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92 lines
2.7 KiB
92 lines
2.7 KiB
/* Copyright (c) 2016 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 <future>
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#include <unordered_set>
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#include "paddle/fluid/framework/executor.h"
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#include "paddle/fluid/framework/op_info.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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#include "paddle/fluid/framework/tensor.h"
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#include "paddle/fluid/operators/nccl/nccl_gpu_common.h"
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#include "paddle/fluid/platform/device_context.h"
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namespace paddle {
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namespace framework {
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class ParallelExecutorPrivate;
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class VarHandle;
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class OpHandle;
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class VarHandleBase;
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struct GuardedBool {
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public:
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GuardedBool() {}
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operator bool() const {
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std::lock_guard<std::mutex> g(mtx_);
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return value_;
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}
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GuardedBool& operator=(bool o) {
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std::lock_guard<std::mutex> g(mtx_);
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value_ = o;
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return *this;
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}
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private:
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mutable std::mutex mtx_;
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bool value_;
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};
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class ParallelExecutor {
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public:
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explicit ParallelExecutor(const std::vector<platform::Place>& places,
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const std::unordered_set<std::string>& params,
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const ProgramDesc& startup_program,
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const ProgramDesc& main_program,
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const std::string& loss_var_name, Scope* scope);
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void Run(const std::vector<std::string>& fetch_tensors,
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const std::string& fetched_var_name = "fetched_var");
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private:
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ParallelExecutorPrivate* member_;
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void BCastParamsToGPUs(const ProgramDesc& startup_program) const;
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VarHandle* GetVarHandle(const std::string& each_var_name,
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const platform::Place& place) const;
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void GenerateVar(OpHandle* op_handle, const std::string& each_var_name,
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const platform::Place& place) const;
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void ConstructDependencyGraph(const std::unordered_set<std::string>& params,
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const ProgramDesc& main_program,
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const std::string& loss_var_name) const;
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void BuildNCCLCommunicator() const;
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void RunOp(std::unordered_map<VarHandleBase*, GuardedBool>& pending_vars,
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OpHandle* op) const;
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void PolishGraphToSupportDataHarzaeds() const;
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};
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} // namespace framework
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} // namespace paddle
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