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99 lines
3.3 KiB
99 lines
3.3 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 <map>
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#include <string>
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#include <vector>
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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/platform/device_context.h"
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namespace paddle {
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namespace framework {
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extern void InitializeVariable(Variable* var, proto::VarType::Type var_type);
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struct ExecutorPrepareContext {
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ExecutorPrepareContext(const framework::ProgramDesc& prog, size_t block_id);
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~ExecutorPrepareContext();
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const framework::ProgramDesc& prog_;
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size_t block_id_;
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std::vector<std::unique_ptr<OperatorBase>> ops_;
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};
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class Executor {
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public:
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// TODO(dzhwinter) : Do not rely on this function, it will be removed
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explicit Executor(const platform::DeviceContext& device)
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: Executor(device.GetPlace()) {}
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explicit Executor(const platform::Place& place);
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#ifdef PADDLE_WITH_DISTRIBUTE
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/*
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* Sending signal to pserver to mark current trainer stop.
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*/
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void Complete();
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#endif
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/* @Brief
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* Runtime evaluation of the given ProgramDesc under certain Scope
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*
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* @param
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* ProgramDesc
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* Scope
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*/
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void Run(const ProgramDesc& prog, Scope* scope, int block_id,
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bool create_local_scope = true, bool create_vars = true);
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void Run(const ProgramDesc& program, Scope* scope,
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std::map<std::string, const LoDTensor*>* feed_targets,
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std::map<std::string, LoDTensor*>* fetch_targets,
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bool create_local_scope = true, bool create_vars = true,
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const std::string& feed_holder_name = "feed",
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const std::string& fetch_holder_name = "fetch");
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static std::unique_ptr<ExecutorPrepareContext> Prepare(
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const ProgramDesc& program, int block_id);
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static std::vector<std::shared_ptr<ExecutorPrepareContext>> Prepare(
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const ProgramDesc& program, const std::vector<int>& block_ids);
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void CreateVariables(const ProgramDesc& pdesc, Scope* scope, int block_id);
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void RunPreparedContext(ExecutorPrepareContext* ctx, Scope* scope,
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bool create_local_scope = true,
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bool create_vars = true);
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void RunPreparedContext(ExecutorPrepareContext* ctx, Scope* scope,
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std::map<std::string, const LoDTensor*>* feed_targets,
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std::map<std::string, LoDTensor*>* fetch_targets,
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bool create_local_scope = true,
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bool create_vars = true,
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const std::string& feed_holder_name = "feed",
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const std::string& fetch_holder_name = "fetch");
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void EnableMKLDNN(const ProgramDesc& program);
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private:
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const platform::Place place_;
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};
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} // namespace framework
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} // namespace paddle
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