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89 lines
3.0 KiB
89 lines
3.0 KiB
/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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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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#pragma once
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#include <map>
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#include <memory>
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#include <mutex> // NOLINT
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#include <set>
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#include <string>
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#include <thread> // NOLINT
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#include <vector>
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#include "paddle/fluid/framework/data_feed.h"
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#include "paddle/fluid/framework/executor.h"
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#include "paddle/fluid/framework/program_desc.h"
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#include "paddle/fluid/framework/scope.h"
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namespace paddle {
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namespace framework {
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void CreateTensor(Variable* var, proto::VarType::Type var_type);
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class ExecutorThreadWorker {
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public:
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ExecutorThreadWorker()
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: thread_id_(-1), root_scope_(NULL), thread_scope_(NULL), debug_(false) {}
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~ExecutorThreadWorker() {}
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void CreateThreadResource(const framework::ProgramDesc& program,
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const paddle::platform::Place& place);
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void SetThreadId(int tid);
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void SetDebug(const bool debug) { debug_ = debug; }
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void SetRootScope(Scope* g_scope);
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// set cpu device in this function
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// cpu binding is used by default
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void SetDevice();
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// since we read data into memory that can not be accessed by program
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// we need to bind memory of data with corresponding variables in program
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// this function should be called after data feed is set
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void BindingDataFeedMemory();
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// set data feed declared in executor
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void SetDataFeed(const std::shared_ptr<DataFeed>& datafeed);
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// A multi-thread training function
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void TrainFiles();
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// set fetch variable names from python interface assigned by users
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void SetFetchVarNames(const std::vector<std::string>& fetch_var_names);
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private:
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void CreateThreadScope(const framework::ProgramDesc& program);
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void CreateThreadOperators(const framework::ProgramDesc& program);
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void SetMainProgram(const ProgramDesc& main_program_desc);
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void SetPlace(const paddle::platform::Place& place);
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protected:
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// thread index
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std::shared_ptr<DataFeed> thread_reader_; // shared queue, thread buffer
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int thread_id_;
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// operator name
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std::vector<std::string> op_names_;
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// thread level, local operators for forward and backward
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std::vector<OperatorBase*> ops_;
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// main program for training
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std::unique_ptr<framework::ProgramDesc> main_program_;
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// execution place
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platform::Place place_;
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// root scope for model parameters
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Scope* root_scope_;
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// a thread scope, father scope is global score which is shared
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Scope* thread_scope_;
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private:
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std::vector<std::string> fetch_var_names_;
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std::vector<std::vector<float>> fetch_values_;
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bool debug_;
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};
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} // namespace framework
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} // namespace paddle
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