Use normilized image pixels as input data, which should be in the range
@@ -114,8 +117,14 @@ def main(use_cuda):
if use_cuda and not fluid.core.is_compiled_with_cuda():
return
save_path = "image_classification_vgg.inference.model"
- train(use_cuda, save_path)
- infer(use_cuda, save_path)
+
+ train(
+ use_cuda=use_cuda, train_program=train_network, save_dirname=save_path)
+
+ infer(
+ use_cuda=use_cuda,
+ inference_program=inference_network,
+ save_dirname=save_path)
if __name__ == '__main__':
From ae1990731d78c46cde120e42f939ba30ce22630a Mon Sep 17 00:00:00 2001
From: daminglu <daming-lu@users.noreply.github.com>
Date: Fri, 18 May 2018 18:33:48 -0700
Subject: [PATCH 174/195] Test word2vec (#10779)
---
paddle/fluid/inference/tests/test_helper.h | 3 +-
...ec_new_api.py => test_word2vec_new_api.py} | 57 ++++++++++++-------
2 files changed, 39 insertions(+), 21 deletions(-)
rename python/paddle/fluid/tests/book/high-level-api/word2vec/{no_test_word2vec_new_api.py => test_word2vec_new_api.py} (77%)
diff --git a/paddle/fluid/inference/tests/test_helper.h b/paddle/fluid/inference/tests/test_helper.h
index 1adbf57d0b..cc1589514a 100644
--- a/paddle/fluid/inference/tests/test_helper.h
+++ b/paddle/fluid/inference/tests/test_helper.h
@@ -236,8 +236,7 @@ void TestInference(const std::string& dirname,
// Disable the profiler and print the timing information
paddle::platform::DisableProfiler(
- paddle::platform::EventSortingKey::kDefault,
- "run_inference_profiler");
+ paddle::platform::EventSortingKey::kDefault, "run_inference_profiler");
paddle::platform::ResetProfiler();
}
diff --git a/python/paddle/fluid/tests/book/high-level-api/word2vec/no_test_word2vec_new_api.py b/python/paddle/fluid/tests/book/high-level-api/word2vec/test_word2vec_new_api.py
similarity index 77%
rename from python/paddle/fluid/tests/book/high-level-api/word2vec/no_test_word2vec_new_api.py
rename to python/paddle/fluid/tests/book/high-level-api/word2vec/test_word2vec_new_api.py
index 6d7495e4dd..bf86cd9acf 100644
--- a/python/paddle/fluid/tests/book/high-level-api/word2vec/no_test_word2vec_new_api.py
+++ b/python/paddle/fluid/tests/book/high-level-api/word2vec/test_word2vec_new_api.py
@@ -90,7 +90,7 @@ def train_program(is_sparse):
return avg_cost
-def train(use_cuda, train_program, save_path):
+def train(use_cuda, train_program, save_dirname):
train_reader = paddle.batch(
paddle.dataset.imikolov.train(word_dict, N), BATCH_SIZE)
test_reader = paddle.batch(
@@ -99,27 +99,36 @@ def train(use_cuda, train_program, save_path):
place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
def event_handler(event):
- if isinstance(event, fluid.EndEpochEvent):
- outs = trainer.test(reader=test_reader)
+ if isinstance(event, fluid.EndStepEvent):
+ outs = trainer.test(
+ reader=test_reader,
+ feed_order=['firstw', 'secondw', 'thirdw', 'forthw', 'nextw'])
avg_cost = outs[0]
print("loss= ", avg_cost)
- if avg_cost < 5.0:
- trainer.save_params(save_path)
- return
+ if avg_cost < 10.0:
+ trainer.save_params(save_dirname)
+ trainer.stop()
+
if math.isnan(avg_cost):
sys.exit("got NaN loss, training failed.")
trainer = fluid.Trainer(
- train_program, fluid.optimizer.SGD(learning_rate=0.001), place=place)
+ train_func=train_program,
+ optimizer=fluid.optimizer.SGD(learning_rate=0.001),
+ place=place)
+
trainer.train(
- reader=train_reader, num_epochs=1, event_handler=event_handler)
+ reader=train_reader,
+ num_epochs=1,
+ event_handler=event_handler,
+ feed_order=['firstw', 'secondw', 'thirdw', 'forthw', 'nextw'])
-def infer(use_cuda, inference_program, save_path):
+def infer(use_cuda, inference_program, save_dirname=None):
place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
inferencer = fluid.Inferencer(
- infer_func=inference_program, param_path=save_path, place=place)
+ infer_func=inference_program, param_path=save_dirname, place=place)
lod = [0, 1]
first_word = create_random_lodtensor(lod, place, low=0, high=dict_size - 1)
@@ -127,12 +136,14 @@ def infer(use_cuda, inference_program, save_path):
third_word = create_random_lodtensor(lod, place, low=0, high=dict_size - 1)
fourth_word = create_random_lodtensor(lod, place, low=0, high=dict_size - 1)
- result = inferencer.infer({
- 'firstw': first_word,
- 'secondw': second_word,
- 'thirdw': third_word,
- 'forthw': fourth_word
- })
+ result = inferencer.infer(
+ {
+ 'firstw': first_word,
+ 'secondw': second_word,
+ 'thirdw': third_word,
+ 'forthw': fourth_word
+ },
+ return_numpy=False)
print(np.array(result[0]))
@@ -140,9 +151,17 @@ def main(use_cuda, is_sparse):
if use_cuda and not fluid.core.is_compiled_with_cuda():
return
- save_path = "word2vec.params"
- train(use_cuda, partial(train_program, is_sparse), save_path)
- infer(use_cuda, partial(inference_program, is_sparse), save_path)
+ save_path = "word2vec.inference.model"
+
+ train(
+ use_cuda=use_cuda,
+ train_program=partial(train_program, is_sparse),
+ save_dirname=save_path)
+
+ infer(
+ use_cuda=use_cuda,
+ inference_program=partial(inference_program, is_sparse),
+ save_dirname=save_path)
if __name__ == '__main__':
From 0ad9212d78d26a82e5d9722aad7807b3fede47d1 Mon Sep 17 00:00:00 2001
From: Lei Wang <bestwanglei@gmail.com>
Date: Fri, 18 May 2018 19:04:13 -0700
Subject: [PATCH 175/195] Dockerfile: unify dev and product docker environment.
(#10778)
* Dockerfile: unify dev and product docker environment.
* Fix check style error.
* Use envrioment valuable to get version info.
---
paddle/scripts/paddle_build.sh | 10 ++++++----
1 file changed, 6 insertions(+), 4 deletions(-)
diff --git a/paddle/scripts/paddle_build.sh b/paddle/scripts/paddle_build.sh
index 3efca04a5c..fbe219a1c9 100755
--- a/paddle/scripts/paddle_build.sh
+++ b/paddle/scripts/paddle_build.sh
@@ -405,17 +405,19 @@ EOF
function gen_dockerfile() {
# Set BASE_IMAGE according to env variables
+ CUDA_MAJOR="$(echo $CUDA_VERSION | cut -d '.' -f 1).$(echo $CUDA_VERSION | cut -d '.' -f 2)"
+ CUDNN_MAJOR=$(echo $CUDNN_VERSION | cut -d '.' -f 1)
if [[ ${WITH_GPU} == "ON" ]]; then
- BASE_IMAGE="nvidia/cuda:8.0-cudnn5-runtime-ubuntu16.04"
+ BASE_IMAGE="nvidia/cuda:${CUDA_MAJOR}-cudnn${CUDNN_MAJOR}-runtime-ubuntu16.04"
else
- BASE_IMAGE="ubuntu:16.04"
+ BASE_IMAGE="ubuntu:16.04"
fi
DOCKERFILE_GPU_ENV=""
DOCKERFILE_CUDNN_DSO=""
if [[ ${WITH_GPU:-OFF} == 'ON' ]]; then
DOCKERFILE_GPU_ENV="ENV LD_LIBRARY_PATH /usr/lib/x86_64-linux-gnu:\${LD_LIBRARY_PATH}"
- DOCKERFILE_CUDNN_DSO="RUN ln -s /usr/lib/x86_64-linux-gnu/libcudnn.so.5 /usr/lib/x86_64-linux-gnu/libcudnn.so"
+ DOCKERFILE_CUDNN_DSO="RUN ln -s /usr/lib/x86_64-linux-gnu/libcudnn.so.${CUDNN_MAJOR} /usr/lib/x86_64-linux-gnu/libcudnn.so"
fi
cat <<EOF
@@ -490,7 +492,7 @@ function gen_fluid_inference_lib() {
Deploying fluid inference library ...
========================================
EOF
- make inference_lib_dist
+ make -j `nproc` inference_lib_dist
fi
}
From a66afe067588f434d7eb3b11faddfe248c794f65 Mon Sep 17 00:00:00 2001
From: baiyf <baiyfbupt@gmail.com>
Date: Sun, 20 May 2018 18:34:03 +0800
Subject: [PATCH 176/195] Expose prior_box op into detection.py (#10773)
* package prior_box op
* add doc
* add unittest
* add unittest
* fix CI fails
---
python/paddle/fluid/layers/detection.py | 141 +++++++++++++-------
python/paddle/fluid/tests/test_detection.py | 18 +++
2 files changed, 114 insertions(+), 45 deletions(-)
diff --git a/python/paddle/fluid/layers/detection.py b/python/paddle/fluid/layers/detection.py
index a5938fe494..b33adf55cf 100644
--- a/python/paddle/fluid/layers/detection.py
+++ b/python/paddle/fluid/layers/detection.py
@@ -23,6 +23,7 @@ import nn
import math
__all__ = [
+ 'prior_box',
'multi_box_head',
'bipartite_match',
'target_assign',
@@ -564,6 +565,98 @@ def ssd_loss(location,
return loss
+def prior_box(input,
+ image,
+ min_sizes,
+ max_sizes=None,
+ aspect_ratios=None,
+ variance=[0.1, 0.1, 0.2, 0.2],
+ flip=False,
+ clip=False,
+ steps=[0.0, 0.0],
+ offset=0.5,
+ name=None):
+ """
+ **Prior box operator**
+
+ Generate prior boxes for SSD(Single Shot MultiBox Detector) algorithm.
+ Each position of the input produce N prior boxes, N is determined by
+ the count of min_sizes, max_sizes and aspect_ratios, The size of the
+ box is in range(min_size, max_size) interval, which is generated in
+ sequence according to the aspect_ratios.
+
+ Args:
+ input(Variable): The Input Variables, the format is NCHW.
+ image(Variable): The input image data of PriorBoxOp,
+ the layout is NCHW.
+ min_sizes(list|tuple): min sizes of generated prior boxes.
+ max_sizes(list|tuple|None): max sizes of generated prior boxes.
+ Default: None.
+ aspect_ratios(list|tuple): the aspect ratios of generated prior
+ boxes. Default: None.
+ variance(list|tuple): the variances to be encoded in prior boxes.
+ Default:[0.1, 0.1, 0.2, 0.2].
+ flip(bool): Whether to flip aspect ratios. Default:False.
+ clip(bool): Whether to clip out-of-boundary boxes. Default: False.
+ step(list|turple): Prior boxes step across weight and height, If
+ step[0] == 0.0/step[1] == 0.0, the prior boxes step across
+ height/weight of the input will be automatically calculated.
+ Default: [0.0]
+ offset(float): Prior boxes center offset. Default: 0.5
+ name(str): Name of the prior box op. Default: None.
+
+ Returns:
+ boxes(Variable): the output prior boxes of PriorBox.
+ The layout is [H, W, num_priors, 4].
+ H is the height of input, W is the width of input,
+ num_priors is the total
+ box count of each position of input.
+ Variances(Variable): the expanded variances of PriorBox.
+ The layout is [H, W, num_priors, 4].
+ H is the height of input, W is the width of input
+ num_priors is the total
+ box count of each position of input
+
+
+ Examples:
+ .. code-block:: python
+ box, var = prior_box(
+ input=conv1,
+ image=images,
+ min_sizes=[100.],
+ flip=True,
+ clip=True)
+ """
+ helper = LayerHelper("prior_box", **locals())
+ dtype = helper.input_dtype()
+
+ attrs = {
+ 'min_sizes': min_sizes,
+ 'aspect_ratios': aspect_ratios,
+ 'variances': variance,
+ 'flip': flip,
+ 'clip': clip,
+ 'step_w': steps[0],
+ 'step_h': steps[1],
+ 'offset': offset
+ }
+ if max_sizes is not None and len(max_sizes) > 0 and max_sizes[0] > 0:
+ attrs['max_sizes'] = max_sizes
+
+ box = helper.create_tmp_variable(dtype)
+ var = helper.create_tmp_variable(dtype)
+ helper.append_op(
+ type="prior_box",
+ inputs={"Input": input,
+ "Image": image},
+ outputs={"Boxes": box,
+ "Variances": var},
+ attrs=attrs, )
+ box.stop_gradient = True
+ var.stop_gradient = True
+ return box, var
+
+
def multi_box_head(inputs,
image,
base_size,
@@ -660,47 +753,6 @@ def multi_box_head(inputs,
clip=True)
"""
- def _prior_box_(input,
- image,
- min_sizes,
- max_sizes,
- aspect_ratios,
- variance,
- flip=False,
- clip=False,
- step_w=0.0,
- step_h=0.0,
- offset=0.5,
- name=None):
- helper = LayerHelper("prior_box", **locals())
- dtype = helper.input_dtype()
-
- attrs = {
- 'min_sizes': min_sizes,
- 'aspect_ratios': aspect_ratios,
- 'variances': variance,
- 'flip': flip,
- 'clip': clip,
- 'step_w': step_w,
- 'step_h': step_h,
- 'offset': offset
- }
- if len(max_sizes) > 0 and max_sizes[0] > 0:
- attrs['max_sizes'] = max_sizes
-
- box = helper.create_tmp_variable(dtype)
- var = helper.create_tmp_variable(dtype)
- helper.append_op(
- type="prior_box",
- inputs={"Input": input,
- "Image": image},
- outputs={"Boxes": box,
- "Variances": var},
- attrs=attrs, )
- box.stop_gradient = True
- var.stop_gradient = True
- return box, var
-
def _reshape_with_axis_(input, axis=1):
if not (axis > 0 and axis < len(input.shape)):
raise ValueError("The axis should be smaller than "
@@ -777,11 +829,10 @@ def multi_box_head(inputs,
aspect_ratio = aspect_ratios[i]
if not _is_list_or_tuple_(aspect_ratio):
aspect_ratio = [aspect_ratio]
+ step = [step_w[i] if step_w else 0.0, step_h[i] if step_w else 0.0]
- box, var = _prior_box_(input, image, min_size, max_size, aspect_ratio,
- variance, flip, clip, step_w[i]
- if step_w else 0.0, step_h[i]
- if step_w else 0.0, offset)
+ box, var = prior_box(input, image, min_size, max_size, aspect_ratio,
+ variance, flip, clip, step, offset)
box_results.append(box)
var_results.append(var)
diff --git a/python/paddle/fluid/tests/test_detection.py b/python/paddle/fluid/tests/test_detection.py
index 921260ef3f..8569d838bd 100644
--- a/python/paddle/fluid/tests/test_detection.py
+++ b/python/paddle/fluid/tests/test_detection.py
@@ -109,6 +109,24 @@ class TestDetection(unittest.TestCase):
print(str(program))
+class TestPriorBox(unittest.TestCase):
+ def test_prior_box(self):
+ data_shape = [3, 224, 224]
+ images = fluid.layers.data(
+ name='pixel', shape=data_shape, dtype='float32')
+ conv1 = fluid.layers.conv2d(images, 3, 3, 2)
+ box, var = layers.prior_box(
+ input=conv1,
+ image=images,
+ min_sizes=[100.0],
+ aspect_ratios=[1.],
+ flip=True,
+ clip=True)
+ assert len(box.shape) == 4
+ assert box.shape == var.shape
+ assert box.shape[3] == 4
+
+
class TestMultiBoxHead(unittest.TestCase):
def test_multi_box_head(self):
data_shape = [3, 224, 224]
From 0e4467eee40a0b31bacec57e2dd46623af40143d Mon Sep 17 00:00:00 2001
From: dzhwinter <dongzhihong01@baidu.com>
Date: Mon, 21 May 2018 10:18:58 +0800
Subject: [PATCH 177/195] "fix compile" (#10657)
---
paddle/fluid/operators/beam_search_op.h | 4 ----
paddle/fluid/platform/CMakeLists.txt | 2 +-
2 files changed, 1 insertion(+), 5 deletions(-)
diff --git a/paddle/fluid/operators/beam_search_op.h b/paddle/fluid/operators/beam_search_op.h
index 9b51db8a45..46bc4f6f93 100644
--- a/paddle/fluid/operators/beam_search_op.h
+++ b/paddle/fluid/operators/beam_search_op.h
@@ -14,10 +14,6 @@ limitations under the License. */
#pragma once
-#ifdef PADDLE_WITH_TESTING
-#include "gtest/gtest.h"
-#endif
-
#include <string>
#include <vector>
#include "paddle/fluid/framework/lod_tensor.h"
diff --git a/paddle/fluid/platform/CMakeLists.txt b/paddle/fluid/platform/CMakeLists.txt
index 79e3c26fef..b29035bafd 100644
--- a/paddle/fluid/platform/CMakeLists.txt
+++ b/paddle/fluid/platform/CMakeLists.txt
@@ -49,7 +49,7 @@ nv_test(device_context_test SRCS device_context_test.cu DEPS device_context gpu_
nv_test(cudnn_helper_test SRCS cudnn_helper_test.cc DEPS dynload_cuda)
nv_test(transform_test SRCS transform_test.cu DEPS memory place device_context)
-cc_library(device_tracer SRCS device_tracer.cc DEPS boost profiler_proto ${GPU_CTX_DEPS})
+cc_library(device_tracer SRCS device_tracer.cc DEPS boost profiler_proto framework_proto ${GPU_CTX_DEPS})
cc_library(profiler SRCS profiler.cc DEPS device_context device_tracer)
cc_test(profiler_test SRCS profiler_test.cc DEPS profiler)
From 7ae03ec08b1d2699fa6520bedd7b20dd4fc02f54 Mon Sep 17 00:00:00 2001
From: Yancey <yanxu05@baidu.com>
Date: Mon, 21 May 2018 10:33:03 +0800
Subject: [PATCH 178/195] fix lack split_byref op in parallel executor (#10770)
---
paddle/fluid/framework/details/multi_devices_graph_builder.cc | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/paddle/fluid/framework/details/multi_devices_graph_builder.cc b/paddle/fluid/framework/details/multi_devices_graph_builder.cc
index 45bad58145..6b0c0a6b9f 100644
--- a/paddle/fluid/framework/details/multi_devices_graph_builder.cc
+++ b/paddle/fluid/framework/details/multi_devices_graph_builder.cc
@@ -98,7 +98,7 @@ bool MultiDevSSAGraphBuilder::IsDistTrainOp(const OpDesc &op,
return false;
};
- if (op.Type() == "split") {
+ if (op.Type() == "split" || op.Type() == "split_byref") {
return checker(op.OutputArgumentNames(), send_op->InputArgumentNames());
} else if (op.Type() == "concat") {
return checker(op.InputArgumentNames(), send_op->OutputArgumentNames());
From 1bd0197b5ae4e46f91f19b25d4c90d3924387916 Mon Sep 17 00:00:00 2001
From: Shan Yi <35982308+shanyi15@users.noreply.github.com>
Date: Mon, 21 May 2018 10:59:17 +0800
Subject: [PATCH 179/195] Update cpu_profiling_cn.md
---
doc/fluid/howto/optimization/cpu_profiling_cn.md | 4 +++-
1 file changed, 3 insertions(+), 1 deletion(-)
diff --git a/doc/fluid/howto/optimization/cpu_profiling_cn.md b/doc/fluid/howto/optimization/cpu_profiling_cn.md
index 8266dec3c6..198a05a79e 100644
--- a/doc/fluid/howto/optimization/cpu_profiling_cn.md
+++ b/doc/fluid/howto/optimization/cpu_profiling_cn.md
@@ -1,3 +1,5 @@
+# CPU性能调优
+
此教程会介绍如何使用Python的cProfile包、Python库yep、Google perftools来进行性能分析 (profiling) 与调优（performance tuning）。
Profling 指发现性能瓶颈。系统中的瓶颈可能和程序员开发过程中想象的瓶颈相去甚远。Tuning 指消除瓶颈。性能优化的过程通常是不断重复地 profiling 和 tuning。
@@ -8,7 +10,7 @@ PaddlePaddle 用户一般通过调用 Python API 编写深度学习程序。大
* Python 与 C++ 混合代码的性能分析
-# Python代码的性能分析
+## Python代码的性能分析
### 生成性能分析文件
From 60f4b73aaa2be72df5f4e8082b3a9e1e295b1b84 Mon Sep 17 00:00:00 2001
From: Shan Yi <35982308+shanyi15@users.noreply.github.com>
Date: Mon, 21 May 2018 11:02:59 +0800
Subject: [PATCH 180/195] Update cpu_profiling_en.md
---
doc/fluid/howto/optimization/cpu_profiling_en.md | 4 +++-
1 file changed, 3 insertions(+), 1 deletion(-)
diff --git a/doc/fluid/howto/optimization/cpu_profiling_en.md b/doc/fluid/howto/optimization/cpu_profiling_en.md
index e95556dd60..216694965b 100644
--- a/doc/fluid/howto/optimization/cpu_profiling_en.md
+++ b/doc/fluid/howto/optimization/cpu_profiling_en.md
@@ -1,3 +1,5 @@
+# Tune CPU performance
+
This tutorial introduces techniques we use to profile and tune the
CPU performance of PaddlePaddle. We will use Python packages
`cProfile` and `yep`, and Google's `perftools`.
@@ -14,7 +16,7 @@ the profiling and tuning of
1. the Python code and
1. the mixture of Python and C++ code.
-# Profiling the Python Code
+## Profiling the Python Code
### Generate the Performance Profiling File
From 5828101c239fa51f85eb34caeb942e2df92467e6 Mon Sep 17 00:00:00 2001
From: dzhwinter <dongzhihong01@baidu.com>
Date: Mon, 21 May 2018 15:11:17 +0800
Subject: [PATCH 181/195] make uint8 support in data_type transform and memory
optimize (#10715)
* "a piece of job."
* "fix typeo"
* "fix ci"
---
paddle/fluid/framework/data_type_transform.cc | 6 ++++++
paddle/fluid/pybind/protobuf.cc | 1 +
python/paddle/fluid/framework.py | 2 ++
.../fluid/transpiler/memory_optimization_transpiler.py | 3 ++-
4 files changed, 11 insertions(+), 1 deletion(-)
diff --git a/paddle/fluid/framework/data_type_transform.cc b/paddle/fluid/framework/data_type_transform.cc
index c0523f3c79..5a57ec2058 100644
--- a/paddle/fluid/framework/data_type_transform.cc
+++ b/paddle/fluid/framework/data_type_transform.cc
@@ -91,6 +91,12 @@ void TransDataType(const OpKernelType& kernel_type_for_var,
case proto::VarType::BOOL:
framework::VisitDataType(dst_type, CastDataType<bool>(in, out, ctx));
break;
+ case proto::VarType::INT16:
+ framework::VisitDataType(dst_type, CastDataType<bool>(in, out, ctx));
+ break;
+ case proto::VarType::UINT8:
+ framework::VisitDataType(dst_type, CastDataType<bool>(in, out, ctx));
+ break;
default:
PADDLE_THROW("Not support type %d", src_type);
}
diff --git a/paddle/fluid/pybind/protobuf.cc b/paddle/fluid/pybind/protobuf.cc
index 6471eb3ab7..bcf6d4dd30 100644
--- a/paddle/fluid/pybind/protobuf.cc
+++ b/paddle/fluid/pybind/protobuf.cc
@@ -238,6 +238,7 @@ void BindVarDsec(pybind11::module *m) {
pybind11::enum_<pd::proto::VarType::Type>(var_desc, "VarType", "")
.value("BOOL", pd::proto::VarType::BOOL)
+ .value("UINT8", pd::proto::VarType::UINT8)
.value("INT16", pd::proto::VarType::INT16)
.value("INT32", pd::proto::VarType::INT32)
.value("INT64", pd::proto::VarType::INT64)
diff --git a/python/paddle/fluid/framework.py b/python/paddle/fluid/framework.py
index 38c765938f..161ea55586 100644
--- a/python/paddle/fluid/framework.py
+++ b/python/paddle/fluid/framework.py
@@ -72,6 +72,8 @@ def convert_np_dtype_to_dtype_(np_dtype):
return core.VarDesc.VarType.INT64
elif dtype == np.bool:
return core.VarDesc.VarType.BOOL
+ elif dtype == np.uint8:
+ return core.VarDesc.VarType.UINT8
else:
raise ValueError("Not supported numpy dtype " + str(dtype))
diff --git a/python/paddle/fluid/transpiler/memory_optimization_transpiler.py b/python/paddle/fluid/transpiler/memory_optimization_transpiler.py
index 49034b47b2..80a8f7c09c 100644
--- a/python/paddle/fluid/transpiler/memory_optimization_transpiler.py
+++ b/python/paddle/fluid/transpiler/memory_optimization_transpiler.py
@@ -24,7 +24,8 @@ dtype_to_size = {
core.VarDesc.VarType.INT16: 2,
core.VarDesc.VarType.INT32: 4,
core.VarDesc.VarType.INT64: 8,
- core.VarDesc.VarType.BOOL: 1
+ core.VarDesc.VarType.BOOL: 1,
+ core.VarDesc.VarType.UINT8: 1,
}
SUB_BLOCK_OPS = [
From 9ff6715f8a51af81e1aaaea3388c406900b25f37 Mon Sep 17 00:00:00 2001
From: Qingsheng Li <liqingsheng@baidu.com>
Date: Mon, 21 May 2018 15:27:17 +0800
Subject: [PATCH 182/195] Enhanced is_empty_op for our seq2seq model (#10704)
* Added kernel to is_empty_op
* Added python API
* Updated code as required
* Updated unittests
---
paddle/fluid/operators/is_empty_op.cc | 57 ++++++++++---------
paddle/fluid/operators/is_empty_op.h | 37 ++++++++++++
python/paddle/fluid/layers/control_flow.py | 38 +++++++++++++
.../fluid/tests/unittests/test_is_empty_op.py | 42 ++++----------
4 files changed, 117 insertions(+), 57 deletions(-)
create mode 100644 paddle/fluid/operators/is_empty_op.h
diff --git a/paddle/fluid/operators/is_empty_op.cc b/paddle/fluid/operators/is_empty_op.cc
index d3f3ad9244..29b73951bb 100644
--- a/paddle/fluid/operators/is_empty_op.cc
+++ b/paddle/fluid/operators/is_empty_op.cc
@@ -12,45 +12,41 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
+#include "paddle/fluid/operators/is_empty_op.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/framework/operator.h"
namespace paddle {
namespace operators {
-constexpr char kInput[] = "X";
-constexpr char kOutput[] = "Out";
-
-class IsEmptyOp : public framework::OperatorBase {
+class IsEmptyOp : public framework::OperatorWithKernel {
public:
- IsEmptyOp(const std::string &type, const framework::VariableNameMap &inputs,
- const framework::VariableNameMap &outputs,
- const framework::AttributeMap &attrs)
- : OperatorBase(type, inputs, outputs, attrs) {}
+ using framework::OperatorWithKernel::OperatorWithKernel;
- private:
- void RunImpl(const framework::Scope &scope,
- const platform::Place &place) const override {
- // get input
- auto *var = scope.FindVar(Input(kInput));
- PADDLE_ENFORCE_NOT_NULL(var);
- auto &tensor = var->Get<framework::LoDTensor>();
- // get output
- auto *out = scope.FindVar(Output(kOutput));
- PADDLE_ENFORCE_NOT_NULL(out);
- auto *out_tensor = out->GetMutable<framework::LoDTensor>();
+ protected:
+ void InferShape(framework::InferShapeContext *ctx) const override {
+ PADDLE_ENFORCE(ctx->HasInput("X"),
+ "Input(X) of IsEmptyOp should not be null.");
+ PADDLE_ENFORCE(ctx->HasOutput("Out"),
+ "Output(Out) of IsEmptyOp should not be null.");
+ ctx->SetOutputDim("Out", {1});
+ }
- out_tensor->Resize({1});
- out_tensor->mutable_data<bool>(platform::CPUPlace())[0] =
- framework::product(tensor.dims()) == 0;
+ framework::OpKernelType GetExpectedKernelType(
+ const framework::ExecutionContext &ctx) const override {
+ framework::OpKernelType kt = framework::OpKernelType(
+ framework::ToDataType(ctx.Input<framework::LoDTensor>("X")->type()),
+ platform::CPUPlace());
+ return kt;
}
};
-class IsEmptyOpProtoMaker : public framework::OpProtoAndCheckerMaker {
+class IsEmptyOpMaker : public framework::OpProtoAndCheckerMaker {
public:
void Make() override {
- AddInput(kInput, "(Tensor) Tensor which is to be checked.");
- AddOutput(kOutput, "(Tensor) a boolean Tensor that indicate empty or not.");
+ AddInput("X", "(LoDTensor) Tensor which is to be checked.");
+ AddOutput("Out",
+ "(LoDTensor) a boolean Tensor that indicate empty or not.");
AddComment(R"DOC(
IsEmpty Operator which checks whether a tensor is empty.
@@ -62,5 +58,12 @@ It will just return product(tensor.ddims()) > 0;
} // namespace operators
} // namespace paddle
-REGISTER_OP_WITHOUT_GRADIENT(is_empty, paddle::operators::IsEmptyOp,
- paddle::operators::IsEmptyOpProtoMaker);
+namespace ops = paddle::operators;
+
+REGISTER_OPERATOR(is_empty, ops::IsEmptyOp, ops::IsEmptyOpMaker,
+ paddle::framework::EmptyGradOpMaker);
+REGISTER_OP_CPU_KERNEL(
+ is_empty, ops::IsEmptyOpKernel<paddle::platform::CPUDeviceContext, float>,
+ ops::IsEmptyOpKernel<paddle::platform::CPUDeviceContext, double>,
+ ops::IsEmptyOpKernel<paddle::platform::CPUDeviceContext, int>,
+ ops::IsEmptyOpKernel<paddle::platform::CPUDeviceContext, int64_t>);
diff --git a/paddle/fluid/operators/is_empty_op.h b/paddle/fluid/operators/is_empty_op.h
new file mode 100644
index 0000000000..3e3af22fa8
--- /dev/null
+++ b/paddle/fluid/operators/is_empty_op.h
@@ -0,0 +1,37 @@
+/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License. */
+
+#pragma once
+#include "paddle/fluid/framework/op_registry.h"
+#include "paddle/fluid/framework/operator.h"
+
+namespace paddle {
+namespace operators {
+
+template <typename DeviceContext, typename T>
+class IsEmptyOpKernel : public framework::OpKernel<T> {
+ public:
+ void Compute(const framework::ExecutionContext& context) const override {
+ // get input
+ auto* input_tensor = context.Input<framework::LoDTensor>("X");
+ // get output
+ auto* output_tensor = context.Output<framework::LoDTensor>("Out");
+
+ output_tensor->mutable_data<bool>(platform::CPUPlace())[0] =
+ framework::product(input_tensor->dims()) == 0;
+ }
+};
+
+} // namespace operators
+} // namespace paddle
diff --git a/python/paddle/fluid/layers/control_flow.py b/python/paddle/fluid/layers/control_flow.py
index 4b707973e2..dee4144808 100644
--- a/python/paddle/fluid/layers/control_flow.py
+++ b/python/paddle/fluid/layers/control_flow.py
@@ -49,6 +49,7 @@ __all__ = [
'reorder_lod_tensor_by_rank',
'ParallelDo',
'Print',
+ 'is_empty',
]
@@ -1562,3 +1563,40 @@ def reorder_lod_tensor_by_rank(x, rank_table):
'RankTable': [rank_table]},
outputs={'Out': [out]})
return out
+
+
+def is_empty(x, cond=None, **ignored):
+ """
+ **Is Empty**
+
+ This layer returns the truth value of whether the variable is empty.
+
+ Args:
+ x(Variable): Operand of *is_empty*
+ cond(Variable|None): Optional output variable to store the result
+ of *is_empty*
+
+ Returns:
+ Variable: The tensor variable storing the output of *is_empty*.
+
+ Raises:
+ TypeError: If input cond is not a variable, or cond's dtype is
+ not bool
+
+ Examples:
+ .. code-block:: python
+
+ less = fluid.layers.is_empty(x=input)
+ """
+ helper = LayerHelper("is_empty", **locals())
+ if cond is None:
+ cond = helper.create_tmp_variable(dtype='bool')
+ cond.stop_gradient = True
+ elif not isinstance(cond, Variable):
+ raise TypeError("cond takes a variable")
+ elif cond.dtype != 'bool':
+ raise TypeError("The data type of cond must be bool")
+
+ helper.append_op(
+ type='is_empty', inputs={'X': [x]}, outputs={'Out': [cond]})
+ return cond
diff --git a/python/paddle/fluid/tests/unittests/test_is_empty_op.py b/python/paddle/fluid/tests/unittests/test_is_empty_op.py
index 4d11cf226b..11121d9b65 100644
--- a/python/paddle/fluid/tests/unittests/test_is_empty_op.py
+++ b/python/paddle/fluid/tests/unittests/test_is_empty_op.py
@@ -14,42 +14,24 @@
import unittest
import numpy as np
-from paddle.fluid.op import Operator
-import paddle.fluid.core as core
+from op_test import OpTest
-def create_tensor(scope, name, np_data):
- tensor = scope.var(name).get_tensor()
- tensor.set_dims(np_data.shape)
- tensor.set(np_data, core.CPUPlace())
- return tensor
-
-
-class TestIsEmptyOp(unittest.TestCase):
+class TestEmpty(OpTest):
def setUp(self):
- self.scope = core.Scope()
- # create input variables
- np_data0 = np.array([0, 1, 2])
- create_tensor(self.scope, "X0", np_data0)
-
- np_data1 = np.array([1])
- t = create_tensor(self.scope, "X1", np_data1)
- t.set_dims([0])
+ self.op_type = "is_empty"
+ self.inputs = {'X': np.array([1, 2, 3])}
+ self.outputs = {'Out': np.array([False])}
- # create output variables
- self.scope.var("out")
+ def test_check_output(self):
+ self.check_output()
- def test_no_empty(self):
- self.one_case("X0", False)
- def test_empty(self):
- self.one_case("X1", True)
-
- def one_case(self, input, target):
- op = Operator(type="is_empty", X=input, Out="out")
- op.run(self.scope, core.CPUPlace())
- out = self.scope.var("out").get_tensor()
- self.assertEqual(np.array(out)[0], target)
+class TestNotEmpty(TestEmpty):
+ def setUp(self):
+ self.op_type = "is_empty"
+ self.inputs = {'X': np.array([])}
+ self.outputs = {'Out': np.array([True])}
if __name__ == "__main__":
From 35e5563695ac9a227a1d78965b417ee45202b457 Mon Sep 17 00:00:00 2001
From: Yancey <yanxu05@baidu.com>
Date: Mon, 21 May 2018 15:37:43 +0800
Subject: [PATCH 183/195] fix wheel package name (#10697)
* fix wheel package name
* delete cuda7.5 cudnn5
---
doc/v2/build_and_install/pip_install_cn.rst | 11 +++++------
doc/v2/build_and_install/pip_install_en.rst | 11 +++++------
2 files changed, 10 insertions(+), 12 deletions(-)
diff --git a/doc/v2/build_and_install/pip_install_cn.rst b/doc/v2/build_and_install/pip_install_cn.rst
index b3d8827437..aa1dc6ee2c 100644
--- a/doc/v2/build_and_install/pip_install_cn.rst
+++ b/doc/v2/build_and_install/pip_install_cn.rst
@@ -37,12 +37,11 @@ PaddlePaddle可以使用常用的Python包管理工具
:header: "版本说明", "cp27-cp27mu", "cp27-cp27m"
:widths: 1, 3, 3
- "cpu_avx_mkl", "`paddlepaddle-0.11.0-cp27-cp27mu-linux_x86_64.whl <https://guest:@paddleci.ngrok.io/repository/download/Manylinux1_CpuAvxCp27cp27mu/.lastSuccessful/paddlepaddle-0.11.0-cp27-cp27mu-linux_x86_64.whl>`_", "`paddlepaddle-0.11.0-cp27-cp27m-linux_x86_64.whl <https://guest:@paddleci.ngrok.io/repository/download/Manylinux1_CpuAvxCp27cp27mu/.lastSuccessful/paddlepaddle-0.11.0-cp27-cp27m-linux_x86_64.whl>`_"
- "cpu_avx_openblas", "`paddlepaddle-0.11.0-cp27-cp27mu-linux_x86_64.whl <https://guest:@paddleci.ngrok.io/repository/download/Manylinux1_CpuAvxOpenblas/.lastSuccessful/paddlepaddle-0.11.0-cp27-cp27mu-linux_x86_64.whl>`_", "`paddlepaddle-0.11.0-cp27-cp27m-linux_x86_64.whl <https://guest:@paddleci.ngrok.io/repository/download/Manylinux1_CpuAvxOpenblas/.lastSuccessful/paddlepaddle-0.11.0-cp27-cp27m-linux_x86_64.whl>`_"
- "cpu_noavx_openblas", "`paddlepaddle-0.11.0-cp27-cp27mu-linux_x86_64.whl <https://guest:@paddleci.ngrok.io/repository/download/Manylinux1_CpuNoavxOpenblas/.lastSuccessful/paddlepaddle-0.11.0-cp27-cp27mu-linux_x86_64.whl>`_", "`paddlepaddle-0.11.0-cp27-cp27m-linux_x86_64.whl <https://guest:@paddleci.ngrok.io/repository/download/Manylinux1_CpuNoavxOpenblas/.lastSuccessful/paddlepaddle-0.11.0-cp27-cp27m-linux_x86_64.whl>`_"
- "cuda7.5_cudnn5_avx_mkl", "`paddlepaddle_gpu-0.11.0-cp27-cp27mu-linux_x86_64.whl <https://guest:@paddleci.ngrok.io/repository/download/Manylinux1_Cuda75cudnn5cp27cp27mu/.lastSuccessful/paddlepaddle_gpu-0.11.0-cp27-cp27mu-linux_x86_64.whl>`_", "`paddlepaddle_gpu-0.11.0-cp27-cp27m-linux_x86_64.whl <https://guest:@paddleci.ngrok.io/repository/download/Manylinux1_Cuda75cudnn5cp27cp27mu/.lastSuccessful/paddlepaddle_gpu-0.11.0-cp27-cp27m-linux_x86_64.whl>`_"
- "cuda8.0_cudnn5_avx_mkl", "`paddlepaddle_gpu-0.11.0-cp27-cp27mu-linux_x86_64.whl <https://guest:@paddleci.ngrok.io/repository/download/Manylinux1_Cuda80cudnn5cp27cp27mu/.lastSuccessful/paddlepaddle_gpu-0.11.0-cp27-cp27mu-linux_x86_64.whl>`_", "`paddlepaddle_gpu-0.11.0-cp27-cp27m-linux_x86_64.whl <https://guest:@paddleci.ngrok.io/repository/download/Manylinux1_Cuda80cudnn5cp27cp27mu/.lastSuccessful/paddlepaddle_gpu-0.11.0-cp27-cp27m-linux_x86_64.whl>`_"
- "cuda8.0_cudnn7_avx_mkl", "`paddlepaddle_gpu-0.11.0-cp27-cp27mu-linux_x86_64.whl <https://guest:@paddleci.ngrok.io/repository/download/Manylinux1_Cuda8cudnn7cp27cp27mu/.lastSuccessful/paddlepaddle_gpu-0.11.0-cp27-cp27mu-linux_x86_64.whl>`_", "`paddlepaddle_gpu-0.11.0-cp27-cp27m-linux_x86_64.whl <https://guest:@paddleci.ngrok.io/repository/download/Manylinux1_Cuda8cudnn7cp27cp27mu/.lastSuccessful/paddlepaddle_gpu-0.11.0-cp27-cp27m-linux_x86_64.whl>`_"
+ "cpu_avx_mkl", "`paddlepaddle-latest-cp27-cp27mu-linux_x86_64.whl <https://guest:@paddleci.ngrok.io/repository/download/Manylinux1_CpuAvxCp27cp27mu/.lastSuccessful/paddlepaddle-latest-cp27-cp27mu-linux_x86_64.whl>`_", "`paddlepaddle-latest-cp27-cp27m-linux_x86_64.whl <https://guest:@paddleci.ngrok.io/repository/download/Manylinux1_CpuAvxCp27cp27mu/.lastSuccessful/paddlepaddle-latest-cp27-cp27m-linux_x86_64.whl>`_"
+ "cpu_avx_openblas", "`paddlepaddle-latest-cp27-cp27mu-linux_x86_64.whl <https://guest:@paddleci.ngrok.io/repository/download/Manylinux1_CpuAvxOpenblas/.lastSuccessful/paddlepaddle-latest-cp27-cp27mu-linux_x86_64.whl>`_", "`paddlepaddle-latest-cp27-cp27m-linux_x86_64.whl <https://guest:@paddleci.ngrok.io/repository/download/Manylinux1_CpuAvxOpenblas/.lastSuccessful/paddlepaddle-latest-cp27-cp27m-linux_x86_64.whl>`_"
+ "cpu_noavx_openblas", "`paddlepaddle-latest-cp27-cp27mu-linux_x86_64.whl <https://guest:@paddleci.ngrok.io/repository/download/Manylinux1_CpuNoavxOpenblas/.lastSuccessful/paddlepaddle-latest-cp27-cp27mu-linux_x86_64.whl>`_", "`paddlepaddle-latest-cp27-cp27m-linux_x86_64.whl <https://guest:@paddleci.ngrok.io/repository/download/Manylinux1_CpuNoavxOpenblas/.lastSuccessful/paddlepaddle-latest-cp27-cp27m-linux_x86_64.whl>`_"
+ "cuda8.0_cudnn5_avx_mkl", "`paddlepaddle_gpu-latest-cp27-cp27mu-linux_x86_64.whl <https://guest:@paddleci.ngrok.io/repository/download/Manylinux1_Cuda80cudnn5cp27cp27mu/.lastSuccessful/paddlepaddle_gpu-latest-cp27-cp27mu-linux_x86_64.whl>`_", "`paddlepaddle_gpu-latest-cp27-cp27m-linux_x86_64.whl <https://guest:@paddleci.ngrok.io/repository/download/Manylinux1_Cuda80cudnn5cp27cp27mu/.lastSuccessful/paddlepaddle_gpu-latest-cp27-cp27m-linux_x86_64.whl>`_"
+ "cuda8.0_cudnn7_avx_mkl", "`paddlepaddle_gpu-latest-cp27-cp27mu-linux_x86_64.whl <https://guest:@paddleci.ngrok.io/repository/download/Manylinux1_Cuda8cudnn7cp27cp27mu/.lastSuccessful/paddlepaddle_gpu-latest-cp27-cp27mu-linux_x86_64.whl>`_", "`paddlepaddle_gpu-latest-cp27-cp27m-linux_x86_64.whl <https://guest:@paddleci.ngrok.io/repository/download/Manylinux1_Cuda8cudnn7cp27cp27mu/.lastSuccessful/paddlepaddle_gpu-latest-cp27-cp27m-linux_x86_64.whl>`_"
.. _pip_dependency:
diff --git a/doc/v2/build_and_install/pip_install_en.rst b/doc/v2/build_and_install/pip_install_en.rst
index 1e409d86b9..a70821eb48 100644
--- a/doc/v2/build_and_install/pip_install_en.rst
+++ b/doc/v2/build_and_install/pip_install_en.rst
@@ -40,12 +40,11 @@ If the links below shows up the login form, just click "Log in as guest" to star
:header: "version", "cp27-cp27mu", "cp27-cp27m"
:widths: 1, 3, 3
- "cpu_avx_mkl", "`paddlepaddle-0.11.0-cp27-cp27mu-linux_x86_64.whl <https://guest:@paddleci.ngrok.io/repository/download/Manylinux1_CpuAvxCp27cp27mu/.lastSuccessful/paddlepaddle-0.11.0-cp27-cp27mu-linux_x86_64.whl>`_", "`paddlepaddle-0.11.0-cp27-cp27m-linux_x86_64.whl <https://guest:@paddleci.ngrok.io/repository/download/Manylinux1_CpuAvxCp27cp27mu/.lastSuccessful/paddlepaddle-0.11.0-cp27-cp27m-linux_x86_64.whl>`_"
- "cpu_avx_openblas", "`paddlepaddle-0.11.0-cp27-cp27mu-linux_x86_64.whl <https://guest:@paddleci.ngrok.io/repository/download/Manylinux1_CpuAvxOpenblas/.lastSuccessful/paddlepaddle-0.11.0-cp27-cp27mu-linux_x86_64.whl>`_", "`paddlepaddle-0.11.0-cp27-cp27m-linux_x86_64.whl <https://guest:@paddleci.ngrok.io/repository/download/Manylinux1_CpuAvxOpenblas/.lastSuccessful/paddlepaddle-0.11.0-cp27-cp27m-linux_x86_64.whl>`_"
- "cpu_noavx_openblas", "`paddlepaddle-0.11.0-cp27-cp27mu-linux_x86_64.whl <https://guest:@paddleci.ngrok.io/repository/download/Manylinux1_CpuNoavxOpenblas/.lastSuccessful/paddlepaddle-0.11.0-cp27-cp27mu-linux_x86_64.whl>`_", "`paddlepaddle-0.11.0-cp27-cp27m-linux_x86_64.whl <https://guest:@paddleci.ngrok.io/repository/download/Manylinux1_CpuNoavxOpenblas/.lastSuccessful/paddlepaddle-0.11.0-cp27-cp27m-linux_x86_64.whl>`_"
- "cuda7.5_cudnn5_avx_mkl", "`paddlepaddle_gpu-0.11.0-cp27-cp27mu-linux_x86_64.whl <https://guest:@paddleci.ngrok.io/repository/download/Manylinux1_Cuda75cudnn5cp27cp27mu/.lastSuccessful/paddlepaddle_gpu-0.11.0-cp27-cp27mu-linux_x86_64.whl>`_", "`paddlepaddle_gpu-0.11.0-cp27-cp27m-linux_x86_64.whl <https://guest:@paddleci.ngrok.io/repository/download/Manylinux1_Cuda75cudnn5cp27cp27mu/.lastSuccessful/paddlepaddle_gpu-0.11.0-cp27-cp27m-linux_x86_64.whl>`_"
- "cuda8.0_cudnn5_avx_mkl", "`paddlepaddle_gpu-0.11.0-cp27-cp27mu-linux_x86_64.whl <https://guest:@paddleci.ngrok.io/repository/download/Manylinux1_Cuda80cudnn5cp27cp27mu/.lastSuccessful/paddlepaddle_gpu-0.11.0-cp27-cp27mu-linux_x86_64.whl>`_", "`paddlepaddle_gpu-0.11.0-cp27-cp27m-linux_x86_64.whl <https://guest:@paddleci.ngrok.io/repository/download/Manylinux1_Cuda80cudnn5cp27cp27mu/.lastSuccessful/paddlepaddle_gpu-0.11.0-cp27-cp27m-linux_x86_64.whl>`_"
- "cuda8.0_cudnn7_avx_mkl", "`paddlepaddle_gpu-0.11.0-cp27-cp27mu-linux_x86_64.whl <https://guest:@paddleci.ngrok.io/repository/download/Manylinux1_Cuda8cudnn7cp27cp27mu/.lastSuccessful/paddlepaddle_gpu-0.11.0-cp27-cp27mu-linux_x86_64.whl>`_", "`paddlepaddle_gpu-0.11.0-cp27-cp27m-linux_x86_64.whl <https://guest:@paddleci.ngrok.io/repository/download/Manylinux1_Cuda8cudnn7cp27cp27mu/.lastSuccessful/paddlepaddle_gpu-0.11.0-cp27-cp27m-linux_x86_64.whl>`_"
+ "cpu_avx_mkl", "`paddlepaddle-latest-cp27-cp27mu-linux_x86_64.whl <https://guest:@paddleci.ngrok.io/repository/download/Manylinux1_CpuAvxCp27cp27mu/.lastSuccessful/paddlepaddle-latest-cp27-cp27mu-linux_x86_64.whl>`_", "`paddlepaddle-latest-cp27-cp27m-linux_x86_64.whl <https://guest:@paddleci.ngrok.io/repository/download/Manylinux1_CpuAvxCp27cp27mu/.lastSuccessful/paddlepaddle-latest-cp27-cp27m-linux_x86_64.whl>`_"
+ "cpu_avx_openblas", "`paddlepaddle-latest-cp27-cp27mu-linux_x86_64.whl <https://guest:@paddleci.ngrok.io/repository/download/Manylinux1_CpuAvxOpenblas/.lastSuccessful/paddlepaddle-latest-cp27-cp27mu-linux_x86_64.whl>`_", "`paddlepaddle-latest-cp27-cp27m-linux_x86_64.whl <https://guest:@paddleci.ngrok.io/repository/download/Manylinux1_CpuAvxOpenblas/.lastSuccessful/paddlepaddle-latest-cp27-cp27m-linux_x86_64.whl>`_"
+ "cpu_noavx_openblas", "`paddlepaddle-latest-cp27-cp27mu-linux_x86_64.whl <https://guest:@paddleci.ngrok.io/repository/download/Manylinux1_CpuNoavxOpenblas/.lastSuccessful/paddlepaddle-latest-cp27-cp27mu-linux_x86_64.whl>`_", "`paddlepaddle-latest-cp27-cp27m-linux_x86_64.whl <https://guest:@paddleci.ngrok.io/repository/download/Manylinux1_CpuNoavxOpenblas/.lastSuccessful/paddlepaddle-latest-cp27-cp27m-linux_x86_64.whl>`_"
+ "cuda8.0_cudnn5_avx_mkl", "`paddlepaddle_gpu-latest-cp27-cp27mu-linux_x86_64.whl <https://guest:@paddleci.ngrok.io/repository/download/Manylinux1_Cuda80cudnn5cp27cp27mu/.lastSuccessful/paddlepaddle_gpu-latest-cp27-cp27mu-linux_x86_64.whl>`_", "`paddlepaddle_gpu-latest-cp27-cp27m-linux_x86_64.whl <https://guest:@paddleci.ngrok.io/repository/download/Manylinux1_Cuda80cudnn5cp27cp27mu/.lastSuccessful/paddlepaddle_gpu-latest-cp27-cp27m-linux_x86_64.whl>`_"
+ "cuda8.0_cudnn7_avx_mkl", "`paddlepaddle_gpu-latest-cp27-cp27mu-linux_x86_64.whl <https://guest:@paddleci.ngrok.io/repository/download/Manylinux1_Cuda8cudnn7cp27cp27mu/.lastSuccessful/paddlepaddle_gpu-latest-cp27-cp27mu-linux_x86_64.whl>`_", "`paddlepaddle_gpu-latest-cp27-cp27m-linux_x86_64.whl <https://guest:@paddleci.ngrok.io/repository/download/Manylinux1_Cuda8cudnn7cp27cp27mu/.lastSuccessful/paddlepaddle_gpu-latest-cp27-cp27m-linux_x86_64.whl>`_"
.. _pip_dependency:
From 1c81301e6d3bf84f914287e615f1b0d801b8dbbd Mon Sep 17 00:00:00 2001
From: Krzysztof Binias <krzysztof.binias@intel.com>
Date: Fri, 11 May 2018 10:40:29 +0200
Subject: [PATCH 184/195] Update activations for MKL-DNN
---
.../fluid/operators/activation_mkldnn_op.cc | 21 +++++++++-------
paddle/fluid/operators/activation_op.cc | 25 ++++++++++++++++---
paddle/fluid/operators/mkldnn_activation_op.h | 14 ++++++-----
3 files changed, 41 insertions(+), 19 deletions(-)
diff --git a/paddle/fluid/operators/activation_mkldnn_op.cc b/paddle/fluid/operators/activation_mkldnn_op.cc
index ab7c612271..fcc06a7093 100644
--- a/paddle/fluid/operators/activation_mkldnn_op.cc
+++ b/paddle/fluid/operators/activation_mkldnn_op.cc
@@ -52,9 +52,11 @@ void eltwise_forward(const ExecContext &ctx, mkldnn::algorithm algorithm,
mkldnn::memory::format::nchw);
// create memory primitives
- auto src_memory =
+ auto src_memory = std::make_shared<mkldnn::memory>(
mkldnn::memory({data_md, mkldnn_engine},
- static_cast<void *>(const_cast<float *>(src_data)));
+ static_cast<void *>(const_cast<float *>(src_data))));
+ // save source memory to device context to be referred in backward path
+ dev_ctx.SetBlob("InputX@eltwise_pd", src_memory);
auto dst_memory =
mkldnn::memory({data_md, mkldnn_engine},
static_cast<void *>(const_cast<float *>(dst_data)));
@@ -69,7 +71,7 @@ void eltwise_forward(const ExecContext &ctx, mkldnn::algorithm algorithm,
forward_desc, mkldnn_engine);
dev_ctx.SetBlob(key_eltwise_pd, forward_pd);
- auto eltwise = mkldnn::eltwise_forward(*forward_pd, src_memory, dst_memory);
+ auto eltwise = mkldnn::eltwise_forward(*forward_pd, *src_memory, dst_memory);
// push primitive to stream and wait until it's executed
std::vector<mkldnn::primitive> pipeline = {eltwise};
@@ -83,8 +85,7 @@ void eltwise_grad(const ExecContext &ctx, mkldnn::algorithm algorithm,
const auto &mkldnn_engine = dev_ctx.GetEngine();
// get buffers
- const auto *x = ctx.template Input<Tensor>("X");
- const auto *src = x->template data<T>();
+ const auto *x = ctx.template Input<Tensor>("Out");
auto *dout = ctx.template Input<Tensor>(framework::GradVarName("Out"));
const auto *diff_dst = dout->template data<T>();
@@ -103,9 +104,11 @@ void eltwise_grad(const ExecContext &ctx, mkldnn::algorithm algorithm,
: platform::MKLDNNMemDesc(src_tz, mkldnn::memory::f32,
mkldnn::memory::format::nchw);
+ // retrieve source memory from device context
+ const std::shared_ptr<void> src_memory = dev_ctx.GetBlob("InputX@eltwise_pd");
+ auto *p_src_memory = static_cast<mkldnn::memory *>(src_memory.get());
+
// create memory primitives
- auto src_memory = mkldnn::memory(
- {data_md, mkldnn_engine}, static_cast<void *>(const_cast<float *>(src)));
auto diff_src_memory =
mkldnn::memory({data_md, mkldnn_engine},
static_cast<void *>(const_cast<float *>(diff_src)));
@@ -128,8 +131,8 @@ void eltwise_grad(const ExecContext &ctx, mkldnn::algorithm algorithm,
auto eltwise_bwd_prim_desc = mkldnn::eltwise_backward::primitive_desc(
backward_desc, mkldnn_engine, *p_forward_pd);
- auto eltwise_bwd = mkldnn::eltwise_backward(eltwise_bwd_prim_desc, src_memory,
- diff_dst_memory, diff_src_memory);
+ auto eltwise_bwd = mkldnn::eltwise_backward(
+ eltwise_bwd_prim_desc, *p_src_memory, diff_dst_memory, diff_src_memory);
// push primitive to stream and wait until it's executed
std::vector<mkldnn::primitive> pipeline = {eltwise_bwd};
diff --git a/paddle/fluid/operators/activation_op.cc b/paddle/fluid/operators/activation_op.cc
index 55482abdf0..6f7a965bcf 100644
--- a/paddle/fluid/operators/activation_op.cc
+++ b/paddle/fluid/operators/activation_op.cc
@@ -458,21 +458,22 @@ namespace ops = paddle::operators;
#define FOR_EACH_INPLACE_OP_FUNCTOR(__macro) \
__macro(Sigmoid, sigmoid); \
- __macro(Relu, relu); \
__macro(Exp, exp); \
- __macro(Tanh, tanh); \
__macro(Ceil, ceil); \
__macro(Floor, floor); \
- __macro(Sqrt, sqrt); \
__macro(SoftRelu, soft_relu); \
__macro(Relu6, relu6); \
__macro(Reciprocal, reciprocal); \
__macro(HardSigmoid, hard_sigmoid);
+#define FOR_EACH_MKLDNN_INPLACE_OP_FUNCTOR(__macro) \
+ __macro(Relu, relu); \
+ __macro(Tanh, tanh); \
+ __macro(Sqrt, sqrt);
+
#define FOR_EACH_OP_FUNCTOR(__macro) \
__macro(LogSigmoid, logsigmoid); \
__macro(SoftShrink, softshrink); \
- __macro(Abs, abs); \
__macro(Cos, cos); \
__macro(Sin, sin); \
__macro(Round, round); \
@@ -490,18 +491,32 @@ namespace ops = paddle::operators;
__macro(Swish, swish); \
__macro(ThresholdedRelu, thresholded_relu);
+#define FOR_EACH_MKLDNN_OP_FUNCTOR(__macro) __macro(Abs, abs);
+
#define REGISTER_INPLACE_ACTIVATION_OP(OP_NAME, KERNEL_TYPE) \
REGISTER_OPERATOR(KERNEL_TYPE, ::paddle::operators::ActivationOp, \
::paddle::operators::OP_NAME##OpMaker, \
::paddle::operators::OP_NAME##GradMaker); \
REGISTER_OPERATOR(KERNEL_TYPE##_grad, ::paddle::operators::ActivationOpGrad)
+#define REGISTER_INPLACE_ACTIVATION_MKLDNN_OP(OP_NAME, KERNEL_TYPE) \
+ REGISTER_OPERATOR(KERNEL_TYPE, ops::ActivationWithMKLDNNOp, \
+ ::paddle::operators::OP_NAME##OpMaker, \
+ ::paddle::operators::OP_NAME##GradMaker); \
+ REGISTER_OPERATOR(KERNEL_TYPE##_grad, ops::ActivationWithMKLDNNOpGrad)
+
#define REGISTER_ACTIVATION_OP(OP_NAME, KERNEL_TYPE) \
REGISTER_OPERATOR(KERNEL_TYPE, ::paddle::operators::ActivationOp, \
::paddle::operators::OP_NAME##OpMaker, \
::paddle::framework::DefaultGradOpDescMaker<true>); \
REGISTER_OPERATOR(KERNEL_TYPE##_grad, ::paddle::operators::ActivationOpGrad)
+#define REGISTER_ACTIVATION_MKLDNN_OP(OP_NAME, KERNEL_TYPE) \
+ REGISTER_OPERATOR(KERNEL_TYPE, ops::ActivationWithMKLDNNOp, \
+ ::paddle::operators::OP_NAME##OpMaker, \
+ ::paddle::framework::DefaultGradOpDescMaker<true>); \
+ REGISTER_OPERATOR(KERNEL_TYPE##_grad, ops::ActivationWithMKLDNNOpGrad)
+
#define REGISTER_ACTIVATION_CPU_KERNEL(act_type, functor, grad_functor) \
REGISTER_OP_CPU_KERNEL( \
act_type, ops::ActivationKernel<paddle::platform::CPUDeviceContext, \
@@ -516,5 +531,7 @@ namespace ops = paddle::operators;
ops::grad_functor<double>>);
FOR_EACH_OP_FUNCTOR(REGISTER_ACTIVATION_OP);
+FOR_EACH_MKLDNN_OP_FUNCTOR(REGISTER_ACTIVATION_MKLDNN_OP);
FOR_EACH_INPLACE_OP_FUNCTOR(REGISTER_INPLACE_ACTIVATION_OP);
+FOR_EACH_MKLDNN_INPLACE_OP_FUNCTOR(REGISTER_INPLACE_ACTIVATION_MKLDNN_OP);
FOR_EACH_KERNEL_FUNCTOR(REGISTER_ACTIVATION_CPU_KERNEL);
diff --git a/paddle/fluid/operators/mkldnn_activation_op.h b/paddle/fluid/operators/mkldnn_activation_op.h
index f26a165b5a..de8daed170 100644
--- a/paddle/fluid/operators/mkldnn_activation_op.h
+++ b/paddle/fluid/operators/mkldnn_activation_op.h
@@ -13,6 +13,8 @@ See the License for the specific language governing permissions and
limitations under the License. */
#pragma once
+#include <string>
+
#include "paddle/fluid/framework/eigen.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/operators/detail/safe_ref.h"
@@ -61,9 +63,9 @@ class MKLDNNActivationGradKernel
};
namespace { // NOLINT
-framework::OpKernelType GetKernelType(
- const framework::ExecutionContext& ctx,
- const framework::OperatorWithKernel& oper) {
+framework::OpKernelType GetKernelType(const framework::ExecutionContext& ctx,
+ const framework::OperatorWithKernel& oper,
+ const std::string& name) {
framework::LibraryType library{framework::LibraryType::kPlain};
#ifdef PADDLE_WITH_MKLDNN
if (library == framework::LibraryType::kPlain &&
@@ -73,7 +75,7 @@ framework::OpKernelType GetKernelType(
#endif
framework::DataLayout layout = framework::DataLayout::kAnyLayout;
return framework::OpKernelType(
- framework::ToDataType(ctx.Input<framework::Tensor>("X")->type()),
+ framework::ToDataType(ctx.Input<framework::Tensor>(name)->type()),
ctx.GetPlace(), layout, library);
}
} // anonymous namespace
@@ -89,7 +91,7 @@ class ActivationWithMKLDNNOp : public framework::OperatorWithKernel {
framework::OpKernelType GetExpectedKernelType(
const framework::ExecutionContext& ctx) const override {
- return GetKernelType(ctx, *this);
+ return GetKernelType(ctx, *this, "X");
}
};
@@ -103,7 +105,7 @@ class ActivationWithMKLDNNOpGrad : public framework::OperatorWithKernel {
framework::OpKernelType GetExpectedKernelType(
const framework::ExecutionContext& ctx) const override {
- return GetKernelType(ctx, *this);
+ return GetKernelType(ctx, *this, "Out");
}
};
From a76d0dd488934d2f8859234f1d8d0e6eccfd5c30 Mon Sep 17 00:00:00 2001
From: Krzysztof Binias <krzysztof.binias@intel.com>
Date: Mon, 14 May 2018 12:18:48 +0200
Subject: [PATCH 185/195] MKL-DNN activations improvements
---
paddle/fluid/operators/activation_op.cc | 58 +++++++++++--------
paddle/fluid/operators/mkldnn_activation_op.h | 47 ---------------
2 files changed, 34 insertions(+), 71 deletions(-)
diff --git a/paddle/fluid/operators/activation_op.cc b/paddle/fluid/operators/activation_op.cc
index 6f7a965bcf..dd71c66a75 100644
--- a/paddle/fluid/operators/activation_op.cc
+++ b/paddle/fluid/operators/activation_op.cc
@@ -41,7 +41,7 @@ namespace operators {
\
protected: \
std::unique_ptr<::paddle::framework::OpDesc> Apply() const override { \
- auto *op = new ::paddle::framework::OpDesc(); \
+ auto* op = new ::paddle::framework::OpDesc(); \
op->SetType(#KERNEL_TYPE "_grad"); \
op->SetInput("Out", Output("Out")); \
op->SetInput(::paddle::framework::GradVarName("Out"), \
@@ -54,23 +54,50 @@ namespace operators {
} \
}
+framework::OpKernelType GetKernelType(const framework::ExecutionContext& ctx,
+ const framework::OperatorWithKernel& oper,
+ const std::string& name) {
+ framework::LibraryType library{framework::LibraryType::kPlain};
+#ifdef PADDLE_WITH_MKLDNN
+ auto it = oper.Attrs().find("use_mkldnn");
+ if (library == framework::LibraryType::kPlain && it != oper.Attrs().end() &&
+ platform::CanMKLDNNBeUsed(ctx)) {
+ library = framework::LibraryType::kMKLDNN;
+ }
+#endif
+ framework::DataLayout layout = framework::DataLayout::kAnyLayout;
+ return framework::OpKernelType(
+ framework::ToDataType(ctx.Input<framework::Tensor>(name)->type()),
+ ctx.GetPlace(), layout, library);
+}
+
class ActivationOp : public framework::OperatorWithKernel {
public:
using framework::OperatorWithKernel::OperatorWithKernel;
- void InferShape(framework::InferShapeContext *ctx) const override {
+ void InferShape(framework::InferShapeContext* ctx) const override {
ctx->SetOutputDim("Out", ctx->GetInputDim("X"));
ctx->ShareLoD("X", /*->*/ "Out");
}
+
+ framework::OpKernelType GetExpectedKernelType(
+ const framework::ExecutionContext& ctx) const override {
+ return GetKernelType(ctx, *this, "X");
+ }
};
class ActivationOpGrad : public framework::OperatorWithKernel {
public:
using framework::OperatorWithKernel::OperatorWithKernel;
- void InferShape(framework::InferShapeContext *ctx) const override {
+ void InferShape(framework::InferShapeContext* ctx) const override {
ctx->SetOutputDim(framework::GradVarName("X"), ctx->GetInputDim("Out"));
}
+
+ framework::OpKernelType GetExpectedKernelType(
+ const framework::ExecutionContext& ctx) const override {
+ return GetKernelType(ctx, *this, "Out");
+ }
};
__attribute__((unused)) constexpr char SigmoidDoc[] = R"DOC(
@@ -458,22 +485,21 @@ namespace ops = paddle::operators;
#define FOR_EACH_INPLACE_OP_FUNCTOR(__macro) \
__macro(Sigmoid, sigmoid); \
+ __macro(Relu, relu); \
__macro(Exp, exp); \
+ __macro(Tanh, tanh); \
__macro(Ceil, ceil); \
__macro(Floor, floor); \
+ __macro(Sqrt, sqrt); \
__macro(SoftRelu, soft_relu); \
__macro(Relu6, relu6); \
__macro(Reciprocal, reciprocal); \
__macro(HardSigmoid, hard_sigmoid);
-#define FOR_EACH_MKLDNN_INPLACE_OP_FUNCTOR(__macro) \
- __macro(Relu, relu); \
- __macro(Tanh, tanh); \
- __macro(Sqrt, sqrt);
-
#define FOR_EACH_OP_FUNCTOR(__macro) \
__macro(LogSigmoid, logsigmoid); \
__macro(SoftShrink, softshrink); \
+ __macro(Abs, abs); \
__macro(Cos, cos); \
__macro(Sin, sin); \
__macro(Round, round); \
@@ -491,32 +517,18 @@ namespace ops = paddle::operators;
__macro(Swish, swish); \
__macro(ThresholdedRelu, thresholded_relu);
-#define FOR_EACH_MKLDNN_OP_FUNCTOR(__macro) __macro(Abs, abs);
-
#define REGISTER_INPLACE_ACTIVATION_OP(OP_NAME, KERNEL_TYPE) \
REGISTER_OPERATOR(KERNEL_TYPE, ::paddle::operators::ActivationOp, \
::paddle::operators::OP_NAME##OpMaker, \
::paddle::operators::OP_NAME##GradMaker); \
REGISTER_OPERATOR(KERNEL_TYPE##_grad, ::paddle::operators::ActivationOpGrad)
-#define REGISTER_INPLACE_ACTIVATION_MKLDNN_OP(OP_NAME, KERNEL_TYPE) \
- REGISTER_OPERATOR(KERNEL_TYPE, ops::ActivationWithMKLDNNOp, \
- ::paddle::operators::OP_NAME##OpMaker, \
- ::paddle::operators::OP_NAME##GradMaker); \
- REGISTER_OPERATOR(KERNEL_TYPE##_grad, ops::ActivationWithMKLDNNOpGrad)
-
#define REGISTER_ACTIVATION_OP(OP_NAME, KERNEL_TYPE) \
REGISTER_OPERATOR(KERNEL_TYPE, ::paddle::operators::ActivationOp, \
::paddle::operators::OP_NAME##OpMaker, \
::paddle::framework::DefaultGradOpDescMaker<true>); \
REGISTER_OPERATOR(KERNEL_TYPE##_grad, ::paddle::operators::ActivationOpGrad)
-#define REGISTER_ACTIVATION_MKLDNN_OP(OP_NAME, KERNEL_TYPE) \
- REGISTER_OPERATOR(KERNEL_TYPE, ops::ActivationWithMKLDNNOp, \
- ::paddle::operators::OP_NAME##OpMaker, \
- ::paddle::framework::DefaultGradOpDescMaker<true>); \
- REGISTER_OPERATOR(KERNEL_TYPE##_grad, ops::ActivationWithMKLDNNOpGrad)
-
#define REGISTER_ACTIVATION_CPU_KERNEL(act_type, functor, grad_functor) \
REGISTER_OP_CPU_KERNEL( \
act_type, ops::ActivationKernel<paddle::platform::CPUDeviceContext, \
@@ -531,7 +543,5 @@ namespace ops = paddle::operators;
ops::grad_functor<double>>);
FOR_EACH_OP_FUNCTOR(REGISTER_ACTIVATION_OP);
-FOR_EACH_MKLDNN_OP_FUNCTOR(REGISTER_ACTIVATION_MKLDNN_OP);
FOR_EACH_INPLACE_OP_FUNCTOR(REGISTER_INPLACE_ACTIVATION_OP);
-FOR_EACH_MKLDNN_INPLACE_OP_FUNCTOR(REGISTER_INPLACE_ACTIVATION_MKLDNN_OP);
FOR_EACH_KERNEL_FUNCTOR(REGISTER_ACTIVATION_CPU_KERNEL);
diff --git a/paddle/fluid/operators/mkldnn_activation_op.h b/paddle/fluid/operators/mkldnn_activation_op.h
index de8daed170..85664623d7 100644
--- a/paddle/fluid/operators/mkldnn_activation_op.h
+++ b/paddle/fluid/operators/mkldnn_activation_op.h
@@ -62,52 +62,5 @@ class MKLDNNActivationGradKernel
}
};
-namespace { // NOLINT
-framework::OpKernelType GetKernelType(const framework::ExecutionContext& ctx,
- const framework::OperatorWithKernel& oper,
- const std::string& name) {
- framework::LibraryType library{framework::LibraryType::kPlain};
-#ifdef PADDLE_WITH_MKLDNN
- if (library == framework::LibraryType::kPlain &&
- platform::CanMKLDNNBeUsed(ctx)) {
- library = framework::LibraryType::kMKLDNN;
- }
-#endif
- framework::DataLayout layout = framework::DataLayout::kAnyLayout;
- return framework::OpKernelType(
- framework::ToDataType(ctx.Input<framework::Tensor>(name)->type()),
- ctx.GetPlace(), layout, library);
-}
-} // anonymous namespace
-
-class ActivationWithMKLDNNOp : public framework::OperatorWithKernel {
- public:
- using framework::OperatorWithKernel::OperatorWithKernel;
-
- void InferShape(framework::InferShapeContext* ctx) const override {
- ctx->SetOutputDim("Out", ctx->GetInputDim("X"));
- ctx->ShareLoD("X", /*->*/ "Out");
- }
-
- framework::OpKernelType GetExpectedKernelType(
- const framework::ExecutionContext& ctx) const override {
- return GetKernelType(ctx, *this, "X");
- }
-};
-
-class ActivationWithMKLDNNOpGrad : public framework::OperatorWithKernel {
- public:
- using framework::OperatorWithKernel::OperatorWithKernel;
-
- void InferShape(framework::InferShapeContext* ctx) const override {
- ctx->SetOutputDim(framework::GradVarName("X"), ctx->GetInputDim("Out"));
- }
-
- framework::OpKernelType GetExpectedKernelType(
- const framework::ExecutionContext& ctx) const override {
- return GetKernelType(ctx, *this, "Out");
- }
-};
-
} // namespace operators
} // namespace paddle
From 0cc25a400b1a968f3500273727818af5ee7dc340 Mon Sep 17 00:00:00 2001
From: Krzysztof Binias <krzysztof.binias@intel.com>
Date: Wed, 16 May 2018 10:18:41 +0200
Subject: [PATCH 186/195] Realloc for forward
---
.../fluid/operators/activation_mkldnn_op.cc | 102 +++++++++++-------
1 file changed, 64 insertions(+), 38 deletions(-)
diff --git a/paddle/fluid/operators/activation_mkldnn_op.cc b/paddle/fluid/operators/activation_mkldnn_op.cc
index fcc06a7093..6f29192550 100644
--- a/paddle/fluid/operators/activation_mkldnn_op.cc
+++ b/paddle/fluid/operators/activation_mkldnn_op.cc
@@ -23,6 +23,13 @@ using paddle::framework::Tensor;
using paddle::platform::MKLDNNDeviceContext;
namespace {
+std::string gethash(const mkldnn::memory::dims &operand_dims,
+ const mkldnn::algorithm algorithm) {
+ return std::string(std::to_string(operand_dims[0]) + "-" +
+ std::to_string(operand_dims[1]) + "-" +
+ std::to_string(algorithm));
+}
+
template <typename T, typename ExecContext>
void eltwise_forward(const ExecContext &ctx, mkldnn::algorithm algorithm,
const T alpha = 0, const T beta = 0) {
@@ -44,37 +51,53 @@ void eltwise_forward(const ExecContext &ctx, mkldnn::algorithm algorithm,
"Input dim must be with 2 or 4");
std::vector<int> src_tz = framework::vectorize2int(src->dims());
- // create memory description
- auto data_md = src_tz.size() == 2
- ? platform::MKLDNNMemDesc(src_tz, mkldnn::memory::f32,
- mkldnn::memory::format::nc)
- : platform::MKLDNNMemDesc(src_tz, mkldnn::memory::f32,
- mkldnn::memory::format::nchw);
-
- // create memory primitives
- auto src_memory = std::make_shared<mkldnn::memory>(
- mkldnn::memory({data_md, mkldnn_engine},
- static_cast<void *>(const_cast<float *>(src_data))));
- // save source memory to device context to be referred in backward path
- dev_ctx.SetBlob("InputX@eltwise_pd", src_memory);
- auto dst_memory =
- mkldnn::memory({data_md, mkldnn_engine},
- static_cast<void *>(const_cast<float *>(dst_data)));
-
- auto forward_desc = mkldnn::eltwise_forward::desc(
- mkldnn::prop_kind::forward_training, algorithm, data_md, alpha, beta);
-
- // save prim desc into global device context to be referred in backward path
- const std::string key = ctx.op().Output("Out");
- const std::string key_eltwise_pd = key + "@eltwise_pd";
- auto forward_pd = std::make_shared<mkldnn::eltwise_forward::primitive_desc>(
- forward_desc, mkldnn_engine);
- dev_ctx.SetBlob(key_eltwise_pd, forward_pd);
-
- auto eltwise = mkldnn::eltwise_forward(*forward_pd, *src_memory, dst_memory);
+ const std::string key = gethash(src_tz, algorithm);
+ const std::string key_src_mem = key + "@eltwise_src_mem";
+ const std::string key_dst_mem = key + "@eltwise_dst_mem";
+ const std::string key_fwd = key + "@eltwise_fwd";
+
+ std::shared_ptr<void> p_src_mem = dev_ctx.GetBlob(key_src_mem);
+ std::shared_ptr<void> p_dst_mem = dev_ctx.GetBlob(key_dst_mem);
+ std::shared_ptr<void> p_fwd = dev_ctx.GetBlob(key_fwd);
+
+ if (p_src_mem == nullptr || p_dst_mem == nullptr || p_fwd == nullptr) {
+ // create memory description
+ auto data_md = src_tz.size() == 2
+ ? platform::MKLDNNMemDesc(src_tz, mkldnn::memory::f32,
+ mkldnn::memory::format::nc)
+ : platform::MKLDNNMemDesc(src_tz, mkldnn::memory::f32,
+ mkldnn::memory::format::nchw);
+
+ // create memory primitives
+ p_src_mem = std::make_shared<mkldnn::memory>(
+ mkldnn::memory({data_md, mkldnn_engine},
+ static_cast<void *>(const_cast<float *>(src_data))));
+ dev_ctx.SetBlob(key_src_mem, p_src_mem);
+
+ p_dst_mem = std::make_shared<mkldnn::memory>(
+ mkldnn::memory({data_md, mkldnn_engine},
+ static_cast<void *>(const_cast<float *>(dst_data))));
+ dev_ctx.SetBlob(key_dst_mem, p_dst_mem);
+
+ auto fwd_desc = mkldnn::eltwise_forward::desc(
+ mkldnn::prop_kind::forward_training, algorithm, data_md, alpha, beta);
+ auto p_fwd_pd = std::make_shared<mkldnn::eltwise_forward::primitive_desc>(
+ fwd_desc, mkldnn_engine);
+ p_fwd = std::make_shared<mkldnn::eltwise_forward>(
+ *(p_fwd_pd.get()), *(static_cast<mkldnn::memory *>(p_src_mem.get())),
+ *(static_cast<mkldnn::memory *>(p_dst_mem.get())));
+ dev_ctx.SetBlob(key_fwd, p_fwd);
+ } else {
+ std::static_pointer_cast<mkldnn::memory>(p_src_mem)->set_data_handle(
+ reinterpret_cast<void *>(const_cast<T *>(src_data)));
+
+ std::static_pointer_cast<mkldnn::memory>(p_dst_mem)->set_data_handle(
+ reinterpret_cast<void *>(const_cast<T *>(dst_data)));
+ }
// push primitive to stream and wait until it's executed
- std::vector<mkldnn::primitive> pipeline = {eltwise};
+ std::vector<mkldnn::primitive> pipeline = {
+ *(static_cast<mkldnn::eltwise_forward::primitive *>(p_fwd.get()))};
mkldnn::stream(mkldnn::stream::kind::eager).submit(pipeline).wait();
}
@@ -85,7 +108,7 @@ void eltwise_grad(const ExecContext &ctx, mkldnn::algorithm algorithm,
const auto &mkldnn_engine = dev_ctx.GetEngine();
// get buffers
- const auto *x = ctx.template Input<Tensor>("Out");
+ const auto *out = ctx.template Input<Tensor>("Out");
auto *dout = ctx.template Input<Tensor>(framework::GradVarName("Out"));
const auto *diff_dst = dout->template data<T>();
@@ -95,7 +118,12 @@ void eltwise_grad(const ExecContext &ctx, mkldnn::algorithm algorithm,
const T *diff_src = dx->template mutable_data<T>(ctx.GetPlace());
// get memory dim
- std::vector<int> src_tz = framework::vectorize2int(x->dims());
+ std::vector<int> src_tz = framework::vectorize2int(out->dims());
+
+ const std::string key = gethash(src_tz, algorithm);
+ const std::string key_src_mem = key + "@eltwise_src_mem";
+ const std::string key_dst_mem = key + "@eltwise_dst_mem";
+ const std::string key_fwd = key + "@eltwise_fwd";
// create memory description
auto data_md = src_tz.size() == 2
@@ -105,8 +133,8 @@ void eltwise_grad(const ExecContext &ctx, mkldnn::algorithm algorithm,
mkldnn::memory::format::nchw);
// retrieve source memory from device context
- const std::shared_ptr<void> src_memory = dev_ctx.GetBlob("InputX@eltwise_pd");
- auto *p_src_memory = static_cast<mkldnn::memory *>(src_memory.get());
+ const std::shared_ptr<void> src_mem = dev_ctx.GetBlob(key_src_mem);
+ auto *p_src_mem = static_cast<mkldnn::memory *>(src_mem.get());
// create memory primitives
auto diff_src_memory =
@@ -120,9 +148,7 @@ void eltwise_grad(const ExecContext &ctx, mkldnn::algorithm algorithm,
mkldnn::eltwise_backward::desc(algorithm, data_md, data_md, alpha, beta);
// retrieve eltwise primitive desc from device context
- const std::string key = ctx.op().Input("Out");
- const std::string key_eltwise_pd = key + "@eltwise_pd";
- const std::shared_ptr<void> forward_pd = dev_ctx.GetBlob(key_eltwise_pd);
+ const std::shared_ptr<void> forward_pd = dev_ctx.GetBlob(key_fwd);
PADDLE_ENFORCE(forward_pd != nullptr,
"Fail to find eltwise_pd in device context");
auto *p_forward_pd =
@@ -131,8 +157,8 @@ void eltwise_grad(const ExecContext &ctx, mkldnn::algorithm algorithm,
auto eltwise_bwd_prim_desc = mkldnn::eltwise_backward::primitive_desc(
backward_desc, mkldnn_engine, *p_forward_pd);
- auto eltwise_bwd = mkldnn::eltwise_backward(
- eltwise_bwd_prim_desc, *p_src_memory, diff_dst_memory, diff_src_memory);
+ auto eltwise_bwd = mkldnn::eltwise_backward(eltwise_bwd_prim_desc, *p_src_mem,
+ diff_dst_memory, diff_src_memory);
// push primitive to stream and wait until it's executed
std::vector<mkldnn::primitive> pipeline = {eltwise_bwd};
From 0aa01929c138f83d41ff187b08813813f2d49e14 Mon Sep 17 00:00:00 2001
From: Krzysztof Binias <krzysztof.binias@intel.com>
Date: Thu, 17 May 2018 15:31:43 +0200
Subject: [PATCH 187/195] Add backward
---
.../fluid/operators/activation_mkldnn_op.cc | 153 ++++++++++--------
paddle/fluid/platform/mkldnn_helper.h | 5 +
2 files changed, 95 insertions(+), 63 deletions(-)
diff --git a/paddle/fluid/operators/activation_mkldnn_op.cc b/paddle/fluid/operators/activation_mkldnn_op.cc
index 6f29192550..482095030f 100644
--- a/paddle/fluid/operators/activation_mkldnn_op.cc
+++ b/paddle/fluid/operators/activation_mkldnn_op.cc
@@ -15,6 +15,7 @@
#include "mkldnn.hpp"
#include "paddle/fluid/operators/activation_op.h"
#include "paddle/fluid/operators/mkldnn_activation_op.h"
+#include "paddle/fluid/platform/mkldnn_helper.h"
namespace paddle {
namespace operators {
@@ -25,9 +26,14 @@ using paddle::platform::MKLDNNDeviceContext;
namespace {
std::string gethash(const mkldnn::memory::dims &operand_dims,
const mkldnn::algorithm algorithm) {
- return std::string(std::to_string(operand_dims[0]) + "-" +
- std::to_string(operand_dims[1]) + "-" +
- std::to_string(algorithm));
+ auto dim2str = [](const mkldnn::memory::dims &operand_dims) {
+ std::string dstr = "";
+ for (size_t i = 0; i < operand_dims.size(); ++i) {
+ dstr += std::to_string(operand_dims[i]) + "-";
+ }
+ return dstr;
+ };
+ return dim2str(operand_dims) + std::to_string(algorithm);
}
template <typename T, typename ExecContext>
@@ -44,7 +50,7 @@ void eltwise_forward(const ExecContext &ctx, mkldnn::algorithm algorithm,
const auto *src_data = src->template data<T>();
auto *dst = ctx.template Output<Tensor>("Out");
- const T *dst_data = dst->template mutable_data<T>(ctx.GetPlace());
+ T *dst_data = dst->template mutable_data<T>(ctx.GetPlace());
// get memory dim
PADDLE_ENFORCE(src->dims().size() == 2 || src->dims().size() == 4,
@@ -52,15 +58,14 @@ void eltwise_forward(const ExecContext &ctx, mkldnn::algorithm algorithm,
std::vector<int> src_tz = framework::vectorize2int(src->dims());
const std::string key = gethash(src_tz, algorithm);
- const std::string key_src_mem = key + "@eltwise_src_mem";
- const std::string key_dst_mem = key + "@eltwise_dst_mem";
+ const std::string key_src_mem = key + "@eltwise_fwd_src_mem";
+ const std::string key_dst_mem = key + "@eltwise_fwd_dst_mem";
const std::string key_fwd = key + "@eltwise_fwd";
- std::shared_ptr<void> p_src_mem = dev_ctx.GetBlob(key_src_mem);
- std::shared_ptr<void> p_dst_mem = dev_ctx.GetBlob(key_dst_mem);
- std::shared_ptr<void> p_fwd = dev_ctx.GetBlob(key_fwd);
+ auto p_fwd = std::static_pointer_cast<mkldnn::eltwise_forward>(
+ dev_ctx.GetBlob(key_fwd));
- if (p_src_mem == nullptr || p_dst_mem == nullptr || p_fwd == nullptr) {
+ if (p_fwd == nullptr) {
// create memory description
auto data_md = src_tz.size() == 2
? platform::MKLDNNMemDesc(src_tz, mkldnn::memory::f32,
@@ -69,35 +74,40 @@ void eltwise_forward(const ExecContext &ctx, mkldnn::algorithm algorithm,
mkldnn::memory::format::nchw);
// create memory primitives
- p_src_mem = std::make_shared<mkldnn::memory>(
- mkldnn::memory({data_md, mkldnn_engine},
- static_cast<void *>(const_cast<float *>(src_data))));
+ auto p_src_mem = std::make_shared<mkldnn::memory>(mkldnn::memory(
+ {data_md, mkldnn_engine}, platform::to_void_cast(src_data)));
dev_ctx.SetBlob(key_src_mem, p_src_mem);
- p_dst_mem = std::make_shared<mkldnn::memory>(
- mkldnn::memory({data_md, mkldnn_engine},
- static_cast<void *>(const_cast<float *>(dst_data))));
+ auto p_dst_mem = std::make_shared<mkldnn::memory>(mkldnn::memory(
+ {data_md, mkldnn_engine}, platform::to_void_cast(dst_data)));
dev_ctx.SetBlob(key_dst_mem, p_dst_mem);
auto fwd_desc = mkldnn::eltwise_forward::desc(
mkldnn::prop_kind::forward_training, algorithm, data_md, alpha, beta);
auto p_fwd_pd = std::make_shared<mkldnn::eltwise_forward::primitive_desc>(
fwd_desc, mkldnn_engine);
+ const std::string key_fwd_pd = key + "eltwise_fwd_pd";
+ dev_ctx.SetBlob(key_fwd_pd, p_fwd_pd);
p_fwd = std::make_shared<mkldnn::eltwise_forward>(
- *(p_fwd_pd.get()), *(static_cast<mkldnn::memory *>(p_src_mem.get())),
- *(static_cast<mkldnn::memory *>(p_dst_mem.get())));
+ *p_fwd_pd, *(p_src_mem.get()), *(p_dst_mem.get()));
dev_ctx.SetBlob(key_fwd, p_fwd);
} else {
- std::static_pointer_cast<mkldnn::memory>(p_src_mem)->set_data_handle(
- reinterpret_cast<void *>(const_cast<T *>(src_data)));
-
- std::static_pointer_cast<mkldnn::memory>(p_dst_mem)->set_data_handle(
- reinterpret_cast<void *>(const_cast<T *>(dst_data)));
+ // primitives already exist
+ auto p_src_mem =
+ std::static_pointer_cast<mkldnn::memory>(dev_ctx.GetBlob(key_src_mem));
+ PADDLE_ENFORCE(p_src_mem != nullptr,
+ "Fail to find eltwise p_src_mem in device context.");
+ auto p_dst_mem =
+ std::static_pointer_cast<mkldnn::memory>(dev_ctx.GetBlob(key_dst_mem));
+ PADDLE_ENFORCE(p_dst_mem != nullptr,
+ "Fail to find eltwise p_src_mem in device context.");
+
+ p_src_mem->set_data_handle(platform::to_void_reinterpret_cast(src_data));
+ p_dst_mem->set_data_handle(dst_data);
}
// push primitive to stream and wait until it's executed
- std::vector<mkldnn::primitive> pipeline = {
- *(static_cast<mkldnn::eltwise_forward::primitive *>(p_fwd.get()))};
+ std::vector<mkldnn::primitive> pipeline = {*(p_fwd.get())};
mkldnn::stream(mkldnn::stream::kind::eager).submit(pipeline).wait();
}
@@ -121,47 +131,64 @@ void eltwise_grad(const ExecContext &ctx, mkldnn::algorithm algorithm,
std::vector<int> src_tz = framework::vectorize2int(out->dims());
const std::string key = gethash(src_tz, algorithm);
- const std::string key_src_mem = key + "@eltwise_src_mem";
- const std::string key_dst_mem = key + "@eltwise_dst_mem";
- const std::string key_fwd = key + "@eltwise_fwd";
- // create memory description
- auto data_md = src_tz.size() == 2
- ? platform::MKLDNNMemDesc(src_tz, mkldnn::memory::f32,
- mkldnn::memory::format::nc)
- : platform::MKLDNNMemDesc(src_tz, mkldnn::memory::f32,
- mkldnn::memory::format::nchw);
-
- // retrieve source memory from device context
- const std::shared_ptr<void> src_mem = dev_ctx.GetBlob(key_src_mem);
- auto *p_src_mem = static_cast<mkldnn::memory *>(src_mem.get());
-
- // create memory primitives
- auto diff_src_memory =
- mkldnn::memory({data_md, mkldnn_engine},
- static_cast<void *>(const_cast<float *>(diff_src)));
- auto diff_dst_memory =
- mkldnn::memory({data_md, mkldnn_engine},
- static_cast<void *>(const_cast<float *>(diff_dst)));
-
- auto backward_desc =
- mkldnn::eltwise_backward::desc(algorithm, data_md, data_md, alpha, beta);
-
- // retrieve eltwise primitive desc from device context
- const std::shared_ptr<void> forward_pd = dev_ctx.GetBlob(key_fwd);
- PADDLE_ENFORCE(forward_pd != nullptr,
- "Fail to find eltwise_pd in device context");
- auto *p_forward_pd =
- static_cast<mkldnn::eltwise_forward::primitive_desc *>(forward_pd.get());
-
- auto eltwise_bwd_prim_desc = mkldnn::eltwise_backward::primitive_desc(
- backward_desc, mkldnn_engine, *p_forward_pd);
-
- auto eltwise_bwd = mkldnn::eltwise_backward(eltwise_bwd_prim_desc, *p_src_mem,
- diff_dst_memory, diff_src_memory);
+ const std::string key_diff_src_mem = key + "@eltwise_diff_src_mem";
+ const std::string key_diff_dst_mem = key + "@eltwise_diff_dst_mem";
+ const std::string key_grad = key + "@eltwise_grad";
+
+ auto p_grad = std::static_pointer_cast<mkldnn::eltwise_forward::primitive>(
+ dev_ctx.GetBlob(key_grad));
+
+ if (p_grad == nullptr) {
+ // create memory description
+ auto data_md = src_tz.size() == 2
+ ? platform::MKLDNNMemDesc(src_tz, mkldnn::memory::f32,
+ mkldnn::memory::format::nc)
+ : platform::MKLDNNMemDesc(src_tz, mkldnn::memory::f32,
+ mkldnn::memory::format::nchw);
+
+ // create memory primitives
+ std::shared_ptr<void> p_diff_src_mem =
+ std::make_shared<mkldnn::memory>(mkldnn::memory(
+ {data_md, mkldnn_engine}, platform::to_void_cast(diff_src)));
+ dev_ctx.SetBlob(key_diff_src_mem, p_diff_src_mem);
+ std::shared_ptr<void> p_diff_dst_mem =
+ std::make_shared<mkldnn::memory>(mkldnn::memory(
+ {data_md, mkldnn_engine}, platform::to_void_cast(diff_dst)));
+ dev_ctx.SetBlob(key_diff_dst_mem, p_diff_dst_mem);
+
+ auto bwd_desc = mkldnn::eltwise_backward::desc(algorithm, data_md, data_md,
+ alpha, beta);
+
+ const std::string key_fwd_pd = key + "eltwise_fwd_pd";
+ auto *p_fwd_pd = static_cast<mkldnn::eltwise_forward::primitive_desc *>(
+ dev_ctx.GetBlob(key_fwd_pd).get());
+
+ auto eltwise_bwd_prim_desc = mkldnn::eltwise_backward::primitive_desc(
+ bwd_desc, mkldnn_engine, *p_fwd_pd);
+
+ const std::string key_src_mem = key + "@eltwise_fwd_src_mem";
+ const std::shared_ptr<void> p_src_mem = dev_ctx.GetBlob(key_src_mem);
+
+ p_grad = std::make_shared<mkldnn::eltwise_backward>(
+ eltwise_bwd_prim_desc, *static_cast<mkldnn::memory *>(p_src_mem.get()),
+ *(static_cast<mkldnn::memory *>(p_diff_dst_mem.get())),
+ *(static_cast<mkldnn::memory *>(p_diff_src_mem.get())));
+ } else {
+ // primitives already exist
+ auto p_diff_src_mem = std::static_pointer_cast<mkldnn::memory>(
+ dev_ctx.GetBlob(key_diff_src_mem));
+ auto p_diff_dst_mem = std::static_pointer_cast<mkldnn::memory>(
+ dev_ctx.GetBlob(key_diff_dst_mem));
+
+ p_diff_src_mem->set_data_handle(
+ platform::to_void_reinterpret_cast(diff_src));
+ p_diff_dst_mem->set_data_handle(
+ platform::to_void_reinterpret_cast(diff_dst));
+ }
// push primitive to stream and wait until it's executed
- std::vector<mkldnn::primitive> pipeline = {eltwise_bwd};
+ std::vector<mkldnn::primitive> pipeline = {*(p_grad.get())};
mkldnn::stream(mkldnn::stream::kind::eager).submit(pipeline).wait();
}
} // anonymous namespace
diff --git a/paddle/fluid/platform/mkldnn_helper.h b/paddle/fluid/platform/mkldnn_helper.h
index 56ed5912a1..f1187620d8 100644
--- a/paddle/fluid/platform/mkldnn_helper.h
+++ b/paddle/fluid/platform/mkldnn_helper.h
@@ -38,6 +38,11 @@ void* to_void_cast(const Type* t) {
return static_cast<void*>(const_cast<Type*>(t));
}
+template <typename Type>
+void* to_void_reinterpret_cast(const Type* t) {
+ return reinterpret_cast<void*>(const_cast<Type*>(t));
+}
+
template <class Type>
using tf_desc = typename Type::desc;
From 32929cdff09371bd2655fbf892d39284a7f42dff Mon Sep 17 00:00:00 2001
From: Krzysztof Binias <krzysztof.binias@intel.com>
Date: Thu, 17 May 2018 17:54:05 +0200
Subject: [PATCH 188/195] Cache input data
---
paddle/fluid/operators/activation_mkldnn_op.cc | 18 ++++++++++++++----
1 file changed, 14 insertions(+), 4 deletions(-)
diff --git a/paddle/fluid/operators/activation_mkldnn_op.cc b/paddle/fluid/operators/activation_mkldnn_op.cc
index 482095030f..fa9f78db5f 100644
--- a/paddle/fluid/operators/activation_mkldnn_op.cc
+++ b/paddle/fluid/operators/activation_mkldnn_op.cc
@@ -58,6 +58,7 @@ void eltwise_forward(const ExecContext &ctx, mkldnn::algorithm algorithm,
std::vector<int> src_tz = framework::vectorize2int(src->dims());
const std::string key = gethash(src_tz, algorithm);
+ const std::string key_src_data = key + "@eltwise_fwd_src_data";
const std::string key_src_mem = key + "@eltwise_fwd_src_mem";
const std::string key_dst_mem = key + "@eltwise_fwd_dst_mem";
const std::string key_fwd = key + "@eltwise_fwd";
@@ -65,6 +66,10 @@ void eltwise_forward(const ExecContext &ctx, mkldnn::algorithm algorithm,
auto p_fwd = std::static_pointer_cast<mkldnn::eltwise_forward>(
dev_ctx.GetBlob(key_fwd));
+ // save input data to be referred in backward path
+ auto p_src_data = std::make_shared<const T *>(src_data);
+ dev_ctx.SetBlob(key_src_data, p_src_data);
+
if (p_fwd == nullptr) {
// create memory description
auto data_md = src_tz.size() == 2
@@ -131,11 +136,19 @@ void eltwise_grad(const ExecContext &ctx, mkldnn::algorithm algorithm,
std::vector<int> src_tz = framework::vectorize2int(out->dims());
const std::string key = gethash(src_tz, algorithm);
-
const std::string key_diff_src_mem = key + "@eltwise_diff_src_mem";
const std::string key_diff_dst_mem = key + "@eltwise_diff_dst_mem";
const std::string key_grad = key + "@eltwise_grad";
+ const std::string key_src_data = key + "@eltwise_fwd_src_data";
+ const auto p_src_data =
+ std::static_pointer_cast<T *>(dev_ctx.GetBlob(key_src_data));
+
+ const std::string key_src_mem = key + "@eltwise_fwd_src_mem";
+ auto p_src_mem =
+ std::static_pointer_cast<mkldnn::memory>(dev_ctx.GetBlob(key_src_mem));
+ p_src_mem->set_data_handle(*p_src_data.get());
+
auto p_grad = std::static_pointer_cast<mkldnn::eltwise_forward::primitive>(
dev_ctx.GetBlob(key_grad));
@@ -167,9 +180,6 @@ void eltwise_grad(const ExecContext &ctx, mkldnn::algorithm algorithm,
auto eltwise_bwd_prim_desc = mkldnn::eltwise_backward::primitive_desc(
bwd_desc, mkldnn_engine, *p_fwd_pd);
- const std::string key_src_mem = key + "@eltwise_fwd_src_mem";
- const std::shared_ptr<void> p_src_mem = dev_ctx.GetBlob(key_src_mem);
-
p_grad = std::make_shared<mkldnn::eltwise_backward>(
eltwise_bwd_prim_desc, *static_cast<mkldnn::memory *>(p_src_mem.get()),
*(static_cast<mkldnn::memory *>(p_diff_dst_mem.get())),
From 24904b914cf2671dc43b248f31136bdb6e79c887 Mon Sep 17 00:00:00 2001
From: Krzysztof Binias <krzysztof.binias@intel.com>
Date: Mon, 21 May 2018 12:19:02 +0200
Subject: [PATCH 189/195] Unique key for input data
---
paddle/fluid/operators/activation_mkldnn_op.cc | 6 ++++--
1 file changed, 4 insertions(+), 2 deletions(-)
diff --git a/paddle/fluid/operators/activation_mkldnn_op.cc b/paddle/fluid/operators/activation_mkldnn_op.cc
index fa9f78db5f..b892ac77d9 100644
--- a/paddle/fluid/operators/activation_mkldnn_op.cc
+++ b/paddle/fluid/operators/activation_mkldnn_op.cc
@@ -58,7 +58,8 @@ void eltwise_forward(const ExecContext &ctx, mkldnn::algorithm algorithm,
std::vector<int> src_tz = framework::vectorize2int(src->dims());
const std::string key = gethash(src_tz, algorithm);
- const std::string key_src_data = key + "@eltwise_fwd_src_data";
+ const std::string key_src_data =
+ key + ctx.op().Output("Out") + "@eltwise_fwd_src_data";
const std::string key_src_mem = key + "@eltwise_fwd_src_mem";
const std::string key_dst_mem = key + "@eltwise_fwd_dst_mem";
const std::string key_fwd = key + "@eltwise_fwd";
@@ -140,7 +141,8 @@ void eltwise_grad(const ExecContext &ctx, mkldnn::algorithm algorithm,
const std::string key_diff_dst_mem = key + "@eltwise_diff_dst_mem";
const std::string key_grad = key + "@eltwise_grad";
- const std::string key_src_data = key + "@eltwise_fwd_src_data";
+ const std::string key_src_data =
+ key + ctx.op().Input("Out") + "@eltwise_fwd_src_data";
const auto p_src_data =
std::static_pointer_cast<T *>(dev_ctx.GetBlob(key_src_data));
From d0efd5a1037f622deaa5c4831164a3b325981755 Mon Sep 17 00:00:00 2001
From: weixing02 <wx_crome@163.com>
Date: Mon, 21 May 2018 18:39:47 +0800
Subject: [PATCH 190/195] Add pip install description
---
doc/v2/build_and_install/pip_install_cn.rst | 26 +++++++++++++++++----
doc/v2/build_and_install/pip_install_en.rst | 26 +++++++++++++++++----
2 files changed, 44 insertions(+), 8 deletions(-)
diff --git a/doc/v2/build_and_install/pip_install_cn.rst b/doc/v2/build_and_install/pip_install_cn.rst
index aa1dc6ee2c..9b84bb6425 100644
--- a/doc/v2/build_and_install/pip_install_cn.rst
+++ b/doc/v2/build_and_install/pip_install_cn.rst
@@ -10,20 +10,38 @@ PaddlePaddle可以使用常用的Python包管理工具
使用pip安装
------------------------------
-
-执行下面的命令即可在当前机器上安装PaddlePaddle的运行时环境，并自动下载安装依赖软件，版本为cpu_avx_openblas。
+执行下面的命令即可在当前机器上安装PaddlePaddle的运行时环境，并自动下载安装依赖软件。
.. code-block:: bash
pip install paddlepaddle
+当前的默认版本为0.12.0，cpu_avx_openblas，您可以通过指定版本号来安装其它版本，例如:
+
+ .. code-block:: bash
+
+ pip install paddlepaddle==0.11.0
+
-如果需要安装支持GPU的版本（cuda7.5_cudnn5_avx_openblas），需要执行：
+如果需要安装支持GPU的版本（cuda8.0_cudnn5_avx_openblas），需要执行：
.. code-block:: bash
pip install paddlepaddle-gpu
+当前的默认版本也是0.12.0，PaddlePaddle针对不同需求提供了更多版本的安装包，部分列表如下：
+
+================================= ========================================
+版本号 版本说明
+================================= ========================================
+paddlepaddle-gpu==0.12.0 使用CUDA 8.0和cuDNN 5编译的0.12.0版本
+paddlepaddle-gpu==0.11.0.post87 使用CUDA 8.0和cuDNN 7编译的0.11.0版本
+paddlepaddle-gpu==0.11.0.post8 使用CUDA 8.0和cuDNN 5编译的0.11.0版本
+paddlepaddle-gpu==0.11.0 使用CUDA 7.5和cuDNN 5编译的0.11.0版本
+================================= ========================================
+
+您可以在 `Release History <https://pypi.org/project/paddlepaddle-gpu/#history>`_ 中找到paddlepaddle-gpu的各个发行版本。
+
如果需要获取并安装最新的（开发分支）PaddlePaddle，可以从我们的CI系统中下载最新的whl安装包和c-api开发包并安装，
您可以从下面的表格中找到需要的版本：
@@ -68,7 +86,7 @@ PaddlePaddle发布的安装包会尽量对齐 `manylinux1 <https://www.python.or
------------------------------
- paddlepaddle*.whl is not a supported wheel on this platform.
-
+
出现这个问题的主要原因是，没有找到和当前系统匹配的paddlepaddle安装包。请检查Python版本是否为2.7系列。另外最新的pip官方源中的安装包默认是manylinux1标准，需要使用最新的pip (>9.0.0) 才可以安装。可以使用下面的命令更新您的pip：
.. code-block:: bash
diff --git a/doc/v2/build_and_install/pip_install_en.rst b/doc/v2/build_and_install/pip_install_en.rst
index a70821eb48..fcac76d6a2 100644
--- a/doc/v2/build_and_install/pip_install_en.rst
+++ b/doc/v2/build_and_install/pip_install_en.rst
@@ -12,20 +12,38 @@ Install using pip
------------------------------
Run the following command to install PaddlePaddle on the current
-machine, it will also download requirements, the version is cpu_avx_openblas.
+machine, it will also download requirements.
.. code-block:: bash
pip install paddlepaddle
+the default version is 0.12.0, cpu_avx_openblas, you can specify the versions to satisfy your demands, like:
-If you wish to install GPU version (cuda7.5_cudnn5_avx_openblas), just run:
+ .. code-block:: bash
+
+ pip install paddlepaddle==0.11.0
+
+If you need to install a GPU-enabled version (cuda8.0_cudnn5_avx_openblas), you need to run:
.. code-block:: bash
pip install paddlepaddle-gpu
-If you wish to install the latest develop branch PaddlePaddle,
+The default version is also 0.12.0, PaddlePaddle provides several versions of packages for different needs, as shown in the table:
+
+================================= ========================================
+版本号 版本说明
+================================= ========================================
+paddlepaddle-gpu==0.12.0 0.12.0 built with CUDA 8.0 and cuDNN 5
+paddlepaddle-gpu==0.11.0.post87 0.11.0 built with CUDA 8.0 and cuDNN 7
+paddlepaddle-gpu==0.11.0.post8 0.11.0 built with CUDA 8.0 and cuDNN 5
+paddlepaddle-gpu==0.11.0 0.11.0 built with CUDA 7.5 and cuDNN 5
+================================= ========================================
+
+You can find all versions released of paddlepaddle-gpu in `Release History <https://pypi.org/project/paddlepaddle-gpu/#history>`_ .
+
+If you wish to install the latest develop branch PaddlePaddle,
you can download the latest whl package from our CI system. Access
the below links, log in as guest, then click at the "Artifact"
tab, you'll find the download link of whl packages.
@@ -78,7 +96,7 @@ FAQ
------------------------------
- paddlepaddle*.whl is not a supported wheel on this platform.
-
+
The main cause of this issue is that your current platform is
not supported. Please check that you are using Python 2.7 series.
Besides, pypi only supports manylinux1 standard, you'll need to
From 50e60ef321fdcacd460a1f1e9dcd12f3e3005760 Mon Sep 17 00:00:00 2001
From: Luo Tao <luotao02@baidu.com>
Date: Mon, 21 May 2018 19:01:08 +0800
Subject: [PATCH 191/195] add version and cmakecache in inference_lib
---
cmake/inference_lib.cmake | 20 ++++++++++++++++++++
1 file changed, 20 insertions(+)
diff --git a/cmake/inference_lib.cmake b/cmake/inference_lib.cmake
index 1144ca7f43..7117a3a4f3 100644
--- a/cmake/inference_lib.cmake
+++ b/cmake/inference_lib.cmake
@@ -162,4 +162,24 @@ copy(pybind_lib
DSTS ${dst_dir}/${module}
)
+# CMakeCache Info
+copy(cmake_cache
+ SRCS ${CMAKE_CURRENT_BINARY_DIR}/CMakeCache.txt
+ DSTS ${CMAKE_INSTALL_PREFIX})
+
add_custom_target(inference_lib_dist DEPENDS ${inference_lib_dist_dep})
+
+# paddle fluid version
+execute_process(
+ COMMAND ${GIT_EXECUTABLE} log --pretty=format:%H -1
+ OUTPUT_VARIABLE PADDLE_GIT_COMMIT)
+set(version_file ${CMAKE_INSTALL_PREFIX}/version.txt)
+file(WRITE ${version_file}
+ "GIT COMMIT ID: ${PADDLE_GIT_COMMIT}\n"
+ "WITH_MKL: ${WITH_MKL}\n"
+ "WITH_GPU: ${WITH_GPU}\n")
+if(WITH_GPU)
+ file(APPEND ${version_file}
+ "CUDA version: ${CUDA_VERSION}\n"
+ "CUDNN version: v${CUDNN_MAJOR_VERSION}\n")
+endif()
From f0c4088a886b87ffcbdb1052370c10b290458285 Mon Sep 17 00:00:00 2001
From: Lei Wang <bestwanglei@gmail.com>
Date: Mon, 21 May 2018 10:56:46 -0700
Subject: [PATCH 192/195] Build: remove fixed container name to allow multiple
build together. (#10780)
---
paddle/scripts/paddle_docker_build.sh | 14 --------------
1 file changed, 14 deletions(-)
diff --git a/paddle/scripts/paddle_docker_build.sh b/paddle/scripts/paddle_docker_build.sh
index 77588b8872..3462deb9c2 100755
--- a/paddle/scripts/paddle_docker_build.sh
+++ b/paddle/scripts/paddle_docker_build.sh
@@ -14,20 +14,9 @@
# See the License for the specific language governing permissions and
# limitations under the License.
-function container_running() {
- name=$1
- docker ps -a --format "{{.Names}}" | grep "${name}" > /dev/null
- return $?
-}
-
function start_build_docker() {
docker pull $IMG
- if container_running "${CONTAINER_ID}"; then
- docker stop "${CONTAINER_ID}" 1>/dev/null
- docker rm -f "${CONTAINER_ID}" 1>/dev/null
- fi
-
apt_mirror='s#http://archive.ubuntu.com/ubuntu#mirror://mirrors.ubuntu.com/mirrors.txt#g'
DOCKER_ENV=$(cat <<EOL
-e FLAGS_fraction_of_gpu_memory_to_use=0.15 \
@@ -61,7 +50,6 @@ EOL
fi
set -ex
${DOCKER_CMD} run -it \
- --name $CONTAINER_ID \
${DOCKER_ENV} \
-e SCRIPT_NAME=$0 \
-v $PADDLE_ROOT:/paddle \
@@ -75,10 +63,8 @@ EOL
function main() {
DOCKER_REPO="paddlepaddle/paddle"
VERSION="latest-dev"
- CONTAINER_ID="${USER}_paddle_dev"
PADDLE_ROOT="$( cd "$( dirname "${BASH_SOURCE[0]}")/../../" && pwd )"
if [ "$1" == "build_android" ]; then
- CONTAINER_ID="${USER}_paddle_dev_android"
VERSION="latest-dev-android"
fi
IMG=${DOCKER_REPO}:${VERSION}
From f6543a118141b28410c859feb551f0fa9bae7c02 Mon Sep 17 00:00:00 2001
From: Siddharth Goyal <vi.siddharth78@gmail.com>
Date: Mon, 21 May 2018 15:25:26 -0700
Subject: [PATCH 193/195] [Test-driven] Implementing sentiment_analysis with
new API (#10812)
---
.../tests/book/high-level-api/CMakeLists.txt | 1 +
.../understand_sentiment/CMakeLists.txt | 7 ++
...test_understand_sentiment_stacked_lstm.py} | 90 +++++++++++--------
3 files changed, 61 insertions(+), 37 deletions(-)
create mode 100644 python/paddle/fluid/tests/book/high-level-api/understand_sentiment/CMakeLists.txt
rename python/paddle/fluid/tests/book/high-level-api/understand_sentiment/{notest_understand_sentiment_stacked_lstm.py => test_understand_sentiment_stacked_lstm.py} (63%)
diff --git a/python/paddle/fluid/tests/book/high-level-api/CMakeLists.txt b/python/paddle/fluid/tests/book/high-level-api/CMakeLists.txt
index da76747f82..182e30a6a9 100644
--- a/python/paddle/fluid/tests/book/high-level-api/CMakeLists.txt
+++ b/python/paddle/fluid/tests/book/high-level-api/CMakeLists.txt
@@ -9,3 +9,4 @@ endforeach()
add_subdirectory(fit_a_line)
add_subdirectory(recognize_digits)
add_subdirectory(image_classification)
+add_subdirectory(understand_sentiment)
diff --git a/python/paddle/fluid/tests/book/high-level-api/understand_sentiment/CMakeLists.txt b/python/paddle/fluid/tests/book/high-level-api/understand_sentiment/CMakeLists.txt
new file mode 100644
index 0000000000..673c965b66
--- /dev/null
+++ b/python/paddle/fluid/tests/book/high-level-api/understand_sentiment/CMakeLists.txt
@@ -0,0 +1,7 @@
+file(GLOB TEST_OPS RELATIVE "${CMAKE_CURRENT_SOURCE_DIR}" "test_*.py")
+string(REPLACE ".py" "" TEST_OPS "${TEST_OPS}")
+
+# default test
+foreach(src ${TEST_OPS})
+ py_test(${src} SRCS ${src}.py)
+endforeach()
diff --git a/python/paddle/fluid/tests/book/high-level-api/understand_sentiment/notest_understand_sentiment_stacked_lstm.py b/python/paddle/fluid/tests/book/high-level-api/understand_sentiment/test_understand_sentiment_stacked_lstm.py
similarity index 63%
rename from python/paddle/fluid/tests/book/high-level-api/understand_sentiment/notest_understand_sentiment_stacked_lstm.py
rename to python/paddle/fluid/tests/book/high-level-api/understand_sentiment/test_understand_sentiment_stacked_lstm.py
index 9948e5c023..0d7cbe3874 100644
--- a/python/paddle/fluid/tests/book/high-level-api/understand_sentiment/notest_understand_sentiment_stacked_lstm.py
+++ b/python/paddle/fluid/tests/book/high-level-api/understand_sentiment/test_understand_sentiment_stacked_lstm.py
@@ -17,11 +17,13 @@ from __future__ import print_function
import paddle
import paddle.fluid as fluid
from functools import partial
+import numpy as np
CLASS_DIM = 2
EMB_DIM = 128
HID_DIM = 512
STACKED_NUM = 3
+BATCH_SIZE = 128
def stacked_lstm_net(data, input_dim, class_dim, emb_dim, hid_dim, stacked_num):
@@ -50,7 +52,7 @@ def stacked_lstm_net(data, input_dim, class_dim, emb_dim, hid_dim, stacked_num):
return prediction
-def inference_network(word_dict):
+def inference_program(word_dict):
data = fluid.layers.data(
name="words", shape=[1], dtype="int64", lod_level=1)
@@ -60,57 +62,71 @@ def inference_network(word_dict):
return net
-def train_network(word_dict):
- prediction = inference_network(word_dict)
+def train_program(word_dict):
+ prediction = inference_program(word_dict)
label = fluid.layers.data(name="label", shape=[1], dtype="int64")
cost = fluid.layers.cross_entropy(input=prediction, label=label)
avg_cost = fluid.layers.mean(cost)
accuracy = fluid.layers.accuracy(input=prediction, label=label)
- return avg_cost, accuracy
+ return [avg_cost, accuracy]
-def train(use_cuda, save_path):
- BATCH_SIZE = 128
- EPOCH_NUM = 5
+def train(use_cuda, train_program, save_dirname):
+ place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
+ optimizer = fluid.optimizer.Adagrad(learning_rate=0.002)
word_dict = paddle.dataset.imdb.word_dict()
+ trainer = fluid.Trainer(
+ train_func=partial(train_program, word_dict),
+ place=place,
+ optimizer=optimizer)
- train_data = paddle.batch(
+ def event_handler(event):
+ if isinstance(event, fluid.EndEpochEvent):
+ test_reader = paddle.batch(
+ paddle.dataset.imdb.test(word_dict), batch_size=BATCH_SIZE)
+ avg_cost, acc = trainer.test(
+ reader=test_reader, feed_order=['words', 'label'])
+
+ print("avg_cost: %s" % avg_cost)
+ print("acc : %s" % acc)
+
+ if acc > 0.2: # Smaller value to increase CI speed
+ trainer.save_params(save_dirname)
+ trainer.stop()
+
+ else:
+ print('BatchID {0}, Test Loss {1:0.2}, Acc {2:0.2}'.format(
+ event.epoch + 1, avg_cost, acc))
+ if math.isnan(avg_cost):
+ sys.exit("got NaN loss, training failed.")
+ elif isinstance(event, fluid.EndStepEvent):
+ print("Step {0}, Epoch {1} Metrics {2}".format(
+ event.step, event.epoch, map(np.array, event.metrics)))
+ if event.step == 1: # Run 2 iterations to speed CI
+ trainer.save_params(save_dirname)
+ trainer.stop()
+
+ train_reader = paddle.batch(
paddle.reader.shuffle(
- paddle.dataset.imdb.train(word_dict), buf_size=1000),
+ paddle.dataset.imdb.train(word_dict), buf_size=25000),
batch_size=BATCH_SIZE)
- test_data = paddle.batch(
- paddle.dataset.imdb.test(word_dict), batch_size=BATCH_SIZE)
-
- def event_handler(event):
- if isinstance(event, fluid.EndIteration):
- if (event.batch_id % 10) == 0:
- avg_cost, accuracy = trainer.test(reader=test_data)
-
- print('BatchID {1:04}, Loss {2:2.2}, Acc {3:2.2}'.format(
- event.batch_id + 1, avg_cost, accuracy))
+ trainer.train(
+ num_epochs=1,
+ event_handler=event_handler,
+ reader=train_reader,
+ feed_order=['words', 'label'])
- if accuracy > 0.01: # Low threshold for speeding up CI
- trainer.params.save(save_path)
- return
- place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
- trainer = fluid.Trainer(
- partial(train_network, word_dict),
- optimizer=fluid.optimizer.Adagrad(learning_rate=0.002),
- place=place,
- event_handler=event_handler)
-
- trainer.train(train_data, EPOCH_NUM, event_handler=event_handler)
-
-
-def infer(use_cuda, save_path):
- params = fluid.Params(save_path)
+def infer(use_cuda, inference_program, save_dirname=None):
place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
word_dict = paddle.dataset.imdb.word_dict()
+
inferencer = fluid.Inferencer(
- partial(inference_network, word_dict), params, place=place)
+ infer_func=partial(inference_program, word_dict),
+ param_path=save_dirname,
+ place=place)
def create_random_lodtensor(lod, place, low, high):
data = np.random.random_integers(low, high,
@@ -131,8 +147,8 @@ def main(use_cuda):
if use_cuda and not fluid.core.is_compiled_with_cuda():
return
save_path = "understand_sentiment_stacked_lstm.inference.model"
- train(use_cuda, save_path)
- infer(use_cuda, save_path)
+ train(use_cuda, train_program, save_path)
+ infer(use_cuda, inference_program, save_path)
if __name__ == '__main__':
From be26b71b9eae07781838d422f4d10d1354f88286 Mon Sep 17 00:00:00 2001
From: Qiao Longfei <qiaolongfei@baidu.com>
Date: Tue, 22 May 2018 09:40:17 +0800
Subject: [PATCH 194/195] Add cpp trainer lib and demo (#10681)
add cpp trainer lib and demo
---
paddle/fluid/train/demo/CMakeLists.txt | 66 +++++++++++++++
paddle/fluid/train/demo/README.md | 66 +++++++++++++++
paddle/fluid/train/demo/demo_network.py | 47 +++++++++++
paddle/fluid/train/demo/demo_trainer.cc | 103 ++++++++++++++++++++++++
4 files changed, 282 insertions(+)
create mode 100644 paddle/fluid/train/demo/CMakeLists.txt
create mode 100644 paddle/fluid/train/demo/README.md
create mode 100644 paddle/fluid/train/demo/demo_network.py
create mode 100644 paddle/fluid/train/demo/demo_trainer.cc
diff --git a/paddle/fluid/train/demo/CMakeLists.txt b/paddle/fluid/train/demo/CMakeLists.txt
new file mode 100644
index 0000000000..78d6e5ff55
--- /dev/null
+++ b/paddle/fluid/train/demo/CMakeLists.txt
@@ -0,0 +1,66 @@
+cmake_minimum_required(VERSION 3.0)
+
+project(cpp_train_demo CXX C)
+
+set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++11")
+
+if(NOT DEFINED PADDLE_LIB)
+ message(FATAL_ERROR "please set PADDLE_LIB with -DPADDLE_LIB=/paddle/lib/dir")
+endif()
+
+option(WITH_MKLDNN "Compile PaddlePaddle with MKLDNN" OFF)
+option(WITH_MKL "Compile PaddlePaddle with MKL support, default use openblas." OFF)
+
+include_directories("${PADDLE_LIB}")
+include_directories("${PADDLE_LIB}/third_party/install/protobuf/include")
+include_directories("${PADDLE_LIB}/third_party/install/glog/include")
+include_directories("${PADDLE_LIB}/third_party/install/gflags/include")
+include_directories("${PADDLE_LIB}/third_party/install/snappy/include")
+include_directories("${PADDLE_LIB}/third_party/install/snappystream/include")
+include_directories("${PADDLE_LIB}/third_party/install/zlib/include")
+
+include_directories("${PADDLE_LIB}/third_party/boost")
+include_directories("${PADDLE_LIB}/third_party/eigen3")
+
+link_directories("${PADDLE_LIB}/third_party/install/snappy/lib")
+link_directories("${PADDLE_LIB}/third_party/install/snappystream/lib")
+link_directories("${PADDLE_LIB}/third_party/install/protobuf/lib")
+link_directories("${PADDLE_LIB}/third_party/install/glog/lib")
+link_directories("${PADDLE_LIB}/third_party/install/gflags/lib")
+link_directories("${PADDLE_LIB}/third_party/install/zlib/lib")
+
+add_executable(demo_trainer demo_trainer.cc)
+
+if(WITH_MKLDNN)
+ include_directories("${PADDLE_LIB}/third_party/install/mkldnn/include")
+ set(MKLDNN_LIB ${PADDLE_LIB}/third_party/install/mkldnn/lib/libmkldnn.so.0)
+endif()
+
+if(WITH_MKL)
+ include_directories("${PADDLE_LIB}/third_party/install/mklml/include")
+ set(MATH_LIB ${PADDLE_LIB}/third_party/install/mklml/lib/libmklml_intel.so)
+else()
+ if(APPLE)
+ set(MATH_LIB cblas)
+ else(APPLE)
+ set(MATH_LIB ${PADDLE_LIB}/third_party/install/openblas/lib/libopenblas.a)
+ endif(APPLE)
+endif()
+
+if(APPLE)
+ set(MACOS_LD_FLAGS "-undefined dynamic_lookup -Wl,-all_load -framework CoreFoundation -framework Security")
+else(APPLE)
+ set(ARCHIVE_START "-Wl,--whole-archive")
+ set(ARCHIVE_END "-Wl,--no-whole-archive")
+ set(EXTERNAL_LIB "-lrt -ldl -lpthread")
+endif(APPLE)
+
+target_link_libraries(demo_trainer
+ ${MACOS_LD_FLAGS}
+ ${ARCHIVE_START}
+ ${PADDLE_LIB}/paddle/fluid/inference/libpaddle_fluid.a
+ ${ARCHIVE_END}
+ ${MATH_LIB}
+ ${MKLDNN_LIB}
+ glog gflags protobuf snappystream snappy z
+ ${EXTERNAL_LIB})
diff --git a/paddle/fluid/train/demo/README.md b/paddle/fluid/train/demo/README.md
new file mode 100644
index 0000000000..fd80a77b02
--- /dev/null
+++ b/paddle/fluid/train/demo/README.md
@@ -0,0 +1,66 @@
+
+### step 1. build paddle lib
+
+```
+
+# WITH_MKL=ON|OFF
+# WITH_MKLDNN=ON|OFF
+
+PADDLE_LIB=/paddle/lib/dir
+cmake .. -DCMAKE_INSTALL_PREFIX=$PADDLE_LIB \
+ -DCMAKE_BUILD_TYPE=Release \
+ -DWITH_FLUID_ONLY=ON \
+ -DWITH_GPU=OFF \
+ -DWITH_STYLE_CHECK=OFF \
+ -DWITH_MKL=OFF \
+ -DWITH_MKLDNN=OFF
+make -j8
+make -j8 inference_lib_dist
+```
+
+### step 2. generate program desc
+```
+# please install paddle before run this scripe
+pip install --upgrade paddlepaddle-*.whl
+python demo_network.py
+```
+
+This will generate two program desc files:
+ - startup_program: used to init all parameters
+ - main_program: main logic of the network
+
+### step 3. build demo_trainer and run it.
+
+
+```
+# Make a build dir at the same dir of this README.md document.
+# The demo dir can be put anywhere.
+mkdir build
+cd build
+
+# WITH_MKL=ON|OFF
+# WITH_MKLDNN=ON|OFF
+PADDLE_LIB=/paddle/lib/dir
+
+# PADDLE_LIB is the same with CMAKE_INSTALL_PREFIX when building the lib
+cmake .. -DPADDLE_LIB=$PADDLE_LIB \
+ -DWITH_MKLDNN=OFF \
+ -DWITH_MKL=OFF
+make
+
+# copy startup_program and main_program to this dir
+cp ../startup_program .
+cp ../main_program .
+
+# run demo cpp trainer
+./demo_trainer
+
+```
+
+The output will be:
+```
+step: 0 loss: 1069.02
+step: 1 loss: 1069.02
+step: 2 loss: 1069.02
+....
+```
diff --git a/paddle/fluid/train/demo/demo_network.py b/paddle/fluid/train/demo/demo_network.py
new file mode 100644
index 0000000000..41e98c6a24
--- /dev/null
+++ b/paddle/fluid/train/demo/demo_network.py
@@ -0,0 +1,47 @@
+# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import paddle.fluid as fluid
+import paddle.fluid.framework as framework
+
+
+def train_network(with_optimize):
+ x = fluid.layers.data(name='x', shape=[13], dtype='float32')
+ y_predict = fluid.layers.fc(input=x, size=1, act=None)
+
+ y = fluid.layers.data(name='y', shape=[1], dtype='float32')
+ cost = fluid.layers.square_error_cost(input=y_predict, label=y)
+ avg_cost = fluid.layers.mean(cost)
+
+ if with_optimize:
+ sgd_optimizer = fluid.optimizer.SGD(learning_rate=0.00001)
+ sgd_optimizer.minimize(avg_cost)
+ else:
+ fluid.backward.append_backward(avg_cost)
+
+
+def save_program_desc(network_func):
+ startup_program = framework.Program()
+ train_program = framework.Program()
+
+ with framework.program_guard(train_program, startup_program):
+ network_func(with_optimize=False)
+
+ with open("startup_program", "w") as f:
+ f.write(startup_program.desc.serialize_to_string())
+ with open("main_program", "w") as f:
+ f.write(train_program.desc.serialize_to_string())
+
+
+save_program_desc(train_network)
diff --git a/paddle/fluid/train/demo/demo_trainer.cc b/paddle/fluid/train/demo/demo_trainer.cc
new file mode 100644
index 0000000000..813d838686
--- /dev/null
+++ b/paddle/fluid/train/demo/demo_trainer.cc
@@ -0,0 +1,103 @@
+// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+// http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include <fstream>
+
+#include "paddle/fluid/framework/executor.h"
+#include "paddle/fluid/framework/init.h"
+#include "paddle/fluid/framework/op_registry.h"
+#include "paddle/fluid/framework/program_desc.h"
+#include "paddle/fluid/framework/tensor_util.h"
+#include "paddle/fluid/platform/device_context.h"
+#include "paddle/fluid/platform/place.h"
+
+namespace paddle {
+namespace train {
+
+void ReadBinaryFile(const std::string& filename, std::string* contents) {
+ std::ifstream fin(filename, std::ios::in | std::ios::binary);
+ PADDLE_ENFORCE(static_cast<bool>(fin), "Cannot open file %s", filename);
+ fin.seekg(0, std::ios::end);
+ contents->clear();
+ contents->resize(fin.tellg());
+ fin.seekg(0, std::ios::beg);
+ fin.read(&(contents->at(0)), contents->size());
+ fin.close();
+}
+
+std::unique_ptr<paddle::framework::ProgramDesc> Load(
+ paddle::framework::Executor* executor, const std::string& model_filename) {
+ VLOG(3) << "loading model from " << model_filename;
+ std::string program_desc_str;
+ ReadBinaryFile(model_filename, &program_desc_str);
+
+ std::unique_ptr<paddle::framework::ProgramDesc> main_program(
+ new paddle::framework::ProgramDesc(program_desc_str));
+ return main_program;
+}
+
+} // namespace train
+} // namespace paddle
+
+int main() {
+ paddle::framework::InitDevices(false);
+
+ const auto cpu_place = paddle::platform::CPUPlace();
+
+ paddle::framework::Executor executor(cpu_place);
+ paddle::framework::Scope scope;
+ auto startup_program = paddle::train::Load(&executor, "startup_program");
+ auto train_program = paddle::train::Load(&executor, "main_program");
+
+ std::string loss_name = "";
+ for (auto op_desc : train_program->Block(0).AllOps()) {
+ if (op_desc->Type() == "mean") {
+ loss_name = op_desc->Output("Out")[0];
+ break;
+ }
+ }
+
+ PADDLE_ENFORCE_NE(loss_name, "", "loss not found");
+
+ // init all parameters
+ executor.Run(*startup_program.get(), &scope, 0);
+
+ // prepare data
+ auto x_var = scope.Var("x");
+ auto x_tensor = x_var->GetMutable<paddle::framework::LoDTensor>();
+ x_tensor->Resize({2, 13});
+
+ auto x_data = x_tensor->mutable_data<float>(cpu_place);
+ for (int i = 0; i < 2 * 13; ++i) {
+ x_data[i] = static_cast<float>(i);
+ }
+
+ auto y_var = scope.Var("y");
+ auto y_tensor = y_var->GetMutable<paddle::framework::LoDTensor>();
+ y_tensor->Resize({2, 1});
+ auto y_data = y_tensor->mutable_data<float>(cpu_place);
+ for (int i = 0; i < 2 * 1; ++i) {
+ y_data[i] = static_cast<float>(i);
+ }
+
+ auto loss_var = scope.Var(loss_name);
+
+ for (int i = 0; i < 10; ++i) {
+ executor.Run(*train_program.get(), &scope, 0, false, true);
+ std::cout << "step: " << i << " loss: "
+ << loss_var->Get<paddle::framework::LoDTensor>().data<float>()[0]
+ << std::endl;
+ }
+ return 0;
+}
From 2a77fc507b6f6012871868af296341b37a350da3 Mon Sep 17 00:00:00 2001
From: qingqing01 <dangqingqing@baidu.com>
Date: Tue, 22 May 2018 09:59:00 +0800
Subject: [PATCH 195/195] Enhance detection_map_op and more check in prior_box
API. (#10796)
1. If all bboxes are not difficult ground truth, the users can not define the data layer for this flag and not the input can be None for detection_map API.
2. Set default value for aspect_ratios in prior_box API.
3. Add more check in prior_box API.
---
paddle/fluid/operators/detection_map_op.cc | 8 +++--
paddle/fluid/operators/detection_map_op.h | 22 ++++++++-----
python/paddle/fluid/evaluator.py | 21 ++++++++-----
python/paddle/fluid/layers/detection.py | 31 ++++++++++++++-----
.../tests/unittests/test_detection_map_op.py | 13 +++++++-
5 files changed, 68 insertions(+), 27 deletions(-)
diff --git a/paddle/fluid/operators/detection_map_op.cc b/paddle/fluid/operators/detection_map_op.cc
index 0ccf701b61..716c8625d3 100644
--- a/paddle/fluid/operators/detection_map_op.cc
+++ b/paddle/fluid/operators/detection_map_op.cc
@@ -51,7 +51,8 @@ class DetectionMAPOp : public framework::OperatorWithKernel {
PADDLE_ENFORCE_EQ(label_dims.size(), 2,
"The rank of Input(Label) must be 2, "
"the shape is [N, 6].");
- PADDLE_ENFORCE_EQ(label_dims[1], 6, "The shape is of Input(Label) [N, 6].");
+ PADDLE_ENFORCE(label_dims[1] == 6 || label_dims[1] == 5,
+ "The shape of Input(Label) is [N, 6] or [N, 5].");
if (ctx->HasInput("PosCount")) {
PADDLE_ENFORCE(ctx->HasInput("TruePos"),
@@ -88,9 +89,10 @@ class DetectionMAPOpMaker : public framework::OpProtoAndCheckerMaker {
"offset is N + 1, if LoD[i + 1] - LoD[i] == 0, means there is "
"no detected data.");
AddInput("Label",
- "(LoDTensor) A 2-D LoDTensor with shape[N, 6] represents the"
+ "(LoDTensor) A 2-D LoDTensor represents the"
"Labeled ground-truth data. Each row has 6 values: "
- "[label, is_difficult, xmin, ymin, xmax, ymax], N is the total "
+ "[label, xmin, ymin, xmax, ymax, is_difficult] or 5 values: "
+ "[label, xmin, ymin, xmax, ymax], where N is the total "
"number of ground-truth data in this mini-batch. For each "
"instance, the offsets in first dimension are called LoD, "
"the number of offset is N + 1, if LoD[i + 1] - LoD[i] == 0, "
diff --git a/paddle/fluid/operators/detection_map_op.h b/paddle/fluid/operators/detection_map_op.h
index 431812e2bf..dd1ab85fd8 100644
--- a/paddle/fluid/operators/detection_map_op.h
+++ b/paddle/fluid/operators/detection_map_op.h
@@ -72,7 +72,7 @@ class DetectionMAPOpKernel : public framework::OpKernel<T> {
auto* out_false_pos = ctx.Output<framework::LoDTensor>("AccumFalsePos");
float overlap_threshold = ctx.Attr<float>("overlap_threshold");
- float evaluate_difficult = ctx.Attr<bool>("evaluate_difficult");
+ bool evaluate_difficult = ctx.Attr<bool>("evaluate_difficult");
auto ap_type = GetAPType(ctx.Attr<std::string>("ap_type"));
int class_num = ctx.Attr<int>("class_num");
@@ -175,14 +175,20 @@ class DetectionMAPOpKernel : public framework::OpKernel<T> {
for (int n = 0; n < batch_size; ++n) {
std::map<int, std::vector<Box>> boxes;
for (size_t i = label_index[n]; i < label_index[n + 1]; ++i) {
- Box box(labels(i, 2), labels(i, 3), labels(i, 4), labels(i, 5));
int label = labels(i, 0);
- auto is_difficult = labels(i, 1);
- if (std::abs(is_difficult - 0.0) < 1e-6)
- box.is_difficult = false;
- else
- box.is_difficult = true;
- boxes[label].push_back(box);
+ if (input_label.dims()[1] == 6) {
+ Box box(labels(i, 2), labels(i, 3), labels(i, 4), labels(i, 5));
+ auto is_difficult = labels(i, 1);
+ if (std::abs(is_difficult - 0.0) < 1e-6)
+ box.is_difficult = false;
+ else
+ box.is_difficult = true;
+ boxes[label].push_back(box);
+ } else {
+ PADDLE_ENFORCE_EQ(input_label.dims()[1], 5);
+ Box box(labels(i, 1), labels(i, 2), labels(i, 3), labels(i, 4));
+ boxes[label].push_back(box);
+ }
}
gt_boxes->push_back(boxes);
}
diff --git a/python/paddle/fluid/evaluator.py b/python/paddle/fluid/evaluator.py
index 1ee1d37271..7c6ad6f27d 100644
--- a/python/paddle/fluid/evaluator.py
+++ b/python/paddle/fluid/evaluator.py
@@ -273,10 +273,11 @@ class DetectionMAP(Evaluator):
[M, 6]. The layout is [label, confidence, xmin, ymin, xmax, ymax].
gt_label (Variable): The ground truth label index, which is a LoDTensor
with shape [N, 1].
- gt_difficult (Variable): Whether this ground truth is a difficult
- bounding box (bbox), which is a LoDTensor [N, 1].
gt_box (Variable): The ground truth bounding box (bbox), which is a
LoDTensor with shape [N, 6]. The layout is [xmin, ymin, xmax, ymax].
+ gt_difficult (Variable|None): Whether this ground truth is a difficult
+ bounding bbox, which can be a LoDTensor [N, 1] or not set. If None,
+ it means all the ground truth labels are not difficult bbox.
class_num (int): The class number.
background_label (int): The index of background label, the background
label will be ignored. If set to -1, then all categories will be
@@ -284,7 +285,8 @@ class DetectionMAP(Evaluator):
overlap_threshold (float): The threshold for deciding true/false
positive, 0.5 by defalut.
evaluate_difficult (bool): Whether to consider difficult ground truth
- for evaluation, True by defalut.
+ for evaluation, True by defalut. This argument does not work when
+ gt_difficult is None.
ap_version (string): The average precision calculation ways, it must be
'integral' or '11point'. Please check
https://sanchom.wordpress.com/tag/average-precision/ for details.
@@ -295,7 +297,7 @@ class DetectionMAP(Evaluator):
exe = fluid.executor(place)
map_evaluator = fluid.Evaluator.DetectionMAP(input,
- gt_label, gt_difficult, gt_box)
+ gt_label, gt_box, gt_difficult)
cur_map, accum_map = map_evaluator.get_map_var()
fetch = [cost, cur_map, accum_map]
for epoch in PASS_NUM:
@@ -313,8 +315,8 @@ class DetectionMAP(Evaluator):
input,
gt_label,
gt_box,
- gt_difficult,
- class_num,
+ gt_difficult=None,
+ class_num=None,
background_label=0,
overlap_threshold=0.5,
evaluate_difficult=True,
@@ -322,8 +324,11 @@ class DetectionMAP(Evaluator):
super(DetectionMAP, self).__init__("map_eval")
gt_label = layers.cast(x=gt_label, dtype=gt_box.dtype)
- gt_difficult = layers.cast(x=gt_difficult, dtype=gt_box.dtype)
- label = layers.concat([gt_label, gt_difficult, gt_box], axis=1)
+ if gt_difficult:
+ gt_difficult = layers.cast(x=gt_difficult, dtype=gt_box.dtype)
+ label = layers.concat([gt_label, gt_difficult, gt_box], axis=1)
+ else:
+ label = layers.concat([gt_label, gt_box], axis=1)
# calculate mean average precision (mAP) of current mini-batch
map = layers.detection_map(
diff --git a/python/paddle/fluid/layers/detection.py b/python/paddle/fluid/layers/detection.py
index b33adf55cf..3a83db12fd 100644
--- a/python/paddle/fluid/layers/detection.py
+++ b/python/paddle/fluid/layers/detection.py
@@ -569,7 +569,7 @@ def prior_box(input,
image,
min_sizes,
max_sizes=None,
- aspect_ratios=None,
+ aspect_ratios=[1.],
variance=[0.1, 0.1, 0.2, 0.2],
flip=False,
clip=False,
@@ -589,19 +589,19 @@ def prior_box(input,
input(Variable): The Input Variables, the format is NCHW.
image(Variable): The input image data of PriorBoxOp,
the layout is NCHW.
- min_sizes(list|tuple): min sizes of generated prior boxes.
+ min_sizes(list|tuple|float value): min sizes of generated prior boxes.
max_sizes(list|tuple|None): max sizes of generated prior boxes.
Default: None.
- aspect_ratios(list|tuple): the aspect ratios of generated prior
- boxes. Default: None.
+ aspect_ratios(list|tuple|float value): the aspect ratios of generated
+ prior boxes. Default: [1.].
variance(list|tuple): the variances to be encoded in prior boxes.
Default:[0.1, 0.1, 0.2, 0.2].
flip(bool): Whether to flip aspect ratios. Default:False.
clip(bool): Whether to clip out-of-boundary boxes. Default: False.
- step(list|turple): Prior boxes step across weight and height, If
+ step(list|turple): Prior boxes step across width and height, If
step[0] == 0.0/step[1] == 0.0, the prior boxes step across
- height/weight of the input will be automatically calculated.
- Default: [0.0]
+ height/weight of the input will be automatically calculated.
+ Default: [0., 0.]
offset(float): Prior boxes center offset. Default: 0.5
name(str): Name of the prior box op. Default: None.
@@ -630,6 +630,21 @@ def prior_box(input,
helper = LayerHelper("prior_box", **locals())
dtype = helper.input_dtype()
+ def _is_list_or_tuple_(data):
+ return (isinstance(data, list) or isinstance(data, tuple))
+
+ if not _is_list_or_tuple_(min_sizes):
+ min_sizes = [min_sizes]
+ if not _is_list_or_tuple_(aspect_ratios):
+ aspect_ratios = [aspect_ratios]
+ if not (_is_list_or_tuple_(steps) and len(steps) == 2):
+ raise ValueError('steps should be a list or tuple ',
+ 'with length 2, (step_width, step_height).')
+
+ min_sizes = list(map(float, min_sizes))
+ aspect_ratios = list(map(float, aspect_ratios))
+ steps = list(map(float, steps))
+
attrs = {
'min_sizes': min_sizes,
'aspect_ratios': aspect_ratios,
@@ -641,6 +656,8 @@ def prior_box(input,
'offset': offset
}
if max_sizes is not None and len(max_sizes) > 0 and max_sizes[0] > 0:
+ if not _is_list_or_tuple_(max_sizes):
+ max_sizes = [max_sizes]
attrs['max_sizes'] = max_sizes
box = helper.create_tmp_variable(dtype)
diff --git a/python/paddle/fluid/tests/unittests/test_detection_map_op.py b/python/paddle/fluid/tests/unittests/test_detection_map_op.py
index a905a854ad..f545ad155c 100644
--- a/python/paddle/fluid/tests/unittests/test_detection_map_op.py
+++ b/python/paddle/fluid/tests/unittests/test_detection_map_op.py
@@ -160,7 +160,9 @@ class TestDetectionMAPOp(OpTest):
label_count, true_pos, false_pos = get_input_pos(
self.class_pos_count, self.true_pos, self.true_pos_lod,
self.false_pos, self.false_pos_lod)
- for (label, difficult, xmin, ymin, xmax, ymax) in self.label:
+ for v in self.label:
+ label = v[0]
+ difficult = False if len(v) == 5 else v[1]
if self.evaluate_difficult:
label_count[label] += 1
elif not difficult:
@@ -245,6 +247,15 @@ class TestDetectionMAPOpSkipDiff(TestDetectionMAPOp):
[2, 0.8, 0, 1], [2, 0.1, 1, 0], [3, 0.2, 0, 1]]
+class TestDetectionMAPOpWithoutDiff(TestDetectionMAPOp):
+ def init_test_case(self):
+ super(TestDetectionMAPOpWithoutDiff, self).init_test_case()
+
+ # label xmin ymin xmax ymax
+ self.label = [[1, 0.1, 0.1, 0.3, 0.3], [1, 0.6, 0.6, 0.8, 0.8],
+ [2, 0.3, 0.3, 0.6, 0.5], [1, 0.7, 0.1, 0.9, 0.3]]
+
+
class TestDetectionMAPOp11Point(TestDetectionMAPOp):
def init_test_case(self):
super(TestDetectionMAPOp11Point, self).init_test_case()