Superjom
8 years ago
commit
ddafe5ceeb
@ -0,0 +1,72 @@
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# Copyright (c) 2017 PaddlePaddle Authors. All Rights Reserve.
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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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IF(NOT ${WITH_MKLDNN})
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return()
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ENDIF(NOT ${WITH_MKLDNN})
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INCLUDE(ExternalProject)
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SET(MKLDNN_PROJECT "extern_mkldnn")
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SET(MKLDNN_SOURCES_DIR ${THIRD_PARTY_PATH}/mkldnn)
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SET(MKLDNN_INSTALL_ROOT ${CMAKE_INSTALL_PREFIX})
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IF(NOT "$ENV{HOME}" STREQUAL "/root")
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SET(MKLDNN_INSTALL_ROOT "$ENV{HOME}")
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ENDIF()
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SET(MKLDNN_INSTALL_DIR "${MKLDNN_INSTALL_ROOT}/opt/paddle/third_party/mkldnn")
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SET(MKLDNN_INCLUDE_DIR "${MKLDNN_INSTALL_DIR}/include" CACHE PATH "mkldnn include directory." FORCE)
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IF(WIN32)
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MESSAGE(WARNING "It is not supported compiling with mkldnn in windows Paddle yet."
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"Force WITH_MKLDNN=OFF")
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SET(WITH_MKLDNN OFF)
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return()
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ELSE(WIN32)
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SET(MKLDNN_LIBRARY "${MKLDNN_INSTALL_DIR}/lib/libmkldnn.so" CACHE FILEPATH "mkldnn library." FORCE)
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MESSAGE(STATUS "Set ${MKLDNN_INSTALL_DIR}/lib to runtime path")
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SET(CMAKE_INSTALL_RPATH_USE_LINK_PATH TRUE)
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#SET(CMAKE_MACOSX_RPATH 1) # hold for MacOS
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SET(CMAKE_INSTALL_RPATH "${CMAKE_INSTALL_RPATH}" "${MKLDNN_INSTALL_DIR}/lib")
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ENDIF(WIN32)
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INCLUDE_DIRECTORIES(${MKLDNN_INCLUDE_DIR})
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IF(${CBLAS_PROVIDER} STREQUAL "MKLML")
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SET(MKLDNN_DEPENDS ${MKLML_PROJECT})
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SET(MKLDNN_MKLROOT ${MKLML_ROOT})
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SET(MKLDNN_IOMP_LIB ${MKLML_IOMP_LIB})
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SET(MKLDNN_IOMP_DIR ${MKLML_LIB_DIR})
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ENDIF()
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ExternalProject_Add(
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${MKLDNN_PROJECT}
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${EXTERNAL_PROJECT_LOG_ARGS}
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DEPENDS ${MKLDNN_DEPENDS}
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GIT_REPOSITORY "https://github.com/01org/mkl-dnn.git"
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GIT_TAG "v0.9"
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PREFIX ${MKLDNN_SOURCES_DIR}
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CONFIGURE_COMMAND mkdir -p <SOURCE_DIR>/build
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BUILD_COMMAND cd <SOURCE_DIR>/build
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&& cmake .. -DCMAKE_INSTALL_PREFIX=${MKLDNN_INSTALL_DIR} -DMKLROOT=${MKLDNN_MKLROOT}
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&& $(MAKE)
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INSTALL_COMMAND cd <SOURCE_DIR>/build && $(MAKE) install
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UPDATE_COMMAND ""
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)
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ADD_LIBRARY(mkldnn SHARED IMPORTED GLOBAL)
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SET_PROPERTY(TARGET mkldnn PROPERTY IMPORTED_LOCATION ${MKLDNN_LIBRARY})
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ADD_DEPENDENCIES(mkldnn ${MKLDNN_PROJECT})
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MESSAGE(STATUS "Mkldnn library: ${MKLDNN_LIBRARY}")
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LIST(APPEND external_project_dependencies mkldnn)
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@ -0,0 +1,64 @@
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# Copyright (c) 2017 PaddlePaddle Authors. All Rights Reserve.
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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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IF(NOT ${WITH_MKLML})
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return()
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ENDIF(NOT ${WITH_MKLML})
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INCLUDE(ExternalProject)
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SET(MKLML_PROJECT "extern_mklml")
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SET(MKLML_VER "mklml_lnx_2018.0.20170425")
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SET(MKLML_URL "https://github.com/01org/mkl-dnn/releases/download/v0.9/${MKLML_VER}.tgz")
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SET(MKLML_SOURCE_DIR "${THIRD_PARTY_PATH}/mklml")
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SET(MKLML_DOWNLOAD_DIR "${MKLML_SOURCE_DIR}/src/${MKLML_PROJECT}")
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SET(MKLML_DST_DIR "opt/paddle/third_party/mklml")
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SET(MKLML_INSTALL_ROOT "${CMAKE_INSTALL_PREFIX}")
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IF(NOT "$ENV{HOME}" STREQUAL "/root")
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SET(MKLML_INSTALL_ROOT "$ENV{HOME}")
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ENDIF()
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SET(MKLML_INSTALL_DIR ${MKLML_INSTALL_ROOT}/${MKLML_DST_DIR})
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SET(MKLML_ROOT ${MKLML_INSTALL_DIR}/${MKLML_VER})
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SET(MKLML_INC_DIR ${MKLML_ROOT}/include)
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SET(MKLML_LIB_DIR ${MKLML_ROOT}/lib)
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SET(MKLML_LIB ${MKLML_LIB_DIR}/libmklml_intel.so)
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SET(MKLML_IOMP_LIB ${MKLML_LIB_DIR}/libiomp5.so)
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SET(CMAKE_INSTALL_RPATH "${CMAKE_INSTALL_RPATH}" "${MKLML_ROOT}/lib")
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INCLUDE_DIRECTORIES(${MKLML_INC_DIR})
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SET(mklml_cmakefile ${MKLML_DOWNLOAD_DIR}/CMakeLists.txt)
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FILE(WRITE ${mklml_cmakefile} "PROJECT(MKLML)\n"
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"cmake_minimum_required(VERSION 3.0)\n"
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"install(DIRECTORY ${MKLML_VER}\n"
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" DESTINATION ${MKLML_DST_DIR})\n")
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ExternalProject_Add(
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${MKLML_PROJECT}
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${EXTERNAL_PROJECT_LOG_ARGS}
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PREFIX ${MKLML_SOURCE_DIR}
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DOWNLOAD_DIR ${MKLML_DOWNLOAD_DIR}
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DOWNLOAD_COMMAND wget --no-check-certificate -O ${MKLML_DOWNLOAD_DIR}/${MKLML_VER}.tgz ${MKLML_URL}
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&& tar -xzf ${MKLML_DOWNLOAD_DIR}/${MKLML_VER}.tgz
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DOWNLOAD_NO_PROGRESS 1
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UPDATE_COMMAND ""
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CMAKE_ARGS -DCMAKE_INSTALL_PREFIX=${MKLML_INSTALL_ROOT}
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CMAKE_CACHE_ARGS -DCMAKE_INSTALL_PREFIX:PATH=${MKLML_INSTALL_ROOT}
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)
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ADD_LIBRARY(mklml SHARED IMPORTED GLOBAL)
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SET_PROPERTY(TARGET mklml PROPERTY IMPORTED_LOCATION ${MKLML_LIB})
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ADD_DEPENDENCIES(mklml ${MKLML_PROJECT})
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LIST(APPEND external_project_dependencies mklml)
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@ -0,0 +1,116 @@
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/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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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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http://www.apache.org/licenses/LICENSE-2.0
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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/framework/grad_op_builder.h"
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#include "paddle/framework/op_registry.h"
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namespace paddle {
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namespace framework {
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OperatorBase* GradOpBuilder::Build() {
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BuildOpInOutArgList();
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std::string grad_op_type = OpRegistry::grad_ops().at(op_->type_);
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OperatorBase* grad_op = OpRegistry::op_creators().at(grad_op_type)();
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grad_op->type_ = grad_op_type;
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CompleteGradOp(grad_op);
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return grad_op;
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}
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OpInOutArg* GradOpBuilder::BuildArg(const VarProto& var,
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const VarIndexMap& var_map,
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const std::vector<int>& format,
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InOutType type) {
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int idx = var_map.at(var.name());
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int begin_idx = format.empty() ? idx : format.at(idx);
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int end_idx = format.empty() ? idx + 1 : format.at(idx + 1);
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return new OpInOutArg(var.name(), type, !var.ignore_gradient(), begin_idx,
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end_idx);
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}
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void GradOpBuilder::BuildOpInOutArgList() {
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const OpProto& op_proto = OpRegistry::protos().at(op_->type_);
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const auto& var_map = *(OpRegistry::VarIndexMaps().at(op_->type_));
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const std::vector<int>& in_format =
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op_->attrs_.count("input_format")
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? op_->GetAttr<std::vector<int>>("input_format")
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: std::vector<int>();
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const std::vector<int>& out_format =
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op_->attrs_.count("output_format")
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? op_->GetAttr<std::vector<int>>("output_format")
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: std::vector<int>();
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for (const auto& var : op_proto.inputs()) {
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arg_list_.emplace_back(
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std::shared_ptr<OpInOutArg>(BuildArg(var, var_map, in_format, IN)));
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}
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for (const auto& var : op_proto.outputs()) {
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arg_list_.emplace_back(
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std::shared_ptr<OpInOutArg>(BuildArg(var, var_map, out_format, OUT)));
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}
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}
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void GradOpBuilder::AddArgIntoGradOp(const OpInOutArg* arg,
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std::vector<std::string>& in_out,
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std::vector<int>& format,
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VarIndexMap* varmap, int& idx,
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bool is_grad) const {
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std::string var_name = arg->proto_name_;
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if (is_grad) {
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var_name += OperatorBase::GRAD_VAR_SUFFIX();
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}
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(*varmap)[var_name] = idx++;
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size_t pre_sz = in_out.size();
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auto base_it =
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arg->type_ == IN ? op_->inputs_.begin() : op_->outputs_.begin();
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std::copy(base_it + arg->begin_idx_, base_it + arg->end_idx_,
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std::back_inserter(in_out));
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if (is_grad) {
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for (size_t i = pre_sz; i < in_out.size(); ++i) {
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in_out[i] += OperatorBase::GRAD_VAR_SUFFIX();
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}
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}
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format.push_back(in_out.size());
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}
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void GradOpBuilder::CompleteGradOp(OperatorBase* grad_op) const {
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grad_op->attrs_ = op_->attrs_;
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grad_op->attrs_.erase("input_format");
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grad_op->attrs_.erase("output_format");
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VarIndexMap* grad_varmap = new VarIndexMap();
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int in_idx = 0;
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int out_idx = 0;
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std::vector<int> in_format({0});
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std::vector<int> out_format({0});
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for (const auto& arg : arg_list_) {
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// op_'s inputs_ and outputs_
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if (arg->needed_in_grad_) {
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AddArgIntoGradOp(arg.get(), grad_op->inputs_, in_format, grad_varmap,
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in_idx, false);
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}
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if (arg->type_ == IN) {
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// gradients of op_'s inputs_
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AddArgIntoGradOp(arg.get(), grad_op->outputs_, out_format, grad_varmap,
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out_idx, true);
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} else {
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// gradients of op_'s outputs_
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AddArgIntoGradOp(arg.get(), grad_op->inputs_, in_format, grad_varmap,
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in_idx, true);
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}
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}
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grad_op->attrs_["input_format"] = in_format;
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grad_op->attrs_["output_format"] = out_format;
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grad_op->in_out_idxs_.reset(grad_varmap);
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}
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} // namespace framework
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} // namespace paddle
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@ -0,0 +1,48 @@
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#pragma once
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#include "paddle/framework/op_proto.pb.h"
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#include "paddle/framework/operator.h"
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namespace paddle {
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namespace framework {
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class OpRegistry;
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enum InOutType { IN, OUT };
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struct OpInOutArg {
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OpInOutArg(const std::string& proto_name, const InOutType& type,
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bool needed_in_grad, size_t begin_idx, size_t end_idx)
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: proto_name_(proto_name),
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type_(type),
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needed_in_grad_(needed_in_grad),
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begin_idx_(begin_idx),
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end_idx_(end_idx) {}
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std::string proto_name_;
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InOutType type_;
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bool needed_in_grad_;
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size_t begin_idx_;
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size_t end_idx_;
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};
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class GradOpBuilder {
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using VarIndexMap = std::unordered_map<std::string, int>;
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public:
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GradOpBuilder(const OperatorBase* op) : op_(op) {}
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OperatorBase* Build();
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private:
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OpInOutArg* BuildArg(const VarProto& var, const VarIndexMap& var_map,
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const std::vector<int>& format, InOutType type);
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void BuildOpInOutArgList();
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void AddArgIntoGradOp(const OpInOutArg* arg, std::vector<std::string>& in_out,
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std::vector<int>& format, VarIndexMap* varmap, int& idx,
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bool is_grad) const;
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void CompleteGradOp(OperatorBase* grad_op) const;
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const OperatorBase* op_;
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std::vector<std::shared_ptr<OpInOutArg>> arg_list_;
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};
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} // namespace framework
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} // namespace paddle
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