/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. */ #pragma once #include #include #include #include "paddle/fluid/framework/garbage_collector.h" #include "paddle/fluid/framework/op_info.h" #include "paddle/fluid/framework/program_desc.h" #include "paddle/fluid/framework/scope.h" #include "paddle/fluid/framework/tensor.h" #include "paddle/fluid/platform/device_context.h" namespace paddle { namespace framework { extern void InitializeVariable(Variable* var, proto::VarType::Type var_type); int64_t GetEagerDeletionThreshold(); template std::unordered_map GetNonPersistableReferenceCount( const ProgramDesc& prog, size_t block_id) { auto& block = prog.Block(block_id); std::unordered_set ignored_vars; std::unordered_map ref_cnts; for (auto var_desc : block.AllVars()) { auto type = var_desc->Proto()->type().type(); if (type != proto::VarType::LOD_TENSOR || var_desc->Persistable()) { ignored_vars.insert(var_desc->Name()); // ignore persistable vars } } for (auto op_desc : block.AllOps()) { for (auto& input : op_desc->Inputs()) { for (auto& input_name : input.second) { if (!ignored_vars.count(input_name)) { if (ref_cnts.count(input_name)) ++ref_cnts[input_name]; else ref_cnts[input_name] = 1; } } } for (auto& output : op_desc->Outputs()) { for (auto output_name : output.second) { if (!ignored_vars.count(output_name)) { if (ref_cnts.count(output_name)) ++ref_cnts[output_name]; else ref_cnts[output_name] = 1; } } } } return ref_cnts; } struct ExecutorPrepareContext { ExecutorPrepareContext(const framework::ProgramDesc& prog, size_t block_id); ~ExecutorPrepareContext(); const framework::ProgramDesc& prog_; size_t block_id_; std::vector> ops_; std::unordered_map ref_cnts_; }; class Executor { public: // TODO(dzhwinter) : Do not rely on this function, it will be removed explicit Executor(const platform::DeviceContext& device) : Executor(device.GetPlace()) {} explicit Executor(const platform::Place& place); #ifdef PADDLE_WITH_DISTRIBUTE /* * Sending signal to pserver to mark current pass started. */ void BeginPass(); /* * Sending signal to pserver to mark current pass finished. */ void EndPass(); #endif /* @Brief * Runtime evaluation of the given ProgramDesc under certain Scope * * @param * ProgramDesc * Scope */ void Run(const ProgramDesc& prog, Scope* scope, int block_id, bool create_local_scope = true, bool create_vars = true); void Run(const ProgramDesc& program, Scope* scope, std::map* feed_targets, std::map* fetch_targets, bool create_local_scope = true, bool create_vars = true, const std::string& feed_holder_name = "feed", const std::string& fetch_holder_name = "fetch"); static std::unique_ptr Prepare( const ProgramDesc& program, int block_id); static std::vector> Prepare( const ProgramDesc& program, const std::vector& block_ids); void CreateVariables(const ProgramDesc& pdesc, Scope* scope, int block_id); void RunPreparedContext(ExecutorPrepareContext* ctx, Scope* scope, bool create_local_scope = true, bool create_vars = true, bool keep_kids = false); void RunPreparedContext(ExecutorPrepareContext* ctx, Scope* scope, std::map* feed_targets, std::map* fetch_targets, bool create_local_scope = true, bool create_vars = true, const std::string& feed_holder_name = "feed", const std::string& fetch_holder_name = "fetch"); void EnableMKLDNN(const ProgramDesc& program); private: const platform::Place place_; }; } // namespace framework } // namespace paddle