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/*
* Copyright (c) 2019 Samsung Electronics Co., Ltd. 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.
*/
#ifndef __ONERT_EXEC_PARALLEL_EXECUTOR_H__
#define __ONERT_EXEC_PARALLEL_EXECUTOR_H__
#include <list>
#include <queue>
#include <unordered_map>
#include "exec/FunctionSequence.h"
#include "Job.h"
#include "ir/OperandIndexSequence.h"
#include "ir/Index.h"
#include <memory>
#include "exec/DataflowExecutor.h"
#include "ParallelScheduler.h"
namespace onert
{
namespace exec
{
/**
* @brief Class to execute Graph in parallel
*/
class ParallelExecutor : public DataflowExecutor
{
protected:
void notify(uint32_t finished_job_id) override;
public:
/**
* @brief Constructs a ParallelExecutor object
*
* @param lowered_graph LoweredGraph object
* @param tensor_builders Tensor builders that are currently used
* @param code_map OpSequence and its code map
*/
ParallelExecutor(std::unique_ptr<ir::LoweredGraph> lowered_graph,
const backend::TensorBuilderSet &tensor_builders, compiler::CodeMap &&code_map);
void executeImpl() override;
private:
std::condition_variable _cv_jobs;
std::mutex _mu_jobs;
std::unique_ptr<ParallelScheduler> _scheduler;
};
} // namespace exec
} // namespace onert
#endif // __ONERT_EXEC_PARALLEL_EXECUTOR_H__
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