Merge branch 'develop' of https://github.com/PaddlePaddle/Paddle into add-async-ssa-graph-executor-communicator
test=developrevert-16555-model_data_cryption_link_all_lib
Qiao Longfei
6 years ago
commit
d8974e6da0
@ -0,0 +1,32 @@
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if(NOT WITH_GPU)
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return()
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endif()
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set(ANAKIN_ROOT "/usr" CACHE PATH "ANAKIN ROOT")
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find_path(ANAKIN_INCLUDE_DIR anakin_config.h
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PATHS ${ANAKIN_ROOT} ${ANAKIN_ROOT}/include
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$ENV{ANAKIN_ROOT} $ENV{ANAKIN_ROOT}/include
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NO_DEFAULT_PATH
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)
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find_library(ANAKIN_LIBRARY NAMES libanakin_saber_common.so libanakin.so
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PATHS ${ANAKIN_ROOT}
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$ENV{ANAKIN_ROOT} $ENV{ANAKIN_ROOT}/lib
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NO_DEFAULT_PATH
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DOC "Path to ANAKIN library.")
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if(ANAKIN_INCLUDE_DIR AND ANAKIN_LIBRARY)
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if(WITH_DSO)
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set(ANAKIN_FOUND ON)
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endif(WITH_DSO)
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else()
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set(ANAKIN_FOUND OFF)
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endif()
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if(ANAKIN_FOUND)
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message(STATUS "Current ANAKIN header is ${ANAKIN_INCLUDE_DIR}/anakin_config.h. ")
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include_directories(${ANAKIN_ROOT}/include)
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include_directories(${ANAKIN_ROOT}/include/saber)
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link_directories(${ANAKIN_ROOT})
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add_definitions(-DPADDLE_WITH_ANAKIN)
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endif()
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@ -0,0 +1,42 @@
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# Copyright (c) 2016 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(ExternalProject)
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SET(DGC_SOURCES_DIR "${THIRD_PARTY_PATH}/dgc")
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SET(DGC_INSTALL_DIR "${THIRD_PARTY_PATH}/install/dgc")
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SET(DGC_INCLUDE_DIR "${DGC_INSTALL_DIR}/include" CACHE PATH "dgc include directory." FORCE)
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SET(DGC_LIBRARIES "${DGC_INSTALL_DIR}/lib/libdgc.a" CACHE FILEPATH "dgc library." FORCE)
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INCLUDE_DIRECTORIES(${DGC_INCLUDE_DIR})
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ExternalProject_Add(
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extern_dgc
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${EXTERNAL_PROJECT_LOG_ARGS}
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GIT_REPOSITORY "https://github.com/PaddlePaddle/Fleet"
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GIT_TAG "2d04dc3800cdd0601f1b65d547dabcc60b0cf9dc"
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SOURCE_DIR "${DGC_SOURCES_DIR}"
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CONFIGURE_COMMAND ""
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BUILD_COMMAND cd collective && make -j
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INSTALL_COMMAND mkdir -p ${DGC_INSTALL_DIR}/lib/ ${DGC_INCLUDE_DIR}/dgc
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&& cp ${DGC_SOURCES_DIR}/collective/build/lib/libdgc.a ${DGC_LIBRARIES}
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&& cp ${DGC_SOURCES_DIR}/collective/build/include/dgc.h ${DGC_INCLUDE_DIR}/dgc/
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BUILD_IN_SOURCE 1
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)
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ADD_LIBRARY(dgc SHARED IMPORTED GLOBAL)
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SET_PROPERTY(TARGET dgc PROPERTY IMPORTED_LOCATION ${DGC_LIBRARIES})
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ADD_DEPENDENCIES(dgc extern_dgc)
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LIST(APPEND external_project_dependencies dgc)
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@ -1,140 +0,0 @@
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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 <string>
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#include <vector>
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#include "paddle/fluid/framework/details/computation_op_handle.h"
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#include "paddle/fluid/framework/details/op_handle_base.h"
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#include "paddle/fluid/framework/details/var_handle.h"
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#include "paddle/fluid/framework/garbage_collector.h"
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#include "paddle/fluid/framework/lod_tensor_array.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/framework/tensor.h"
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namespace paddle {
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namespace framework {
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namespace details {
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class EarlyDeleteOpHandle : public OpHandleBase {
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public:
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EarlyDeleteOpHandle(ir::Node* node, const Scope* scope,
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const platform::Place& place,
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const std::vector<std::string>& names,
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GarbageCollector* gc)
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: OpHandleBase(node),
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scope_(scope),
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place_(place),
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names_(names),
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gc_(gc) {
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#ifdef PADDLE_WITH_CUDA
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if (IsStreamGarabageCollector()) {
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auto gpu_place = boost::get<platform::CUDAPlace>(place);
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PADDLE_ENFORCE(cudaSetDevice(gpu_place.device));
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PADDLE_ENFORCE(cudaEventCreateWithFlags(&event_, cudaEventDisableTiming));
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}
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#endif
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}
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~EarlyDeleteOpHandle() {
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#ifdef PADDLE_WITH_CUDA
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if (IsStreamGarabageCollector()) {
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auto gpu_place = boost::get<platform::CUDAPlace>(dev_ctx_->GetPlace());
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PADDLE_ENFORCE(cudaSetDevice(gpu_place.device));
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PADDLE_ENFORCE(cudaEventDestroy(event_));
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}
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#endif
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}
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std::string Name() const override { return "early_delete"; }
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protected:
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void RunImpl() override {
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std::vector<std::shared_ptr<memory::Allocation>> tensors;
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auto* local_scope = scope_->FindVar(kLocalExecScopeName)->Get<Scope*>();
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for (auto& var_name : names_) {
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auto* var = local_scope->FindVar(var_name);
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PADDLE_ENFORCE(var != nullptr,
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string::Sprintf("Local Scope not has var %s", var_name));
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if (var->IsType<LoDTensor>()) {
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tensors.emplace_back(var->GetMutable<LoDTensor>()->MoveMemoryHolder());
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} else if (var->IsType<SelectedRows>()) {
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tensors.emplace_back(var->GetMutable<SelectedRows>()
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->mutable_value()
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->MoveMemoryHolder());
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} else if (var->IsType<LoDTensorArray>()) {
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LoDTensorArray* tensor_array = var->GetMutable<LoDTensorArray>();
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for (auto& tensor : *tensor_array) {
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tensors.emplace_back(tensor.MoveMemoryHolder());
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}
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}
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}
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if (!tensors.empty()) {
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ClearTensors(tensors);
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}
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}
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private:
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void ClearTensors(
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const std::vector<std::shared_ptr<memory::Allocation>>& tensors) {
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if (platform::is_cpu_place(place_)) {
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ClearCPUTensors(tensors);
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} else {
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ClearGPUTensors(tensors);
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}
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}
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void ClearCPUTensors(
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const std::vector<std::shared_ptr<memory::Allocation>>& tensors) {
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auto* gc = dynamic_cast<CPUGarbageCollector*>(gc_);
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if (gc != nullptr) {
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gc->Add(tensors);
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}
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}
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void ClearGPUTensors(
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const std::vector<std::shared_ptr<memory::Allocation>>& tensors) {
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#ifdef PADDLE_WITH_CUDA
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auto* gc = dynamic_cast<StreamGarbageCollector*>(gc_);
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if (gc != nullptr) {
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auto compute_stream = dev_ctx_->stream();
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auto callback_stream = gc->stream();
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auto callback_func = [=]() {
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PADDLE_ENFORCE(cudaEventRecord(event_, compute_stream));
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PADDLE_ENFORCE(cudaStreamWaitEvent(callback_stream, event_, 0));
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};
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gc_->Add(tensors, callback_func);
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} else {
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gc_->Add(tensors);
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}
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}
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bool IsStreamGarabageCollector() const {
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return dynamic_cast<const StreamGarbageCollector*>(gc_) != nullptr;
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#endif
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}
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const Scope* scope_;
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const platform::Place place_;
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std::vector<std::string> names_;
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GarbageCollector* gc_;
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#ifdef PADDLE_WITH_CUDA
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platform::CUDADeviceContext* dev_ctx_;
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cudaEvent_t event_;
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#endif
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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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