JiabinYang
6 years ago
commit
e0a89503f8
@ -0,0 +1,46 @@
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INCLUDE(ExternalProject)
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set(XXHASH_SOURCE_DIR ${THIRD_PARTY_PATH}/xxhash)
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set(XXHASH_INSTALL_DIR ${THIRD_PARTY_PATH}/install/xxhash)
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set(XXHASH_INCLUDE_DIR "${XXHASH_INSTALL_DIR}/include")
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IF(WITH_STATIC_LIB)
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SET(BUILD_CMD make lib)
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ELSE()
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SET(BUILD_CMD sed -i "s/-Wstrict-prototypes -Wundef/-Wstrict-prototypes -Wundef -fPIC/g" ${XXHASH_SOURCE_DIR}/src/extern_xxhash/Makefile && make lib)
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ENDIF()
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ExternalProject_Add(
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extern_xxhash
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${EXTERNAL_PROJECT_LOG_ARGS}
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GIT_REPOSITORY "https://github.com/Cyan4973/xxHash"
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GIT_TAG "v0.6.5"
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PREFIX ${XXHASH_SOURCE_DIR}
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DOWNLOAD_NAME "xxhash"
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UPDATE_COMMAND ""
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CONFIGURE_COMMAND ""
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BUILD_IN_SOURCE 1
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PATCH_COMMAND
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BUILD_COMMAND ${BUILD_CMD}
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INSTALL_COMMAND export PREFIX=${XXHASH_INSTALL_DIR}/ && make install
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TEST_COMMAND ""
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)
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set(XXHASH_LIBRARIES "${XXHASH_INSTALL_DIR}/lib/libxxhash.a")
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INCLUDE_DIRECTORIES(${XXHASH_INCLUDE_DIR})
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add_library(xxhash STATIC IMPORTED GLOBAL)
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set_property(TARGET xxhash PROPERTY IMPORTED_LOCATION ${XXHASH_LIBRARIES})
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include_directories(${XXHASH_INCLUDE_DIR})
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add_dependencies(xxhash extern_xxhash)
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LIST(APPEND external_project_dependencies xxhash)
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IF(WITH_C_API)
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INSTALL(DIRECTORY ${XXHASH_INCLUDE_DIR} DESTINATION third_party/xxhash)
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IF(ANDROID)
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INSTALL(FILES ${XXHASH_LIBRARIES} DESTINATION third_party/xxhash/lib/${ANDROID_ABI})
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ELSE()
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INSTALL(FILES ${XXHASH_LIBRARIES} DESTINATION third_party/xxhash/lib)
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ENDIF()
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ENDIF()
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@ -0,0 +1,55 @@
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// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#include "paddle/fluid/framework/details/fused_broadcast_op_handle.h"
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#include "paddle/fluid/framework/details/container_cast.h"
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#include "paddle/fluid/framework/details/variable_visitor.h"
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#include "paddle/fluid/platform/profiler.h"
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namespace paddle {
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namespace framework {
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namespace details {
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void FusedBroadcastOpHandle::RunImpl() {
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platform::RecordEvent record_event(Name(), dev_ctxes_.begin()->second);
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if (places_.size() == 1UL) return;
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auto in_var_handles = DynamicCast<VarHandle>(inputs_);
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auto out_var_handles = DynamicCast<VarHandle>(outputs_);
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WaitInputVarGenerated();
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std::vector<const Scope *> var_scopes;
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for (auto *s : local_scopes_) {
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var_scopes.emplace_back(s->FindVar(kLocalExecScopeName)->Get<Scope *>());
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}
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size_t place_num = places_.size();
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PADDLE_ENFORCE_EQ(in_var_handles.size() * place_num, out_var_handles.size());
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for (size_t i = 0; i < in_var_handles.size(); ++i) {
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BroadcastOneVar(
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*in_var_handles[i],
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std::vector<VarHandle *>(out_var_handles.begin() + i * place_num,
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out_var_handles.begin() + (i + 1) * place_num),
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var_scopes);
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}
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}
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std::string FusedBroadcastOpHandle::Name() const { return "fused_broadcast"; }
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} // namespace details
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} // namespace framework
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} // namespace paddle
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@ -0,0 +1,57 @@
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// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#pragma once
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#include <map>
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#include <string>
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#include <vector>
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#include "paddle/fluid/framework/details/broadcast_op_handle.h"
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#include "paddle/fluid/framework/details/multi_devices_helper.h"
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#include "paddle/fluid/framework/lod_tensor.h"
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#include "paddle/fluid/framework/scope.h"
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#include "paddle/fluid/framework/selected_rows.h"
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#include "paddle/fluid/platform/device_context.h"
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#ifdef PADDLE_WITH_CUDA
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#include "paddle/fluid/platform/nccl_helper.h"
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#endif
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namespace paddle {
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namespace framework {
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namespace details {
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struct FusedBroadcastOpHandle : public BroadcastOpHandle {
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public:
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#ifdef PADDLE_WITH_CUDA
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FusedBroadcastOpHandle(ir::Node *node,
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const std::vector<Scope *> local_scopes,
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const std::vector<platform::Place> &places,
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const platform::NCCLContextMap *nccl_ctx)
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: BroadcastOpHandle(node, local_scopes, places, nccl_ctx) {}
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#else
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FusedBroadcastOpHandle(ir::Node* node, const std::vector<Scope*> local_scopes,
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const std::vector<platform::Place>& places)
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: BroadcastOpHandle(node, local_scopes, places) {}
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#endif
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std::string Name() const override;
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protected:
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void RunImpl() override;
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};
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} // namespace details
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} // namespace framework
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} // namespace paddle
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File diff suppressed because it is too large
Load Diff
@ -0,0 +1,44 @@
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// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
// See the License for the specific language governing permissions and
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// limitations under the License.
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#pragma once
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#include "paddle/fluid/framework/ir/fuse_pass_base.h"
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#include "paddle/fluid/framework/ir/graph.h"
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#include "paddle/fluid/framework/ir/pass.h"
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namespace paddle {
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namespace framework {
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namespace ir {
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// BatchMergePass is used to copy forward and backward ops for several
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// times to run several batches to simulate large batch size training
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// as if we have more than 1 GPUs.
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// User can define how many batches to run, gradients will be merged
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// through those repeats, and then do optimization using merged gradients.
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// This pass is extremely useful when doing large batch-size distributed
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// sync training, we can simulate even large batch size as if we have more
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// GPUs.
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class BatchMergePass : public Pass {
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public:
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virtual ~BatchMergePass() {}
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protected:
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std::unique_ptr<Graph> ApplyImpl(std::unique_ptr<Graph> graph) const override;
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};
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} // namespace ir
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} // namespace framework
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} // namespace paddle
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