From 3373535b213c7ad5c24121e9a4e56534bc40e05b Mon Sep 17 00:00:00 2001 From: luotao1 Date: Tue, 14 Aug 2018 16:08:36 +0800 Subject: [PATCH 1/7] fix specific cudnn include and library path --- cmake/configure.cmake | 4 ++++ cmake/external/anakin.cmake | 2 +- 2 files changed, 5 insertions(+), 1 deletion(-) diff --git a/cmake/configure.cmake b/cmake/configure.cmake index c35096e09b..ae90a529b1 100644 --- a/cmake/configure.cmake +++ b/cmake/configure.cmake @@ -104,6 +104,10 @@ if(WITH_GPU) if(${CUDNN_MAJOR_VERSION} VERSION_LESS 7) message(FATAL_ERROR "Anakin needs CUDNN >= 7.0 to compile") endif() + set(ENV{CUDNN_INCLUDE_DIR} ${CUDNN_INCLUDE_DIR}) + set(ENV{CUDNN_LIBRARY} ${CUDNN_LIBRARY}) + message(STATUS "cudnn include header is ${CUDNN_INCLUDE_DIR}/cudnn.h") + message(STATUS "cudnn library is ${CUDNN_LIBRARY}") endif() elseif(WITH_AMD_GPU) add_definitions(-DPADDLE_WITH_HIP) diff --git a/cmake/external/anakin.cmake b/cmake/external/anakin.cmake index 403873a510..5de7ca8f46 100644 --- a/cmake/external/anakin.cmake +++ b/cmake/external/anakin.cmake @@ -37,7 +37,7 @@ ExternalProject_Add( ${EXTERNAL_PROJECT_LOG_ARGS} # TODO(luotao): use PaddlePaddle/Anakin later GIT_REPOSITORY "https://github.com/luotao1/Anakin" - GIT_TAG "3957ae9263eaa0b1986758dac60a88852afb09be" + GIT_TAG "842a89ae3747ede25d8acbc29030d2eb602ced1f" PREFIX ${ANAKIN_SOURCE_DIR} UPDATE_COMMAND "" CMAKE_ARGS -DUSE_GPU_PLACE=YES From d06849305a67d6645699384ae87ec1870e5756e3 Mon Sep 17 00:00:00 2001 From: gongweibao Date: Wed, 15 Aug 2018 21:17:14 +0800 Subject: [PATCH 2/7] parameter dispather. (#12666) --- paddle/fluid/framework/threadpool.cc | 7 ++ .../distributed/variable_response.cc | 7 +- paddle/fluid/operators/listen_and_serv_op.cc | 5 +- python/paddle/fluid/__init__.py | 2 +- python/paddle/fluid/initializer.py | 1 - .../fluid/tests/unittests/CMakeLists.txt | 4 +- .../fluid/tests/unittests/test_dist_train.py | 17 +++ .../tests/unittests/test_dist_transpiler.py | 50 ++++++--- .../fluid/transpiler/distribute_transpiler.py | 100 +++++++++++++++--- 9 files changed, 162 insertions(+), 31 deletions(-) diff --git a/paddle/fluid/framework/threadpool.cc b/paddle/fluid/framework/threadpool.cc index f26f212d4d..18cdca3a65 100644 --- a/paddle/fluid/framework/threadpool.cc +++ b/paddle/fluid/framework/threadpool.cc @@ -20,6 +20,9 @@ DEFINE_int32(io_threadpool_size, 100, "number of threads used for doing IO, default 100"); +DEFINE_int32(dist_threadpool_size, 0, + "number of threads used for distributed executed."); + namespace paddle { namespace framework { @@ -35,6 +38,10 @@ void ThreadPool::Init() { if (threadpool_.get() == nullptr) { // TODO(Yancey1989): specify the max threads number int num_threads = std::thread::hardware_concurrency(); + if (FLAGS_dist_threadpool_size > 0) { + num_threads = FLAGS_dist_threadpool_size; + VLOG(1) << "set dist_threadpool_size to " << num_threads; + } PADDLE_ENFORCE_GT(num_threads, 0); threadpool_.reset(new ThreadPool(num_threads)); } diff --git a/paddle/fluid/operators/distributed/variable_response.cc b/paddle/fluid/operators/distributed/variable_response.cc index 466bce18af..8e38b3713f 100644 --- a/paddle/fluid/operators/distributed/variable_response.cc +++ b/paddle/fluid/operators/distributed/variable_response.cc @@ -190,12 +190,15 @@ bool VariableResponse::ProcSerializedField( #endif } + VLOG(7) << "ProcSerializedField:" << meta_.varname() + << ", type:" << meta_.type() << std::endl; framework::DDim dims = GetDims(meta_.dims()); if (meta_.type() == sendrecv::LOD_TENSOR) { PADDLE_ENFORCE(meta_.lod_size() >= 0, "lod info should be got first!"); if (!CopyLodTensorData(input, *dev_ctx_, dims, num_bytes)) { return false; } + return true; } @@ -206,7 +209,9 @@ bool VariableResponse::ProcSerializedField( return true; } - return true; + PADDLE_ENFORCE("not supported var types:", meta_.varname(), meta_.type()); + + return false; } }; // namespace distributed diff --git a/paddle/fluid/operators/listen_and_serv_op.cc b/paddle/fluid/operators/listen_and_serv_op.cc index b194807696..f196e18fe1 100644 --- a/paddle/fluid/operators/listen_and_serv_op.cc +++ b/paddle/fluid/operators/listen_and_serv_op.cc @@ -123,8 +123,11 @@ void ListenAndServOp::RunSyncLoop( optimize_prepared.begin(), std::shared_ptr(nullptr)); + // Trainers will get all parameters from pserver in the + // startup program, so we will wait RequestGet first + rpc_service_->SetCond(distributed::kRequestGet); + rpc_service_->WaitBarrier(distributed::kRequestGet); rpc_service_->ResetBarrierCounter(); - while (true) { rpc_service_->Profiler().OneStep(); // Get from multiple trainers, we don't care about the order in which diff --git a/python/paddle/fluid/__init__.py b/python/paddle/fluid/__init__.py index 1ae05dec8d..9aac3c7fc1 100644 --- a/python/paddle/fluid/__init__.py +++ b/python/paddle/fluid/__init__.py @@ -122,7 +122,7 @@ def __bootstrap__(): 'use_pinned_memory', 'check_nan_inf', 'benchmark', 'warpctc_dir', 'eager_delete_scope', 'use_mkldnn', 'initial_cpu_memory_in_mb', 'init_allocated_mem', 'free_idle_memory', 'paddle_num_threads', - 'cpu_deterministic' + "dist_threadpool_size", 'cpu_deterministic' ] if core.is_compiled_with_dist(): read_env_flags.append('rpc_deadline') diff --git a/python/paddle/fluid/initializer.py b/python/paddle/fluid/initializer.py index 3f740dd7c5..6dedbae7a6 100644 --- a/python/paddle/fluid/initializer.py +++ b/python/paddle/fluid/initializer.py @@ -15,7 +15,6 @@ from . import framework import numpy as np import contextlib -from .framework import convert_np_dtype_to_dtype_ from .core import VarDesc __all__ = [ diff --git a/python/paddle/fluid/tests/unittests/CMakeLists.txt b/python/paddle/fluid/tests/unittests/CMakeLists.txt index a6a911721d..e7dd85ef5c 100644 --- a/python/paddle/fluid/tests/unittests/CMakeLists.txt +++ b/python/paddle/fluid/tests/unittests/CMakeLists.txt @@ -59,8 +59,8 @@ py_test_modules(test_warpctc_op MODULES test_warpctc_op ENVS FLAGS_warpctc_dir=$ if(WITH_DISTRIBUTE) py_test_modules(test_dist_train MODULES test_dist_train SERIAL) set_tests_properties(test_listen_and_serv_op PROPERTIES TIMEOUT 20) - set_tests_properties(test_dist_mnist PROPERTIES TIMEOUT 180) - set_tests_properties(test_dist_word2vec PROPERTIES TIMEOUT 180) + set_tests_properties(test_dist_mnist PROPERTIES TIMEOUT 200) + set_tests_properties(test_dist_word2vec PROPERTIES TIMEOUT 200) endif() py_test_modules(test_parallel_executor_crf MODULES test_parallel_executor_crf SERIAL) py_test_modules(test_parallel_executor_fetch_feed MODULES test_parallel_executor_fetch_feed SERIAL) diff --git a/python/paddle/fluid/tests/unittests/test_dist_train.py b/python/paddle/fluid/tests/unittests/test_dist_train.py index aab8969a96..55aa923f5a 100644 --- a/python/paddle/fluid/tests/unittests/test_dist_train.py +++ b/python/paddle/fluid/tests/unittests/test_dist_train.py @@ -26,6 +26,12 @@ from paddle.fluid.layers.io import ListenAndServ from paddle.fluid.layers.io import Recv from paddle.fluid.layers.io import Send +from paddle.fluid import core + +RPC_OP_ROLE_ATTR_NAME = op_role_attr_name = core.op_proto_and_checker_maker.kOpRoleAttrName( +) +RPC_OP_ROLE_ATTR_VALUE = core.op_proto_and_checker_maker.OpRole.RPC + class TestSendOp(unittest.TestCase): def test_send(self): @@ -89,18 +95,29 @@ class TestSendOp(unittest.TestCase): def init_client(self, place, port): main = fluid.Program() with fluid.program_guard(main): + main.global_block().append_op( + type="fetch_barrier", + inputs={}, + outputs={}, + attrs={ + "endpoints": ["127.0.0.1:{0}".format(port)], + RPC_OP_ROLE_ATTR_NAME: RPC_OP_ROLE_ATTR_VALUE + }) + x = layers.data( shape=[32, 32], dtype='float32', name='X', append_batch_size=False) fluid.initializer.Constant(value=2.3)(x, main.global_block()) + get_var = main.global_block().create_var( name="scale_0.tmp_0", # server side var dtype="float32", persistable=False, shape=[32, 32]) fluid.initializer.Constant(value=2.3)(get_var, main.global_block()) + Send("127.0.0.1:%d" % port, [x]) o = Recv("127.0.0.1:%d" % port, [get_var]) diff --git a/python/paddle/fluid/tests/unittests/test_dist_transpiler.py b/python/paddle/fluid/tests/unittests/test_dist_transpiler.py index 55f8b3eff8..124abf4ccd 100644 --- a/python/paddle/fluid/tests/unittests/test_dist_transpiler.py +++ b/python/paddle/fluid/tests/unittests/test_dist_transpiler.py @@ -18,6 +18,7 @@ import unittest import paddle.fluid as fluid from paddle.fluid.transpiler.distribute_transpiler import delete_ops import traceback +import collections class TranspilerTest(unittest.TestCase): @@ -53,9 +54,18 @@ class TranspilerTest(unittest.TestCase): self.origin_prog = main.clone() return main - def get_trainer(self, config=None, sync_mode=True): - t = self._transpiler_instance(config, sync_mode) - return t.get_trainer_program() + def get_trainer(self, config=None): + src = fluid.default_startup_program().clone() + + t = self._transpiler_instance(config) + + trainer_main = t.get_trainer_program() + trainer_startup = fluid.default_startup_program() + + assert (src.num_blocks == 1) + assert (trainer_startup.num_blocks == src.num_blocks) + + return trainer_main, trainer_startup def get_pserver(self, ep, config=None, sync_mode=True): t = self._transpiler_instance(config, sync_mode) @@ -91,7 +101,21 @@ class TestBasicModel(TranspilerTest): pserver, startup = self.get_pserver(self.pserver1_ep) pserver2, startup2 = self.get_pserver(self.pserver2_ep) - trainer = self.get_trainer() + trainer, trainer_startup = self.get_trainer() + + # splited var blocks should be in startup program + self.assertTrue("fc_w.block0" in trainer_startup.global_block().vars) + self.assertTrue("fc_w.block1" in trainer_startup.global_block().vars) + self.assertTrue("fc_w" in trainer_startup.global_block().vars) + self.assertTrue("fc_b" in trainer_startup.global_block().vars) + self.assertTrue("fc_w@GRAD" not in trainer_startup.global_block().vars) + self.assertTrue("fc_b@GRAD" not in trainer_startup.global_block().vars) + + src = [op.type for op in trainer_startup.global_block().ops] + dst = ['fill_constant', 'fill_constant', 'uniform_random', 'recv', 'recv', \ + 'fetch_barrier', 'concat'] + + self.assertEqual(src, dst) self.assertEqual([op.type for op in trainer.global_block().ops], [ 'mul', 'elementwise_add', 'elementwise_sub', 'square', 'mean', @@ -142,7 +166,7 @@ class TestBasicModelWithLargeBlockSize(TranspilerTest): pserver, startup = self.get_pserver(self.pserver1_ep, config) pserver2, startup2 = self.get_pserver(self.pserver2_ep, config) - trainer = self.get_trainer(config) + trainer, _ = self.get_trainer(config) self.assertEqual([op.type for op in trainer.global_block().ops], [ 'mul', 'elementwise_add', 'elementwise_sub', 'square', 'mean', @@ -226,7 +250,7 @@ class TestLRDecay(TranspilerTest): def transpiler_test_impl(self): pserver, startup = self.get_pserver(self.pserver1_ep) - trainer = self.get_trainer() + trainer, _ = self.get_trainer() self.assertEqual(len(pserver.blocks), 4) lr_decay_ops = [op.type for op in pserver.blocks[1].ops] @@ -256,7 +280,7 @@ class TestLRDecayConditional(TranspilerTest): def transpiler_test_impl(self): pserver, startup = self.get_pserver(self.pserver1_ep) - trainer = self.get_trainer() + trainer, _ = self.get_trainer() serv_op = pserver.blocks[0].ops[0] sub_blocks = [] @@ -305,7 +329,7 @@ class TestL2Decay(TranspilerTest): def transpiler_test_impl(self): pserver, startup = self.get_pserver(self.pserver1_ep) - trainer = self.get_trainer() + trainer, _ = self.get_trainer() self.assertEqual(len(pserver.blocks), 3) self.assertEqual([op.type for op in pserver.blocks[1].ops], @@ -340,7 +364,7 @@ class TestL2DecayWithPiecewise(TranspilerTest): def transpiler_test_impl(self): pserver, startup = self.get_pserver(self.pserver1_ep) - trainer = self.get_trainer() + trainer, _ = self.get_trainer() self.assertEqual(len(pserver.blocks), 9) self.assertEqual([op.type for op in pserver.blocks[1].ops], [ @@ -415,7 +439,7 @@ class TestLocalLookupTable(TestDistLookupTableBase): self.assertEqual([op.type for op in pserver1.blocks[2].ops], ["sum", "adam", "scale", "scale"]) - trainer = self.get_trainer() + trainer, _ = self.get_trainer() self.assertEqual(len(trainer.blocks), 1) ops = [ 'lookup_table', 'sequence_pool', 'lookup_table', 'sequence_pool', @@ -453,7 +477,7 @@ class TestDistLookupTable(TestDistLookupTableBase): # 5 save table self.assertEqual([op.type for op in pserver1.blocks[5].ops], ["save"]) - trainer = self.get_trainer() + trainer, _ = self.get_trainer() self.assertEqual(len(trainer.blocks), 1) ops = [ 'split_ids', 'prefetch', 'merge_ids', 'sequence_pool', 'split_ids', @@ -486,7 +510,7 @@ class TestAsyncLocalLookupTable(TestDistLookupTableBase): self.assertEqual([op.type for op in pserver1.blocks[2].ops], ["adam", "scale", "scale"]) - trainer = self.get_trainer(config) + trainer, _ = self.get_trainer(config) self.assertEqual(len(trainer.blocks), 1) ops = [ 'lookup_table', 'sequence_pool', 'lookup_table', 'sequence_pool', @@ -525,7 +549,7 @@ class TestAsyncDistLookupTable(TestDistLookupTableBase): # 5 save table self.assertEqual([op.type for op in pserver1.blocks[5].ops], ["save"]) - trainer = self.get_trainer(config) + trainer, _ = self.get_trainer(config) self.assertEqual(len(trainer.blocks), 1) ops = [ 'split_ids', 'prefetch', 'merge_ids', 'sequence_pool', 'split_ids', diff --git a/python/paddle/fluid/transpiler/distribute_transpiler.py b/python/paddle/fluid/transpiler/distribute_transpiler.py index c97beea1b3..ce4709f23b 100644 --- a/python/paddle/fluid/transpiler/distribute_transpiler.py +++ b/python/paddle/fluid/transpiler/distribute_transpiler.py @@ -195,6 +195,9 @@ class DistributeTranspiler(object): if program is None: program = default_main_program() self.origin_program = program + self.origin_startup_program = default_startup_program().clone() + + self.startup_program = default_startup_program() self.trainer_num = trainers self.sync_mode = sync_mode self.trainer_id = trainer_id @@ -205,10 +208,10 @@ class DistributeTranspiler(object): ps_dispatcher = self.config.split_method(self.pserver_endpoints) self.has_distributed_lookup_table = self._has_distributed_lookup_table() - # split and create vars, then put splited vars in dicts for later use. + # step 1: split and create vars, then put splited vars in dicts for later use. self._init_splited_vars() - # step 3.1: insert send op to send gradient vars to parameter servers + # step 2: insert send op to send gradient vars to parameter servers ps_dispatcher.reset() send_vars = [] @@ -265,7 +268,7 @@ class DistributeTranspiler(object): RPC_OP_ROLE_ATTR_NAME: RPC_OP_ROLE_ATTR_VALUE }) - # step 3.2: insert recv op to receive parameters from parameter server + # step 3: insert recv op to receive parameters from parameter server recv_vars = [] for _, var in enumerate(send_vars): recv_vars.append(self.grad_param_mapping[var]) @@ -312,6 +315,8 @@ class DistributeTranspiler(object): outputs={"Out": [orig_param]}, attrs={"axis": 0}) + self._get_trainer_startup_program(recv_vars=recv_vars, eplist=eplist) + if self.has_distributed_lookup_table: self._replace_lookup_table_op_with_prefetch(program, pserver_endpoints) @@ -328,8 +333,78 @@ class DistributeTranspiler(object): # FIXME(typhoonzero): Also ops like clip_gradient, lrn_decay? delete_ops(self.origin_program.global_block(), self.optimize_ops) self.origin_program.__str__() + return self.origin_program + def _get_trainer_startup_program(self, + recv_vars, + eplist, + startup_program=None): + """ + Get transpiled trainer side startup program. + + Args: + startup_program(Program): Startup program. + + Returns: + Program: trainer side startup program. + """ + if startup_program is None: + startup_program = self.startup_program + + # FIXME(gongwb): delete not need ops. + # note that: some parameter is not trainable and those ops can't be deleted. + + for varname, splited_var in self.param_var_mapping.iteritems(): + # Get the eplist of recv vars + eps = [] + for var in splited_var: + index = [v.name for v in recv_vars].index(var.name) + eps.append(eplist[index]) + + for var in splited_var: + if startup_program.global_block().has_var(var.name): + continue + + startup_program.global_block().create_var( + name=var.name, + persistable=False, + type=var.type, + dtype=var.dtype, + shape=var.shape, + lod_level=var.lod_level) + + op = startup_program.global_block().append_op( + type="recv", + inputs={}, + outputs={"Out": splited_var}, + attrs={ + "epmap": eps, + RPC_OP_ROLE_ATTR_NAME: RPC_OP_ROLE_ATTR_VALUE + }) + + startup_program.global_block().append_op( + type="fetch_barrier", + inputs={}, + outputs={}, + attrs={ + "endpoints": self.pserver_endpoints, + RPC_OP_ROLE_ATTR_NAME: RPC_OP_ROLE_ATTR_VALUE + }) + + for varname, splited_var in self.param_var_mapping.iteritems(): + #add concat ops to merge splited parameters received from parameter servers. + if len(splited_var) <= 1: + continue + orig_param = startup_program.global_block().vars[varname] + startup_program.global_block().append_op( + type="concat", + inputs={"X": splited_var}, + outputs={"Out": [orig_param]}, + attrs={"axis": 0}) + + return startup_program + def get_pserver_program(self, endpoint): """ Get parameter server side program. @@ -576,14 +651,16 @@ class DistributeTranspiler(object): new_outputs = dict() # do not append startup op if var is not on this pserver op_on_pserver = False - for key in op.output_names: - newname, _ = _get_splited_name_and_shape(op.output(key)[0]) - if newname: - op_on_pserver = True - new_outputs[key] = created_var_map[newname] - elif op.output(key)[0] in pserver_vars: - op_on_pserver = True - new_outputs[key] = pserver_vars[op.output(key)[0]] + # TODO(gongwb): remove this line. + if op.type not in ["recv", "fetch_barrier", "concat"]: + for key in op.output_names: + newname, _ = _get_splited_name_and_shape(op.output(key)[0]) + if newname: + op_on_pserver = True + new_outputs[key] = created_var_map[newname] + elif op.output(key)[0] in pserver_vars: + op_on_pserver = True + new_outputs[key] = pserver_vars[op.output(key)[0]] if op_on_pserver: # most startup program ops have no inputs @@ -1022,7 +1099,6 @@ class DistributeTranspiler(object): var_mapping[varname] = \ [program.global_block().var(orig_var.name)] continue - var_mapping[varname] = [] orig_shape = orig_var.shape orig_dim1_flatten = 1 From c108376506faa8c51f489a4c1e658a446424453a Mon Sep 17 00:00:00 2001 From: jerrywgz Date: Wed, 15 Aug 2018 22:38:25 +0800 Subject: [PATCH 3/7] Add three modes for prelu_op (#12630) * Add three modes for prelu_op. --- paddle/fluid/API.spec | 1 + paddle/fluid/operators/prelu_op.cc | 65 +++++++-- paddle/fluid/operators/prelu_op.cu | 22 --- paddle/fluid/operators/prelu_op.h | 125 ++++++++++-------- python/paddle/fluid/layers/nn.py | 54 ++++++++ .../fluid/tests/unittests/test_layers.py | 15 +++ .../fluid/tests/unittests/test_prelu_op.py | 56 ++++++-- 7 files changed, 237 insertions(+), 101 deletions(-) delete mode 100644 paddle/fluid/operators/prelu_op.cu diff --git a/paddle/fluid/API.spec b/paddle/fluid/API.spec index c020ff45ad..ea9105d79c 100644 --- a/paddle/fluid/API.spec +++ b/paddle/fluid/API.spec @@ -159,6 +159,7 @@ paddle.fluid.layers.relu ArgSpec(args=['x'], varargs=None, keywords=None, defaul paddle.fluid.layers.log ArgSpec(args=['x'], varargs=None, keywords=None, defaults=None) paddle.fluid.layers.crop ArgSpec(args=['x', 'shape', 'offsets', 'name'], varargs=None, keywords=None, defaults=(None, None, None)) paddle.fluid.layers.rank_loss ArgSpec(args=['label', 'left', 'right', 'name'], varargs=None, keywords=None, defaults=(None,)) +paddle.fluid.layers.prelu ArgSpec(args=['x', 'mode', 'param_attr', 'name'], varargs=None, keywords=None, defaults=(None, None)) paddle.fluid.layers.flatten ArgSpec(args=['x', 'axis', 'name'], varargs=None, keywords=None, defaults=(1, None)) paddle.fluid.layers.data ArgSpec(args=['name', 'shape', 'append_batch_size', 'dtype', 'lod_level', 'type', 'stop_gradient'], varargs=None, keywords=None, defaults=(True, 'float32', 0, VarType.LOD_TENSOR, True)) paddle.fluid.layers.open_recordio_file ArgSpec(args=['filename', 'shapes', 'lod_levels', 'dtypes', 'pass_num', 'for_parallel'], varargs=None, keywords=None, defaults=(1, True)) diff --git a/paddle/fluid/operators/prelu_op.cc b/paddle/fluid/operators/prelu_op.cc index db040509bc..23d9ea88f6 100644 --- a/paddle/fluid/operators/prelu_op.cc +++ b/paddle/fluid/operators/prelu_op.cc @@ -1,11 +1,8 @@ /* 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. @@ -26,14 +23,40 @@ class PReluOp : public framework::OperatorWithKernel { : OperatorWithKernel(type, inputs, outputs, attrs) {} void InferShape(framework::InferShapeContext *ctx) const override { + std::string mode = ctx->Attrs().Get("mode"); + + auto x_dim = ctx->GetInputDim("X"); PADDLE_ENFORCE(ctx->HasInput("X"), "Input(X) should not be null"); PADDLE_ENFORCE(ctx->HasInput("Alpha"), "Input(Alpha) should not be null"); - PADDLE_ENFORCE(product(ctx->GetInputDim("Alpha")) == 1, - "Size of weight Alpha must be one."); + PADDLE_ENFORCE(ctx->HasOutput("Out"), "Output(Out) should not be null"); - ctx->SetOutputDim("Out", ctx->GetInputDim("X")); + if (mode == "all") { + PADDLE_ENFORCE(product(ctx->GetInputDim("Alpha")) == 1, + "For mode 'all', size of weight Alpha must be one."); + } else if (mode == "channel") { + PADDLE_ENFORCE(product(ctx->GetInputDim("Alpha")) == x_dim[1], + "For channel-wise mode, size of weight Alpha must be " + "equal to the number of channels, should be %d", + x_dim[1]); + } else if (mode == "element") { + PADDLE_ENFORCE(product(ctx->GetInputDim("Alpha")) == product(x_dim), + "For element-wise mode, size of weight Alpha must be " + "equal to the number of input, should be %d", + product(x_dim)); + } else { + PADDLE_THROW("Unkown mode %s", mode); + } + ctx->SetOutputDim("Out", x_dim); ctx->ShareLoD("X", /*->*/ "Out"); } + + protected: + framework::OpKernelType GetExpectedKernelType( + const framework::ExecutionContext &ctx) const override { + return framework::OpKernelType( + framework::ToDataType(ctx.Input("X")->type()), + platform::CPUPlace()); + } }; class PReluOpMaker : public framework::OpProtoAndCheckerMaker { @@ -44,9 +67,7 @@ class PReluOpMaker : public framework::OpProtoAndCheckerMaker { AddOutput("Out", "The output tensor of prelu operator."); AddComment(R"DOC( PRelu Operator. - The equation is: - $$ f(x) = \begin{cases} @@ -54,11 +75,15 @@ f(x) = x, \qquad \text{if} \ x >= 0 \end{cases} $$ - The input `X` can carry the LoD (Level of Details) information, or not. And the output shares the LoD information with input `X`. - +There are modes: + all: all elements share same weight + channel: elements in a channel share same weight + element: each element has a weight )DOC"); + AddAttr("mode", "The mode for inputs to share weights.") + .SetDefault("all"); } }; @@ -71,9 +96,23 @@ class PReluGradOp : public framework::OperatorWithKernel { PADDLE_ENFORCE(ctx->HasInput("X"), "Input(X) must not be null."); PADDLE_ENFORCE(ctx->HasInput(framework::GradVarName("Out")), "Input(Out@GRAD) should not be null"); - ctx->SetOutputDim(framework::GradVarName("X"), ctx->GetInputDim("X")); - ctx->SetOutputDim(framework::GradVarName("Alpha"), - ctx->GetInputDim("Alpha")); + auto x_grad_name = framework::GradVarName("X"); + auto alpha_grad_name = framework::GradVarName("Alpha"); + + if (ctx->HasOutput(x_grad_name)) { + ctx->SetOutputDim(x_grad_name, ctx->GetInputDim("X")); + } + if (ctx->HasOutput(alpha_grad_name)) { + ctx->SetOutputDim(alpha_grad_name, ctx->GetInputDim("Alpha")); + } + } + + protected: + framework::OpKernelType GetExpectedKernelType( + const framework::ExecutionContext &ctx) const override { + return framework::OpKernelType( + framework::ToDataType(ctx.Input("X")->type()), + platform::CPUPlace()); } }; diff --git a/paddle/fluid/operators/prelu_op.cu b/paddle/fluid/operators/prelu_op.cu deleted file mode 100644 index 37d934a290..0000000000 --- a/paddle/fluid/operators/prelu_op.cu +++ /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/prelu_op.h" - -REGISTER_OP_CUDA_KERNEL( - prelu, - paddle::operators::PReluKernel); -REGISTER_OP_CUDA_KERNEL(prelu_grad, - paddle::operators::PReluGradKernel< - paddle::platform::CUDADeviceContext, float>); diff --git a/paddle/fluid/operators/prelu_op.h b/paddle/fluid/operators/prelu_op.h index a6197d3548..f9076cbc67 100644 --- a/paddle/fluid/operators/prelu_op.h +++ b/paddle/fluid/operators/prelu_op.h @@ -1,11 +1,8 @@ /* 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. @@ -13,32 +10,16 @@ See the License for the specific language governing permissions and limitations under the License. */ #pragma once +#include #include "paddle/fluid/framework/eigen.h" #include "paddle/fluid/framework/op_registry.h" #include "paddle/fluid/platform/transform.h" - namespace paddle { namespace operators { using Tensor = framework::Tensor; using platform::Transform; -template -class PReluFunctor { - public: - explicit PReluFunctor(const T* alpha) : alpha_(alpha) {} - - HOSTDEVICE T operator()(const T& x) const { - if (x > 0) - return x; - else - return x * (*alpha_); - } - - private: - const T* alpha_; -}; - template class PReluKernel : public framework::OpKernel { public: @@ -50,53 +31,93 @@ class PReluKernel : public framework::OpKernel { const T* x_ptr = x->data(); T* o_ptr = out->mutable_data(context.GetPlace()); - auto* alpha_ptr = alpha->data(); + const T* alpha_ptr = alpha->data(); + std::string mode = context.Attr("mode"); int numel = x->numel(); - - Transform trans; - trans(context.template device_context(), x_ptr, - x_ptr + numel, o_ptr, PReluFunctor(alpha_ptr)); - } -}; - -template -class PReluGradFunctor { - public: - explicit PReluGradFunctor(const T* alpha) : alpha_(alpha) {} - - HOSTDEVICE T operator()(const T& out, const T& dout) const { - if (out > 0) - return dout; - else - return dout * (*alpha_); + auto dim = x->dims(); + int index = 0; + int i = 0; + int temp = 0; + if (mode == "channel") { + for (i = 0; i < numel; i++) { + temp = numel / (dim[0] * dim[1]); + index = (i / temp) % dim[1]; + o_ptr[i] = x_ptr[i] > 0 ? x_ptr[i] : alpha_ptr[index] * x_ptr[i]; + } + } else if (mode == "element") { + for (i = 0; i < numel; i++) { + o_ptr[i] = x_ptr[i] > 0 ? x_ptr[i] : alpha_ptr[i] * x_ptr[i]; + } + } else { + for (i = 0; i < numel; i++) { + o_ptr[i] = x_ptr[i] > 0 ? x_ptr[i] : alpha_ptr[0] * x_ptr[i]; + } + } } - - private: - const T* alpha_; }; template class PReluGradKernel : public framework::OpKernel { public: void Compute(const framework::ExecutionContext& context) const override { + auto* x = context.Input("X"); auto* dx = context.Output(framework::GradVarName("X")); auto* dout = context.Input(framework::GradVarName("Out")); - + auto* dalpha = context.Output(framework::GradVarName("Alpha")); auto* out = context.Input("Out"); auto* alpha = context.Input("Alpha"); - auto* alpha_ptr = alpha->data(); - - T* dx_ptr = dx->mutable_data(context.GetPlace()); + const T* alpha_ptr = alpha->data(); + const T* x_ptr = x->data(); const T* dout_ptr = dout->data(); const T* out_ptr = out->data(); - int numel = dx->numel(); - - Transform trans; - trans(context.template device_context(), out_ptr, - out_ptr + numel, dout_ptr, dx_ptr, PReluGradFunctor(alpha_ptr)); - - // TODO(Zhuoyuan): add dalpha upgrade when GPU kernels ready + std::string mode = context.Attr("mode"); + int numel = x->numel(); + auto dim = x->dims(); + int index = 0; + int i = 0; + int temp = 0; + if (dx) { + T* dx_ptr = dx->mutable_data(context.GetPlace()); + if (mode == "channel") { + for (i = 0; i < numel; i++) { + temp = numel / (dim[0] * dim[1]); + index = (i / temp) % dim[1]; + dx_ptr[i] = + out_ptr[i] > 0 ? dout_ptr[i] : alpha_ptr[index] * dout_ptr[i]; + } + } else if (mode == "element") { + for (i = 0; i < numel; i++) { + dx_ptr[i] = out_ptr[i] > 0 ? dout_ptr[i] : alpha_ptr[i] * dout_ptr[i]; + } + } else { + for (i = 0; i < numel; i++) { + dx_ptr[i] = out_ptr[i] > 0 ? dout_ptr[i] : alpha_ptr[0] * dout_ptr[i]; + } + } + } + + index = 0; + if (dalpha) { + T* dalpha_ptr = dalpha->mutable_data(context.GetPlace()); + if (mode == "channel") { + for (i = 0; i < numel; i++) { + temp = numel / (dim[0] * dim[1]); + index = (i / temp) % dim[1]; + dalpha_ptr[index] += out_ptr[i] > 0 ? 0 : x_ptr[i] * dout_ptr[i]; + } + } else if (mode == "element") { + for (i = 0; i < numel; i++) { + dalpha_ptr[i] += out_ptr[i] > 0 ? 0 : x_ptr[i] * dout_ptr[i]; + } + } else { + for (i = 0; i < numel; i++) { + dalpha_ptr[0] += out_ptr[i] > 0 ? 0 : x_ptr[i] * dout_ptr[i]; + } + } + } + + // TODO(Guanzhong): add GPU kernels } }; diff --git a/python/paddle/fluid/layers/nn.py b/python/paddle/fluid/layers/nn.py index c75e7eeb43..3e50fc91d9 100644 --- a/python/paddle/fluid/layers/nn.py +++ b/python/paddle/fluid/layers/nn.py @@ -112,6 +112,7 @@ __all__ = [ 'log', 'crop', 'rank_loss', + 'prelu', 'flatten', ] @@ -5364,6 +5365,59 @@ def rank_loss(label, left, right, name=None): return out +def prelu(x, mode, param_attr=None, name=None): + """ + Equation: + + y = \max(0, x) + alpha \min(0, x) + + Args: + x (Variable): The input tensor. + param_attr(ParamAttr|None): The parameter attribute for the learnable + weight (alpha). + mode (string): The mode for weight sharing + all: all elements share same weight + channel:elements in a channel share same weight + element:each element has a weight + name(str|None): A name for this layer(optional). If set None, the layer + will be named automatically. + + Returns: + Variable: The output tensor with the same shape as input. + + Examples: + + .. code-block:: python + + x = fluid.layers.data(name="x", shape=[10,10], dtype="float32") + mode = 'channel' + output = fluid.layers.prelu(x,mode) + """ + helper = LayerHelper('prelu', **locals()) + if mode not in ['all', 'channel', 'element']: + raise ValueError('mode should be one of all, channel, element.') + alpha_shape = [1] + if mode == 'channel': + alpha_shape = [1, x.shape[1], 1, 1] + elif mode == 'element': + alpha_shape = x.shape + dtype = helper.input_dtype(input_param_name='x') + alpha = helper.create_parameter( + attr=param_attr, + shape=alpha_shape, + dtype='float32', + is_bias=False, + default_initializer=Constant(1.0)) + out = helper.create_tmp_variable(dtype) + helper.append_op( + type="prelu", + inputs={"X": x, + 'Alpha': alpha}, + attrs={"mode": mode}, + outputs={"Out": out}) + return out + + def flatten(x, axis=1, name=None): """ **Flatten layer** diff --git a/python/paddle/fluid/tests/unittests/test_layers.py b/python/paddle/fluid/tests/unittests/test_layers.py index 38a138a8fa..07fd0575d3 100644 --- a/python/paddle/fluid/tests/unittests/test_layers.py +++ b/python/paddle/fluid/tests/unittests/test_layers.py @@ -21,6 +21,7 @@ import paddle.fluid.nets as nets from paddle.fluid.framework import Program, program_guard, default_main_program from paddle.fluid.param_attr import ParamAttr import decorators +from paddle.fluid.initializer import Constant class TestBook(unittest.TestCase): @@ -485,6 +486,20 @@ class TestBook(unittest.TestCase): self.assertIsNotNone(out) print(str(program)) + def test_prelu(self): + program = Program() + with program_guard(program): + input = layers.data( + name="input", shape=[5, 200, 100, 100], dtype="float32") + mode = 'channel' + out = layers.prelu( + input, + mode, + param_attr=ParamAttr(initializer=Constant(1.0)), + name='prelu') + self.assertIsNotNone(out) + print(str(program)) + if __name__ == '__main__': unittest.main() diff --git a/python/paddle/fluid/tests/unittests/test_prelu_op.py b/python/paddle/fluid/tests/unittests/test_prelu_op.py index ae19a553bb..cb7de3fc93 100644 --- a/python/paddle/fluid/tests/unittests/test_prelu_op.py +++ b/python/paddle/fluid/tests/unittests/test_prelu_op.py @@ -20,30 +20,58 @@ from op_test import OpTest class PReluTest(OpTest): def setUp(self): self.op_type = "prelu" - x_np = np.random.normal(size=(10, 10)).astype("float32") - - for pos, val in np.ndenumerate(x_np): - # Since zero point in prelu is not differentiable, avoid randomize - # zero. - while abs(val) < 1e-3: - x_np[pos] = np.random.normal() - val = x_np[pos] - - x_np_sign = np.sign(x_np) - x_np = x_np_sign * np.maximum(x_np, .005) - alpha_np = np.array([.1], dtype="float32") - self.inputs = {'X': x_np, 'Alpha': alpha_np} + self.initTestCase() + x_np = np.random.normal(size=(3, 5, 5, 10)).astype("float32") + + # Since zero point in prelu is not differentiable, avoid randomize + # zero. + x_np[np.abs(x_np) < 0.005] = 0.02 + + if self.attrs == {'mode': "all"}: + alpha_np = np.random.rand(1).astype("float32") + self.inputs = {'X': x_np, 'Alpha': alpha_np} + elif self.attrs == {'mode': "channel"}: + alpha_np = np.random.rand(1, x_np.shape[1], 1, 1).astype("float32") + self.inputs = {'X': x_np, 'Alpha': alpha_np} + else: + alpha_np = np.random.rand(*x_np.shape).astype("float32") + self.inputs = {'X': x_np, 'Alpha': alpha_np} + out_np = np.maximum(self.inputs['X'], 0.) out_np = out_np + np.minimum(self.inputs['X'], 0.) * self.inputs['Alpha'] assert out_np is not self.inputs['X'] self.outputs = {'Out': out_np} + def initTestCase(self): + self.attrs = {'mode': "channel"} + def test_check_output(self): self.check_output() def test_check_grad(self): - self.check_grad(['X'], 'Out') + self.check_grad(['X', 'Alpha'], 'Out') + + def test_check_grad_ignore_x(self): + self.check_grad(['Alpha'], 'Out', no_grad_set=set('X')) + + def test_check_grad_ignore_alpha(self): + self.check_grad(['X'], 'Out', no_grad_set=set('Alpha')) + + +class TestCase1(PReluTest): + def initTestCase(self): + self.attrs = {'mode': "all"} + + +class TestCase2(PReluTest): + def initTestCase(self): + self.attrs = {'mode': "channel"} + + +class TestCase3(PReluTest): + def initTestCase(self): + self.attrs = {'mode': "element"} if __name__ == "__main__": From bf3c34960f2a59a2616957f8fb4107b2ac7aa02b Mon Sep 17 00:00:00 2001 From: dzhwinter Date: Thu, 16 Aug 2018 11:00:55 +0800 Subject: [PATCH 4/7] "cherry picked operators changes" (#12184) * "cherry picked operators changes" * "remove duplicated code" * "add constant setter" * "add get expected kernel" * "fix ci" * "add fill constant" --- paddle/fluid/operators/activation_op.cu | 4 +- paddle/fluid/operators/activation_op.h | 12 ++-- paddle/fluid/operators/assign_value_op.cu.cc | 5 +- paddle/fluid/operators/conv_cudnn_op.cu.cc | 56 +++++++++++------- paddle/fluid/operators/cross_entropy_op.cu | 12 ++-- paddle/fluid/operators/elementwise_add_op.cu | 3 +- paddle/fluid/operators/elementwise_div_op.cu | 9 ++- paddle/fluid/operators/elementwise_mul_op.cu | 8 ++- .../fluid/operators/elementwise_op_function.h | 4 +- paddle/fluid/operators/elementwise_sub_op.cu | 8 ++- paddle/fluid/operators/fill_constant_op.cc | 53 ++++++----------- paddle/fluid/operators/fill_constant_op.cu.cc | 26 ++++++++ paddle/fluid/operators/fill_constant_op.h | 48 +++++++++++++++ paddle/fluid/operators/fill_op.cc | 2 +- paddle/fluid/operators/gaussian_random_op.cu | 2 + paddle/fluid/operators/math/cross_entropy.cu | 20 ++++++- paddle/fluid/operators/math/cross_entropy.h | 17 ++++++ .../operators/math/selected_rows_functor.cu | 13 +++- paddle/fluid/operators/math/softmax.cu | 3 + paddle/fluid/operators/mean_op.cu | 10 ++-- paddle/fluid/operators/mean_op.h | 2 +- paddle/fluid/operators/mul_op.cu.cc | 7 ++- paddle/fluid/operators/pool_cudnn_op.cu.cc | 6 +- paddle/fluid/operators/scale_op.cu | 6 +- paddle/fluid/operators/softmax_cudnn_op.cu.cc | 3 +- paddle/fluid/operators/softmax_op.cu.cc | 3 +- paddle/fluid/operators/sum_op.cu | 5 +- paddle/fluid/operators/sum_op.h | 2 +- paddle/fluid/operators/top_k_op.cu | 28 +++++++-- paddle/fluid/operators/uniform_random_op.cu | 59 ++++++++++++++++--- 30 files changed, 328 insertions(+), 108 deletions(-) create mode 100644 paddle/fluid/operators/fill_constant_op.cu.cc create mode 100644 paddle/fluid/operators/fill_constant_op.h diff --git a/paddle/fluid/operators/activation_op.cu b/paddle/fluid/operators/activation_op.cu index 27487b396c..d3a7ceed46 100644 --- a/paddle/fluid/operators/activation_op.cu +++ b/paddle/fluid/operators/activation_op.cu @@ -26,6 +26,8 @@ namespace plat = paddle::platform; act_type##_grad, ops::ActivationGradKernel>, \ ops::ActivationGradKernel>); + ops::grad_functor>, \ + ops::ActivationGradKernel>); FOR_EACH_KERNEL_FUNCTOR(REGISTER_ACTIVATION_CUDA_KERNEL); diff --git a/paddle/fluid/operators/activation_op.h b/paddle/fluid/operators/activation_op.h index 9124151926..48f3b5a5bc 100644 --- a/paddle/fluid/operators/activation_op.h +++ b/paddle/fluid/operators/activation_op.h @@ -333,8 +333,7 @@ struct SqrtGradFunctor : public BaseActivationFunctor { template void operator()(Device d, X x, Out out, dOut dout, dX dx) const { - const Out out_conj = Eigen::numext::conj(out); - dx.device(d) = static_cast(0.5) * dout / out_conj; + dx.device(d) = static_cast(0.5) * dout / out; } }; @@ -740,7 +739,7 @@ struct PowGradFunctor : public BaseActivationFunctor { typename dX> void operator()(Device d, X x, Out out, dOut dout, dX dx) const { dx.device(d) = dout * static_cast(factor) * - x.pow(static_cast(factor - static_cast(1))); + x.pow(static_cast(factor) - static_cast(1)); } }; @@ -863,10 +862,11 @@ struct SwishGradFunctor : public BaseActivationFunctor { template void operator()(Device d, X x, Out out, dOut dout, dX dx) const { + T b = static_cast(beta); auto temp1 = static_cast(1) / - (static_cast(1) + (static_cast(-beta) * x).exp()); - auto temp2 = temp1 * (static_cast(1) - (beta * out)); - dx.device(d) = dout * ((beta * out) + temp2); + (static_cast(1) + (static_cast(-b) * x).exp()); + auto temp2 = temp1 * (static_cast(1) - (b * out)); + dx.device(d) = dout * ((b * out) + temp2); } }; diff --git a/paddle/fluid/operators/assign_value_op.cu.cc b/paddle/fluid/operators/assign_value_op.cu.cc index 08bfde5dc9..0ff174b388 100644 --- a/paddle/fluid/operators/assign_value_op.cu.cc +++ b/paddle/fluid/operators/assign_value_op.cu.cc @@ -13,7 +13,10 @@ See the License for the specific language governing permissions and limitations under the License. */ #include "paddle/fluid/operators/assign_value_op.h" +#include "paddle/fluid/platform/float16.h" namespace ops = paddle::operators; +namespace plat = paddle::platform; REGISTER_OP_CUDA_KERNEL(assign_value, ops::AssignValueKernel, - ops::AssignValueKernel); + ops::AssignValueKernel, + ops::AssignValueKernel); diff --git a/paddle/fluid/operators/conv_cudnn_op.cu.cc b/paddle/fluid/operators/conv_cudnn_op.cu.cc index 22cbf680c0..59bfe8f61d 100644 --- a/paddle/fluid/operators/conv_cudnn_op.cu.cc +++ b/paddle/fluid/operators/conv_cudnn_op.cu.cc @@ -39,6 +39,27 @@ using ScalingParamType = typename platform::CudnnDataType::ScalingParamType; static constexpr size_t kCONV_CUDNN_WORKSPACE_LIMIT_BYTES = static_cast(1024) * 1024 * 1024; +template +// bool EnableFp16(const T& dummy, const DeviceContext& dev_ctx, +bool EnableFp16(const DeviceContext& dev_ctx, + cudnnConvolutionDescriptor_t cudnn_conv_desc) { +#if CUDA_VERSION >= 9000 && CUDNN_VERSION_MIN(7, 0, 1) + // Tensor core is supported since the volta GPU and + // is only enabled when input and filter data are float16 + if (dev_ctx.GetComputeCapability() >= 70 && + std::type_index(typeid(T)) == + std::type_index(typeid(platform::float16))) { + PADDLE_ENFORCE(platform::dynload::cudnnSetConvolutionMathType( + cudnn_conv_desc, CUDNN_TENSOR_OP_MATH)); + return true; + } else { + PADDLE_ENFORCE(platform::dynload::cudnnSetConvolutionMathType( + cudnn_conv_desc, CUDNN_DEFAULT_MATH)); + } +#endif + return false; +} + template class CUDNNConvOpKernel : public framework::OpKernel { public: @@ -128,27 +149,14 @@ class CUDNNConvOpKernel : public framework::OpKernel { cudnnConvolutionFwdAlgo_t algo; auto& dev_ctx = ctx.template device_context(); auto handle = dev_ctx.cudnn_handle(); - - CUDNN_ENFORCE(platform::dynload::cudnnGetConvolutionForwardAlgorithm( - handle, cudnn_input_desc, cudnn_filter_desc, cudnn_conv_desc, - cudnn_output_desc, CUDNN_CONVOLUTION_FWD_SPECIFY_WORKSPACE_LIMIT, - workspace_size_limit, &algo)); - -#if CUDA_VERSION >= 9000 && CUDNN_VERSION_MIN(7, 0, 1) - // Tensor core is supported since the volta GPU and - // is only enabled when input and filter data are float16 - if (dev_ctx.GetComputeCapability() >= 70 && - std::type_index(typeid(T)) == - std::type_index(typeid(platform::float16))) { - CUDNN_ENFORCE(platform::dynload::cudnnSetConvolutionMathType( - cudnn_conv_desc, CUDNN_TENSOR_OP_MATH)); - // Currently tensor core is only enabled using this algo + if (EnableFp16(dev_ctx, cudnn_conv_desc)) { algo = CUDNN_CONVOLUTION_FWD_ALGO_IMPLICIT_PRECOMP_GEMM; } else { - CUDNN_ENFORCE(platform::dynload::cudnnSetConvolutionMathType( - cudnn_conv_desc, CUDNN_DEFAULT_MATH)); + PADDLE_ENFORCE(platform::dynload::cudnnGetConvolutionForwardAlgorithm( + handle, cudnn_input_desc, cudnn_filter_desc, cudnn_conv_desc, + cudnn_output_desc, CUDNN_CONVOLUTION_FWD_SPECIFY_WORKSPACE_LIMIT, + workspace_size_limit, &algo)); } -#endif // get workspace size able to allocate CUDNN_ENFORCE(platform::dynload::cudnnGetConvolutionForwardWorkspaceSize( @@ -288,6 +296,9 @@ class CUDNNConvGradOpKernel : public framework::OpKernel { } else { data_algo = CUDNN_CONVOLUTION_BWD_DATA_ALGO_1; } + if (EnableFp16(dev_ctx, cudnn_conv_desc)) { + data_algo = CUDNN_CONVOLUTION_BWD_DATA_ALGO_1; + } CUDNN_ENFORCE( platform::dynload::cudnnGetConvolutionBackwardDataWorkspaceSize( @@ -307,6 +318,9 @@ class CUDNNConvGradOpKernel : public framework::OpKernel { } else { filter_algo = CUDNN_CONVOLUTION_BWD_FILTER_ALGO_1; } + if (EnableFp16(dev_ctx, cudnn_conv_desc)) { + filter_algo = CUDNN_CONVOLUTION_BWD_FILTER_ALGO_1; + } CUDNN_ENFORCE( platform::dynload::cudnnGetConvolutionBackwardFilterWorkspaceSize( @@ -362,7 +376,8 @@ REGISTER_OP_KERNEL(conv2d, CUDNN, plat::CUDAPlace, paddle::operators::CUDNNConvOpKernel); REGISTER_OP_KERNEL(conv2d_grad, CUDNN, plat::CUDAPlace, paddle::operators::CUDNNConvGradOpKernel, - paddle::operators::CUDNNConvGradOpKernel); + paddle::operators::CUDNNConvGradOpKernel, + paddle::operators::CUDNNConvGradOpKernel); REGISTER_OP_KERNEL(conv3d, CUDNN, plat::CUDAPlace, paddle::operators::CUDNNConvOpKernel, @@ -370,4 +385,5 @@ REGISTER_OP_KERNEL(conv3d, CUDNN, plat::CUDAPlace, paddle::operators::CUDNNConvOpKernel); REGISTER_OP_KERNEL(conv3d_grad, CUDNN, plat::CUDAPlace, paddle::operators::CUDNNConvGradOpKernel, - paddle::operators::CUDNNConvGradOpKernel); + paddle::operators::CUDNNConvGradOpKernel, + paddle::operators::CUDNNConvGradOpKernel) diff --git a/paddle/fluid/operators/cross_entropy_op.cu b/paddle/fluid/operators/cross_entropy_op.cu index 30dbd5bd3d..65fd3a5dbc 100644 --- a/paddle/fluid/operators/cross_entropy_op.cu +++ b/paddle/fluid/operators/cross_entropy_op.cu @@ -13,12 +13,16 @@ See the License for the specific language governing permissions and limitations under the License. */ #include "paddle/fluid/operators/cross_entropy_op.h" +#include "paddle/fluid/platform/float16.h" namespace ops = paddle::operators; +namespace plat = paddle::platform; using CUDACtx = paddle::platform::CUDADeviceContext; REGISTER_OP_CUDA_KERNEL(cross_entropy, ops::CrossEntropyOpKernel, - ops::CrossEntropyOpKernel); -REGISTER_OP_CUDA_KERNEL(cross_entropy_grad, - ops::CrossEntropyGradientOpKernel, - ops::CrossEntropyGradientOpKernel); + ops::CrossEntropyOpKernel, + ops::CrossEntropyOpKernel); +REGISTER_OP_CUDA_KERNEL( + cross_entropy_grad, ops::CrossEntropyGradientOpKernel, + ops::CrossEntropyGradientOpKernel, + ops::CrossEntropyGradientOpKernel); diff --git a/paddle/fluid/operators/elementwise_add_op.cu b/paddle/fluid/operators/elementwise_add_op.cu index dfff518f17..f9f5c66d34 100644 --- a/paddle/fluid/operators/elementwise_add_op.cu +++ b/paddle/fluid/operators/elementwise_add_op.cu @@ -30,4 +30,5 @@ REGISTER_OP_CUDA_KERNEL( ops::ElementwiseAddGradKernel, ops::ElementwiseAddGradKernel, ops::ElementwiseAddGradKernel, - ops::ElementwiseAddGradKernel); + ops::ElementwiseAddGradKernel, + ops::ElementwiseAddGradKernel); diff --git a/paddle/fluid/operators/elementwise_div_op.cu b/paddle/fluid/operators/elementwise_div_op.cu index 588d1f7420..4cc7ba0f43 100644 --- a/paddle/fluid/operators/elementwise_div_op.cu +++ b/paddle/fluid/operators/elementwise_div_op.cu @@ -14,19 +14,24 @@ limitations under the License. */ #define EIGEN_USE_GPU #include "paddle/fluid/operators/elementwise_div_op.h" +#include "paddle/fluid/platform/float16.h" namespace ops = paddle::operators; +namespace plat = paddle::platform; REGISTER_OP_CUDA_KERNEL( elementwise_div, ops::ElementwiseDivKernel, ops::ElementwiseDivKernel, ops::ElementwiseDivKernel, - ops::ElementwiseDivKernel); + ops::ElementwiseDivKernel, + ops::ElementwiseDivKernel); REGISTER_OP_CUDA_KERNEL( elementwise_div_grad, ops::ElementwiseDivGradKernel, ops::ElementwiseDivGradKernel, ops::ElementwiseDivGradKernel, + ops::ElementwiseDivGradKernel, ops::ElementwiseDivGradKernel); + plat::float16>); diff --git a/paddle/fluid/operators/elementwise_mul_op.cu b/paddle/fluid/operators/elementwise_mul_op.cu index 2fb1b4bee6..350d43168d 100644 --- a/paddle/fluid/operators/elementwise_mul_op.cu +++ b/paddle/fluid/operators/elementwise_mul_op.cu @@ -14,19 +14,25 @@ limitations under the License. */ #define EIGEN_USE_GPU #include "paddle/fluid/operators/elementwise_mul_op.h" +#include "paddle/fluid/platform/float16.h" namespace ops = paddle::operators; +namespace plat = paddle::platform; REGISTER_OP_CUDA_KERNEL( elementwise_mul, ops::ElementwiseMulKernel, ops::ElementwiseMulKernel, ops::ElementwiseMulKernel, - ops::ElementwiseMulKernel); + ops::ElementwiseMulKernel, + ops::ElementwiseMulKernel); REGISTER_OP_CUDA_KERNEL( elementwise_mul_grad, ops::ElementwiseMulGradKernel, ops::ElementwiseMulGradKernel, ops::ElementwiseMulGradKernel, + ops::ElementwiseMulGradKernel, ops::ElementwiseMulGradKernel); diff --git a/paddle/fluid/operators/elementwise_op_function.h b/paddle/fluid/operators/elementwise_op_function.h index bc3e95e904..7223a972d2 100644 --- a/paddle/fluid/operators/elementwise_op_function.h +++ b/paddle/fluid/operators/elementwise_op_function.h @@ -350,7 +350,7 @@ static __global__ void ElemwiseGradBroadcast1CUDAKernel( int j = blockIdx.x; int i = threadIdx.x; int tid = threadIdx.x; - T val = 0; + T val(0); do { int x_offset = i * w + j; @@ -418,7 +418,7 @@ static __global__ void ElemwiseGradBroadcast2CUDAKernel( int tid = threadIdx.x; int j = blockIdx.x; - T val = 0; + T val(0); int ttid = tid; while (true) { diff --git a/paddle/fluid/operators/elementwise_sub_op.cu b/paddle/fluid/operators/elementwise_sub_op.cu index 8709f686f9..ff3f6f8a2c 100644 --- a/paddle/fluid/operators/elementwise_sub_op.cu +++ b/paddle/fluid/operators/elementwise_sub_op.cu @@ -14,19 +14,25 @@ limitations under the License. */ #define EIGEN_USE_GPU #include "paddle/fluid/operators/elementwise_sub_op.h" +#include "paddle/fluid/platform/float16.h" namespace ops = paddle::operators; +namespace plat = paddle::platform; REGISTER_OP_CUDA_KERNEL( elementwise_sub, ops::ElementwiseSubKernel, ops::ElementwiseSubKernel, ops::ElementwiseSubKernel, - ops::ElementwiseSubKernel); + ops::ElementwiseSubKernel, + ops::ElementwiseSubKernel); REGISTER_OP_CUDA_KERNEL( elementwise_sub_grad, ops::ElementwiseSubGradKernel, ops::ElementwiseSubGradKernel, ops::ElementwiseSubGradKernel, + ops::ElementwiseSubGradKernel, ops::ElementwiseSubGradKernel); diff --git a/paddle/fluid/operators/fill_constant_op.cc b/paddle/fluid/operators/fill_constant_op.cc index 130f18dde4..862249269e 100644 --- a/paddle/fluid/operators/fill_constant_op.cc +++ b/paddle/fluid/operators/fill_constant_op.cc @@ -12,48 +12,28 @@ 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" -#include "paddle/fluid/framework/op_registry.h" -#include "paddle/fluid/operators/math/math_function.h" -#include "paddle/fluid/platform/device_context.h" +#include "paddle/fluid/operators/fill_constant_op.h" +#include "paddle/fluid/platform/float16.h" namespace paddle { namespace operators { -class FillConstantInferShape : public framework::InferShapeBase { +class FillConstantOp : public framework::OperatorWithKernel { public: - void operator()(framework::InferShapeContext *ctx) const override { + using framework::OperatorWithKernel::OperatorWithKernel; + + void InferShape(framework::InferShapeContext* ctx) const override { PADDLE_ENFORCE(ctx->HasOutput("Out"), "Output(Out) of FillConstantOp should not be null."); - auto &shape = ctx->Attrs().Get>("shape"); + auto& shape = ctx->Attrs().Get>("shape"); ctx->SetOutputDim("Out", framework::make_ddim(shape)); } -}; - -class FillConstantOp : public framework::OperatorBase { - public: - using framework::OperatorBase::OperatorBase; - - private: - void RunImpl(const framework::Scope &scope, - const platform::Place &dev_place) const override { - auto data_type = - static_cast(Attr("dtype")); - auto value = Attr("value"); - auto force_cpu = Attr("force_cpu"); - auto &out = - *scope.FindVar(Output("Out"))->GetMutable(); - out.Resize(framework::make_ddim(Attr>("shape"))); - if (force_cpu) { - auto cpu = platform::CPUPlace(); - out.mutable_data(cpu, framework::ToTypeIndex(data_type)); - } else { - out.mutable_data(dev_place, framework::ToTypeIndex(data_type)); - } - platform::DeviceContextPool &pool = platform::DeviceContextPool::Instance(); - auto &dev_ctx = *pool.Get(dev_place); - math::set_constant(dev_ctx, &out, value); + framework::OpKernelType GetExpectedKernelType( + const framework::ExecutionContext& ctx) const override { + return framework::OpKernelType( + static_cast(ctx.Attr("dtype")), + ctx.device_context()); } }; @@ -87,6 +67,11 @@ Fill up a variable with specified constant value. } // namespace paddle namespace ops = paddle::operators; -REGISTER_OPERATOR(fill_constant, ops::FillConstantOp, - ops::FillConstantInferShape, ops::FillConstantOpMaker, +REGISTER_OPERATOR(fill_constant, ops::FillConstantOp, ops::FillConstantOpMaker, paddle::framework::EmptyGradOpMaker); +REGISTER_OP_CPU_KERNEL( + fill_constant, + ops::FillConstantOpKernel, + ops::FillConstantOpKernel, + ops::FillConstantOpKernel, + ops::FillConstantOpKernel) diff --git a/paddle/fluid/operators/fill_constant_op.cu.cc b/paddle/fluid/operators/fill_constant_op.cu.cc new file mode 100644 index 0000000000..51ccaefa43 --- /dev/null +++ b/paddle/fluid/operators/fill_constant_op.cu.cc @@ -0,0 +1,26 @@ +// 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/operators/fill_constant_op.h" +#include "paddle/fluid/platform/float16.h" + +namespace ops = paddle::operators; +REGISTER_OP_CUDA_KERNEL( + fill_constant, + ops::FillConstantOpKernel, + ops::FillConstantOpKernel, + ops::FillConstantOpKernel, + ops::FillConstantOpKernel, + ops::FillConstantOpKernel) diff --git a/paddle/fluid/operators/fill_constant_op.h b/paddle/fluid/operators/fill_constant_op.h new file mode 100644 index 0000000000..b2a2a7b2fa --- /dev/null +++ b/paddle/fluid/operators/fill_constant_op.h @@ -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. + +#pragma once +#include + +#include "paddle/fluid/framework/data_type.h" +#include "paddle/fluid/framework/op_registry.h" +#include "paddle/fluid/operators/math/math_function.h" + +namespace paddle { +namespace operators { + +template +class FillConstantOpKernel : public framework::OpKernel { + public: + void Compute(const framework::ExecutionContext& ctx) const override { + auto data_type = + static_cast(ctx.Attr("dtype")); + auto value = ctx.Attr("value"); + auto force_cpu = ctx.Attr("force_cpu"); + auto* out = ctx.Output("Out"); + out->Resize(framework::make_ddim(ctx.Attr>("shape"))); + if (force_cpu) { + auto cpu = platform::CPUPlace(); + out->mutable_data(cpu, framework::ToTypeIndex(data_type)); + } else { + out->mutable_data(ctx.GetPlace(), framework::ToTypeIndex(data_type)); + } + + math::set_constant(ctx.template device_context(), out, + value); + } +}; + +} // namespace operators +} // namespace paddle diff --git a/paddle/fluid/operators/fill_op.cc b/paddle/fluid/operators/fill_op.cc index 925dc19061..352a17c927 100644 --- a/paddle/fluid/operators/fill_op.cc +++ b/paddle/fluid/operators/fill_op.cc @@ -16,6 +16,7 @@ limitations under the License. */ #include "paddle/fluid/framework/op_registry.h" #include "paddle/fluid/operators/detail/safe_ref.h" #include "paddle/fluid/platform/device_context.h" +#include "paddle/fluid/platform/float16.h" namespace paddle { namespace operators { @@ -69,7 +70,6 @@ class FillOp : public framework::OperatorBase { framework::VisitDataType( dtype, FillOpVisitor(&tensor, Attr>("value"))); - if (!force_cpu && platform::is_gpu_place(place)) { // Copy tensor to out platform::DeviceContextPool &pool = diff --git a/paddle/fluid/operators/gaussian_random_op.cu b/paddle/fluid/operators/gaussian_random_op.cu index 7784856417..b490723795 100644 --- a/paddle/fluid/operators/gaussian_random_op.cu +++ b/paddle/fluid/operators/gaussian_random_op.cu @@ -15,6 +15,7 @@ limitations under the License. */ #include #include "paddle/fluid/framework/op_registry.h" #include "paddle/fluid/framework/operator.h" +#include "paddle/fluid/platform/float16.h" namespace paddle { namespace operators { @@ -60,6 +61,7 @@ class GPUGaussianRandomKernel : public framework::OpKernel { } // namespace operators } // namespace paddle +namespace plat = paddle::platform; REGISTER_OP_CUDA_KERNEL(gaussian_random, paddle::operators::GPUGaussianRandomKernel, paddle::operators::GPUGaussianRandomKernel); diff --git a/paddle/fluid/operators/math/cross_entropy.cu b/paddle/fluid/operators/math/cross_entropy.cu index 0de58d5fdd..58b85abf82 100644 --- a/paddle/fluid/operators/math/cross_entropy.cu +++ b/paddle/fluid/operators/math/cross_entropy.cu @@ -15,11 +15,25 @@ limitations under the License. */ #include "paddle/fluid/operators/math/cross_entropy.h" #include "paddle/fluid/platform/cuda_device_function.h" #include "paddle/fluid/platform/cuda_primitives.h" +#include "paddle/fluid/platform/float16.h" namespace paddle { namespace operators { namespace math { +template +HOSTDEVICE T log(const T& val) { + return std::log(val); +} + +template <> +HOSTDEVICE platform::float16 log(const platform::float16& val) { + // strage bug, hlog is not exists. + return static_cast(0); + // half tmp = static_cast(val); + // return static_cast(hlog(tmp)); +} + namespace { template __global__ void CrossEntropyKernel(T* Y, const T* X, const int64_t* label, @@ -35,12 +49,12 @@ template __global__ void SoftCrossEntropyKernel(T* Y, const T* X, const T* label, const int class_num) { int tid = threadIdx.x; - T val = 0; + T val(0); int idx = blockIdx.x * class_num + tid; int end = blockIdx.x * class_num + class_num; for (; idx < end; idx += blockDim.x) { - val += math::TolerableValue()(std::log(X[idx])) * label[idx]; + val += math::TolerableValue()(log(X[idx])) * label[idx]; } val = paddle::platform::reduceSum(val, tid, blockDim.x); @@ -84,6 +98,8 @@ class CrossEntropyFunctor { template class CrossEntropyFunctor; template class CrossEntropyFunctor; +template class CrossEntropyFunctor; } // namespace math } // namespace operators } // namespace paddle diff --git a/paddle/fluid/operators/math/cross_entropy.h b/paddle/fluid/operators/math/cross_entropy.h index adc5b3fe47..2e4e4781c2 100644 --- a/paddle/fluid/operators/math/cross_entropy.h +++ b/paddle/fluid/operators/math/cross_entropy.h @@ -13,8 +13,10 @@ See the License for the specific language governing permissions and limitations under the License. */ #pragma once +#include #include "paddle/fluid/framework/eigen.h" #include "paddle/fluid/framework/tensor.h" +#include "paddle/fluid/platform/float16.h" #include "paddle/fluid/platform/hostdevice.h" namespace paddle { @@ -33,6 +35,21 @@ struct TolerableValue { } }; +// float16 value clip behave different. +using paddle::platform::float16; +using paddle::platform::isfinite; +template <> +struct TolerableValue { + HOSTDEVICE float16 operator()(const float16& x) const { + if (isfinite(x)) + return x; + else if (x > static_cast(0)) + return std::numeric_limits::max(); + else + return std::numeric_limits::min(); + } +}; + template class CrossEntropyFunctor { public: diff --git a/paddle/fluid/operators/math/selected_rows_functor.cu b/paddle/fluid/operators/math/selected_rows_functor.cu index a92762c7fe..00dbfc11a2 100644 --- a/paddle/fluid/operators/math/selected_rows_functor.cu +++ b/paddle/fluid/operators/math/selected_rows_functor.cu @@ -18,6 +18,7 @@ limitations under the License. */ #include "paddle/fluid/operators/math/math_function.h" #include "paddle/fluid/operators/math/selected_rows_functor.h" #include "paddle/fluid/platform/cuda_primitives.h" +#include "paddle/fluid/platform/float16.h" namespace paddle { namespace operators { @@ -76,6 +77,7 @@ struct SelectedRowsAdd { template struct SelectedRowsAdd; template struct SelectedRowsAdd; +template struct SelectedRowsAdd; namespace { template @@ -120,7 +122,7 @@ struct SelectedRowsAddTensor { auto* out_data = output->data(); SetConstant functor; - functor(context, output, 0.0); + functor(context, output, static_cast(0)); const int block_size = 256; dim3 threads(block_size, 1); @@ -138,6 +140,8 @@ struct SelectedRowsAddTensor { template struct SelectedRowsAddTensor; template struct SelectedRowsAddTensor; +template struct SelectedRowsAddTensor; template struct SelectedRowsAddTo { @@ -177,6 +181,8 @@ template struct SelectedRowsAddTo; template struct SelectedRowsAddTo; template struct SelectedRowsAddTo; template struct SelectedRowsAddTo; +template struct SelectedRowsAddTo; namespace { template @@ -229,6 +235,8 @@ template struct SelectedRowsAddToTensor; template struct SelectedRowsAddToTensor; template struct SelectedRowsAddToTensor; template struct SelectedRowsAddToTensor; +template struct SelectedRowsAddToTensor; namespace scatter { @@ -276,7 +284,7 @@ struct MergeAdd { context.GetPlace()); math::SetConstant constant_functor; - constant_functor(context, out.mutable_value(), 0.0); + constant_functor(context, out.mutable_value(), static_cast(0)); auto* out_data = out.mutable_value()->data(); auto* input_data = input.value().data(); @@ -300,6 +308,7 @@ template struct MergeAdd; template struct MergeAdd; template struct MergeAdd; template struct MergeAdd; +template struct MergeAdd; template __global__ void UpdateToTensorKernel(const T* selected_rows, diff --git a/paddle/fluid/operators/math/softmax.cu b/paddle/fluid/operators/math/softmax.cu index 3effe77625..785c4baecb 100644 --- a/paddle/fluid/operators/math/softmax.cu +++ b/paddle/fluid/operators/math/softmax.cu @@ -94,12 +94,15 @@ void SoftmaxGradCUDNNFunctor::operator()( template class SoftmaxCUDNNFunctor; template class SoftmaxCUDNNFunctor; template class SoftmaxCUDNNFunctor; +template class SoftmaxGradCUDNNFunctor; template class SoftmaxGradCUDNNFunctor; template class SoftmaxGradCUDNNFunctor; template class SoftmaxFunctor; template class SoftmaxFunctor; template class SoftmaxFunctor; +template class SoftmaxGradFunctor; template class SoftmaxGradFunctor; template class SoftmaxGradFunctor; diff --git a/paddle/fluid/operators/mean_op.cu b/paddle/fluid/operators/mean_op.cu index 91e0ab28ef..07aa23754f 100644 --- a/paddle/fluid/operators/mean_op.cu +++ b/paddle/fluid/operators/mean_op.cu @@ -12,14 +12,16 @@ 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. */ -#define EIGEN_USE_GPU - #include "paddle/fluid/operators/mean_op.h" +#include "paddle/fluid/platform/float16.h" namespace ops = paddle::operators; +namespace plat = paddle::platform; REGISTER_OP_CUDA_KERNEL( mean, ops::MeanKernel, - ops::MeanKernel); + ops::MeanKernel, + ops::MeanKernel); REGISTER_OP_CUDA_KERNEL( mean_grad, ops::MeanGradKernel, - ops::MeanGradKernel); + ops::MeanGradKernel, + ops::MeanGradKernel); diff --git a/paddle/fluid/operators/mean_op.h b/paddle/fluid/operators/mean_op.h index 362e9f9ae8..a41d50ae0b 100644 --- a/paddle/fluid/operators/mean_op.h +++ b/paddle/fluid/operators/mean_op.h @@ -55,7 +55,7 @@ class MeanGradKernel : public framework::OpKernel { IG->mutable_data(context.GetPlace()); T ig_size = static_cast(IG->numel()); - Eigen::DSizes bcast(ig_size); + Eigen::DSizes bcast(static_cast(ig_size)); EigenVector::Flatten(*IG).device( *context.template device_context().eigen_device()) = diff --git a/paddle/fluid/operators/mul_op.cu.cc b/paddle/fluid/operators/mul_op.cu.cc index 81f3e42bf4..6c5a83c6a5 100644 --- a/paddle/fluid/operators/mul_op.cu.cc +++ b/paddle/fluid/operators/mul_op.cu.cc @@ -20,6 +20,7 @@ namespace plat = paddle::platform; REGISTER_OP_CUDA_KERNEL(mul, ops::MulKernel, ops::MulKernel, ops::MulKernel); -REGISTER_OP_CUDA_KERNEL(mul_grad, - ops::MulGradKernel, - ops::MulGradKernel); +REGISTER_OP_CUDA_KERNEL( + mul_grad, ops::MulGradKernel, + ops::MulGradKernel, + ops::MulGradKernel); diff --git a/paddle/fluid/operators/pool_cudnn_op.cu.cc b/paddle/fluid/operators/pool_cudnn_op.cu.cc index 31f083565f..9fdbee818a 100644 --- a/paddle/fluid/operators/pool_cudnn_op.cu.cc +++ b/paddle/fluid/operators/pool_cudnn_op.cu.cc @@ -174,7 +174,8 @@ REGISTER_OP_KERNEL(pool2d, CUDNN, plat::CUDAPlace, ops::PoolCUDNNOpKernel); REGISTER_OP_KERNEL(pool2d_grad, CUDNN, plat::CUDAPlace, ops::PoolCUDNNGradOpKernel, - ops::PoolCUDNNGradOpKernel); + ops::PoolCUDNNGradOpKernel, + ops::PoolCUDNNGradOpKernel); REGISTER_OP_KERNEL(pool3d, CUDNN, plat::CUDAPlace, ops::PoolCUDNNOpKernel, @@ -182,4 +183,5 @@ REGISTER_OP_KERNEL(pool3d, CUDNN, plat::CUDAPlace, ops::PoolCUDNNOpKernel); REGISTER_OP_KERNEL(pool3d_grad, CUDNN, plat::CUDAPlace, ops::PoolCUDNNGradOpKernel, - ops::PoolCUDNNGradOpKernel); + ops::PoolCUDNNGradOpKernel, + ops::PoolCUDNNGradOpKernel); diff --git a/paddle/fluid/operators/scale_op.cu b/paddle/fluid/operators/scale_op.cu index 04c802da12..d266867046 100644 --- a/paddle/fluid/operators/scale_op.cu +++ b/paddle/fluid/operators/scale_op.cu @@ -13,11 +13,15 @@ See the License for the specific language governing permissions and limitations under the License. */ #include "paddle/fluid/operators/scale_op.h" +#include "paddle/fluid/platform/float16.h" +namespace plat = paddle::platform; REGISTER_OP_CUDA_KERNEL( scale, paddle::operators::ScaleKernel, paddle::operators::ScaleKernel, paddle::operators::ScaleKernel, paddle::operators::ScaleKernel); + int64_t>, + paddle::operators::ScaleKernel); diff --git a/paddle/fluid/operators/softmax_cudnn_op.cu.cc b/paddle/fluid/operators/softmax_cudnn_op.cu.cc index 2bdb23e999..c2d45c3d2e 100644 --- a/paddle/fluid/operators/softmax_cudnn_op.cu.cc +++ b/paddle/fluid/operators/softmax_cudnn_op.cu.cc @@ -78,4 +78,5 @@ REGISTER_OP_KERNEL(softmax, CUDNN, plat::CUDAPlace, ops::SoftmaxCUDNNKernel, ops::SoftmaxCUDNNKernel); REGISTER_OP_KERNEL(softmax_grad, CUDNN, plat::CUDAPlace, - ops::SoftmaxGradCUDNNKernel); + ops::SoftmaxGradCUDNNKernel, + ops::SoftmaxGradCUDNNKernel); diff --git a/paddle/fluid/operators/softmax_op.cu.cc b/paddle/fluid/operators/softmax_op.cu.cc index 5fb4f011d9..19359b7eef 100644 --- a/paddle/fluid/operators/softmax_op.cu.cc +++ b/paddle/fluid/operators/softmax_op.cu.cc @@ -23,4 +23,5 @@ REGISTER_OP_CUDA_KERNEL( ops::SoftmaxKernel); REGISTER_OP_CUDA_KERNEL( softmax_grad, ops::SoftmaxGradKernel, - ops::SoftmaxGradKernel); + ops::SoftmaxGradKernel, + ops::SoftmaxGradKernel); diff --git a/paddle/fluid/operators/sum_op.cu b/paddle/fluid/operators/sum_op.cu index 89bcd1bbc8..db4c2d6c11 100644 --- a/paddle/fluid/operators/sum_op.cu +++ b/paddle/fluid/operators/sum_op.cu @@ -11,10 +11,13 @@ limitations under the License. */ #define EIGEN_USE_GPU #include "paddle/fluid/operators/sum_op.h" +#include "paddle/fluid/platform/float16.h" namespace ops = paddle::operators; +namespace plat = paddle::platform; REGISTER_OP_CUDA_KERNEL( sum, ops::SumKernel, ops::SumKernel, ops::SumKernel, - ops::SumKernel); + ops::SumKernel, + ops::SumKernel); diff --git a/paddle/fluid/operators/sum_op.h b/paddle/fluid/operators/sum_op.h index 49a4afb3a8..dda6772796 100644 --- a/paddle/fluid/operators/sum_op.h +++ b/paddle/fluid/operators/sum_op.h @@ -46,7 +46,7 @@ class SumKernel : public framework::OpKernel { if (!in_place) { math::SetConstant constant_functor; constant_functor(context.template device_context(), out, - 0.0); + static_cast(0)); } math::SelectedRowsAddToTensor functor; diff --git a/paddle/fluid/operators/top_k_op.cu b/paddle/fluid/operators/top_k_op.cu index 9da8551eb2..5fc0784f66 100644 --- a/paddle/fluid/operators/top_k_op.cu +++ b/paddle/fluid/operators/top_k_op.cu @@ -11,16 +11,19 @@ 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 #include "paddle/fluid/framework/op_registry.h" #include "paddle/fluid/operators/top_k_op.h" #include "paddle/fluid/platform/assert.h" #include "paddle/fluid/platform/cuda_device_function.h" +#include "paddle/fluid/platform/float16.h" namespace paddle { namespace operators { using Tensor = framework::Tensor; +using paddle::platform::float16; template struct Pair { @@ -32,6 +35,11 @@ struct Pair { id = id; } + __device__ __forceinline__ void clear() { + v = -INFINITY; + id = -1; + } + __device__ __forceinline__ void operator=(const Pair& in) { v = in.v; id = in.id; @@ -53,6 +61,12 @@ struct Pair { int64_t id; }; +template <> +__device__ __forceinline__ void Pair::clear() { + v = platform::raw_uint16_to_float16(0x400); + id = -1; +} + template __device__ __forceinline__ void AddTo(Pair topk[], const Pair& p, int beam_size) { @@ -150,7 +164,7 @@ __device__ __forceinline__ void ThreadGetTopK(Pair topk[], int* beam, if (k < MaxLength - (*beam)) { topk[k] = topk[k + *beam]; } else { - topk[k].set(-INFINITY, -1); + topk[k].clear(); } } if (!(*is_empty)) { @@ -160,7 +174,7 @@ __device__ __forceinline__ void ThreadGetTopK(Pair topk[], int* beam, } *max = topk[MaxLength - 1]; - if ((*max).v == -1) *is_empty = true; + if ((*max).v == static_cast(-1)) *is_empty = true; *beam = 0; } } @@ -181,7 +195,7 @@ __device__ __forceinline__ void ThreadGetTopK(Pair topk[], int* beam, if (k < MaxLength - *beam) { topk[k] = topk[k + *beam]; } else { - topk[k].set(-INFINITY, -1); + topk[k].set(std::numeric_limits::min(), -1); } } if (!(*is_empty)) { @@ -273,7 +287,7 @@ __global__ void KeMatrixTopK(T* output, int output_stride, int64_t* indices, bool firststep = true; for (int k = 0; k < MaxLength; k++) { - topk[k].set(-INFINITY, -1); + topk[k].clear(); } while (k) { ThreadGetTopK(topk, &beam, k, @@ -325,5 +339,7 @@ class TopkOpCUDAKernel : public framework::OpKernel { } // namespace operators } // namespace paddle -REGISTER_OP_CUDA_KERNEL(top_k, paddle::operators::TopkOpCUDAKernel, - paddle::operators::TopkOpCUDAKernel); +REGISTER_OP_CUDA_KERNEL( + top_k, paddle::operators::TopkOpCUDAKernel, + paddle::operators::TopkOpCUDAKernel, + paddle::operators::TopkOpCUDAKernel); diff --git a/paddle/fluid/operators/uniform_random_op.cu b/paddle/fluid/operators/uniform_random_op.cu index e1c7323a30..2b8039a0c1 100644 --- a/paddle/fluid/operators/uniform_random_op.cu +++ b/paddle/fluid/operators/uniform_random_op.cu @@ -11,10 +11,14 @@ 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 #include #include +#include "paddle/fluid/framework/eigen.h" #include "paddle/fluid/framework/op_registry.h" #include "paddle/fluid/framework/operator.h" +#include "paddle/fluid/platform/float16.h" +#include "paddle/fluid/platform/transform.h" namespace paddle { namespace operators { @@ -36,6 +40,11 @@ struct UniformGenerator { } }; +template +struct CastFunctor { + HOSTDEVICE V operator()(const T& a) { return static_cast(a); } +}; + // It seems that Eigen::Tensor::random in GPU will SEGFAULT. // Use std::random and thrust::random(thrust is a std library in CUDA) to // implement uniform random. @@ -66,18 +75,50 @@ class GPUUniformRandomKernel : public framework::OpKernel { T max = static_cast(context.Attr("max")); thrust::counting_iterator index_sequence_begin(0); int64_t size = tensor->numel(); - thrust::transform(index_sequence_begin, index_sequence_begin + size, - thrust::device_ptr(data), - UniformGenerator(min, max, seed)); + if (out_var->IsType() && + std::type_index(typeid(T)) == + std::type_index(typeid(platform::float16))) { + framework::Tensor master_copy_tensor; + master_copy_tensor.Resize(tensor->dims()); + float* master_copy_tensor_data = + master_copy_tensor.mutable_data(context.GetPlace()); + thrust::transform(index_sequence_begin, index_sequence_begin + size, + thrust::device_ptr(master_copy_tensor_data), + UniformGenerator(static_cast(min), + static_cast(max), seed)); + platform::Transform trans; + auto* in_begin = master_copy_tensor.data(); + auto* in_end = in_begin + master_copy_tensor.numel(); + auto* out_begin = tensor->mutable_data(context.GetPlace()); + trans(context.template device_context(), + in_begin, in_end, out_begin, CastFunctor()); + } else { + thrust::transform(index_sequence_begin, index_sequence_begin + size, + thrust::device_ptr(data), + UniformGenerator(min, max, seed)); + } + if (VLOG_IS_ON(5)) { + framework::Tensor cpu_tensor; + framework::TensorCopySync(*tensor, platform::CPUPlace(), &cpu_tensor); + auto& dev_ctx = + *platform::DeviceContextPool::Instance().Get(context.GetPlace()); + dev_ctx.Wait(); + auto x = framework::EigenVector::Flatten(cpu_tensor); + VLOG(5) << "The Uniform output " << x; + } } }; } // namespace operators } // namespace paddle -REGISTER_OP_CUDA_KERNEL(uniform_random, - paddle::operators::GPUUniformRandomKernel, - paddle::operators::GPUUniformRandomKernel); -REGISTER_OP_CUDA_KERNEL(uniform_random_batch_size_like, - paddle::operators::GPUUniformRandomKernel, - paddle::operators::GPUUniformRandomKernel); +namespace plat = paddle::platform; +REGISTER_OP_CUDA_KERNEL( + uniform_random, paddle::operators::GPUUniformRandomKernel, + paddle::operators::GPUUniformRandomKernel, + paddle::operators::GPUUniformRandomKernel); +REGISTER_OP_CUDA_KERNEL( + uniform_random_batch_size_like, + paddle::operators::GPUUniformRandomKernel, + paddle::operators::GPUUniformRandomKernel, + paddle::operators::GPUUniformRandomKernel); From 9f3789944c2c98605f26ffd224fbe1df02fa2e68 Mon Sep 17 00:00:00 2001 From: luotao1 Date: Thu, 16 Aug 2018 11:34:21 +0800 Subject: [PATCH 5/7] use latest anakin commit --- CMakeLists.txt | 3 ++- cmake/external/anakin.cmake | 5 ++--- paddle/fluid/inference/api/CMakeLists.txt | 2 +- 3 files changed, 5 insertions(+), 5 deletions(-) diff --git a/CMakeLists.txt b/CMakeLists.txt index 920c20d6f8..6844772711 100644 --- a/CMakeLists.txt +++ b/CMakeLists.txt @@ -204,11 +204,12 @@ include(external/snappy) # download snappy include(external/snappystream) include(external/threadpool) -set(WITH_ANAKIN OFF CACHE STRING "Disable Anakin first, will add it later." FORCE) if(WITH_GPU) include(cuda) include(tensorrt) include(external/anakin) +elseif() + set(WITH_ANAKIN OFF CACHE STRING "Anakin is used in GPU only now." FORCE) endif() include(cudnn) # set cudnn libraries, must before configure diff --git a/cmake/external/anakin.cmake b/cmake/external/anakin.cmake index 5de7ca8f46..455ef91ac5 100644 --- a/cmake/external/anakin.cmake +++ b/cmake/external/anakin.cmake @@ -35,9 +35,8 @@ set(ANAKIN_COMPILE_EXTRA_FLAGS ExternalProject_Add( extern_anakin ${EXTERNAL_PROJECT_LOG_ARGS} - # TODO(luotao): use PaddlePaddle/Anakin later - GIT_REPOSITORY "https://github.com/luotao1/Anakin" - GIT_TAG "842a89ae3747ede25d8acbc29030d2eb602ced1f" + GIT_REPOSITORY "https://github.com/PaddlePaddle/Anakin" + GIT_TAG "04256ba78fa3da0beb74e8036c8efd68c12824d6" PREFIX ${ANAKIN_SOURCE_DIR} UPDATE_COMMAND "" CMAKE_ARGS -DUSE_GPU_PLACE=YES diff --git a/paddle/fluid/inference/api/CMakeLists.txt b/paddle/fluid/inference/api/CMakeLists.txt index 83867e0a2c..a72e27d651 100644 --- a/paddle/fluid/inference/api/CMakeLists.txt +++ b/paddle/fluid/inference/api/CMakeLists.txt @@ -60,7 +60,7 @@ cc_library(paddle_inference_tensorrt_subgraph_engine inference_api_test(test_api_tensorrt_subgraph_engine SRC api_tensorrt_subgraph_engine_tester.cc ARGS test_word2vec) endif() -if (WITH_ANAKIN) # only needed in CI +if (WITH_ANAKIN AND WITH_GPU) # only needed in CI # compile the libinference_anakin_api.a and anakin.so. nv_library(inference_anakin_api SRCS api.cc api_anakin_engine.cc DEPS anakin_shared anakin_saber) #nv_library(inference_anakin_api_shared SHARED SRCS api.cc api_anakin_engine.cc DEPS anakin) From c44fb003715aab90d14f0d0fce020d0b65ec6fbf Mon Sep 17 00:00:00 2001 From: qingqing01 Date: Thu, 16 Aug 2018 12:01:22 +0800 Subject: [PATCH 6/7] Add name in relu and log API. (#12438) --- paddle/fluid/API.spec | 4 ++-- python/paddle/fluid/layers/nn.py | 8 ++++++-- 2 files changed, 8 insertions(+), 4 deletions(-) diff --git a/paddle/fluid/API.spec b/paddle/fluid/API.spec index ea9105d79c..e963902a50 100644 --- a/paddle/fluid/API.spec +++ b/paddle/fluid/API.spec @@ -155,8 +155,8 @@ paddle.fluid.layers.resize_bilinear ArgSpec(args=['input', 'out_shape', 'scale', paddle.fluid.layers.gather ArgSpec(args=['input', 'index'], varargs=None, keywords=None, defaults=None) paddle.fluid.layers.random_crop ArgSpec(args=['x', 'shape', 'seed'], varargs=None, keywords=None, defaults=(None,)) paddle.fluid.layers.mean_iou ArgSpec(args=['input', 'label', 'num_classes'], varargs=None, keywords=None, defaults=None) -paddle.fluid.layers.relu ArgSpec(args=['x'], varargs=None, keywords=None, defaults=None) -paddle.fluid.layers.log ArgSpec(args=['x'], varargs=None, keywords=None, defaults=None) +paddle.fluid.layers.relu ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)) +paddle.fluid.layers.log ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)) paddle.fluid.layers.crop ArgSpec(args=['x', 'shape', 'offsets', 'name'], varargs=None, keywords=None, defaults=(None, None, None)) paddle.fluid.layers.rank_loss ArgSpec(args=['label', 'left', 'right', 'name'], varargs=None, keywords=None, defaults=(None,)) paddle.fluid.layers.prelu ArgSpec(args=['x', 'mode', 'param_attr', 'name'], varargs=None, keywords=None, defaults=(None, None)) diff --git a/python/paddle/fluid/layers/nn.py b/python/paddle/fluid/layers/nn.py index 3e50fc91d9..be852b6711 100644 --- a/python/paddle/fluid/layers/nn.py +++ b/python/paddle/fluid/layers/nn.py @@ -5090,7 +5090,7 @@ def random_crop(x, shape, seed=None): return out -def log(x): +def log(x, name=None): """ Calculates the natural log of the given input tensor, element-wise. @@ -5100,6 +5100,8 @@ def log(x): Args: x (Variable): Input tensor. + name (str|None, default None): A name for this layer If set None, + the layer will be named automatically. Returns: Variable: The natural log of the input tensor computed element-wise. @@ -5117,7 +5119,7 @@ def log(x): return out -def relu(x): +def relu(x, name=None): """ Relu takes one input data (Tensor) and produces one output data (Tensor) where the rectified linear function, y = max(0, x), is applied to @@ -5129,6 +5131,8 @@ def relu(x): Args: x (Variable): The input tensor. + name (str|None, default None): A name for this layer If set None, + the layer will be named automatically. Returns: Variable: The output tensor with the same shape as input. From 317e18abd2aa69390dcc6a0d6760ba954597863e Mon Sep 17 00:00:00 2001 From: Qingsheng Li Date: Thu, 16 Aug 2018 13:00:55 +0800 Subject: [PATCH 7/7] Remove Data Sharing between input and output in scatter_op (#12672) * Remove Data Sharing between input and output in scatter_op * Removed data sharing in backward op --- paddle/fluid/operators/scatter_op.h | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/paddle/fluid/operators/scatter_op.h b/paddle/fluid/operators/scatter_op.h index d29947b55e..181bb1af5c 100644 --- a/paddle/fluid/operators/scatter_op.h +++ b/paddle/fluid/operators/scatter_op.h @@ -35,7 +35,7 @@ class ScatterOpKernel : public framework::OpKernel { auto *Out = ctx.Output("Out"); // In place output: Out = X, Out[Ids] += Updates - Out->ShareDataWith(*X); + framework::TensorCopySync(*X, ctx.GetPlace(), Out); // Apply ScatterUpdate: Out[index] += Updates[:] ScatterAssign(ctx.device_context(), *Updates, *Ids, Out); } @@ -53,7 +53,7 @@ class ScatterGradientOpKernel : public framework::OpKernel { auto *dOut = ctx.Input(framework::GradVarName("Out")); // In place gradient: dX = dO - dX->ShareDataWith(*dOut); + framework::TensorCopySync(*dOut, ctx.GetPlace(), dX); dUpdates->mutable_data(ctx.GetPlace()); // Gradient by Gather: dUpdates += dO[Ids] CPUGather(ctx.device_context(), *dOut, *Ids, dUpdates);