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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.
*/
/**
* @file ExecEnv.h
* @brief This file contains ExecEnv to access interpreter tensor and execution status
*/
#ifndef __NEURUN_EXEC_INTERP_EXEC_ENV_H_
#define __NEURUN_EXEC_INTERP_EXEC_ENV_H_
#include <unordered_set>
#include "ir/Graph.h"
#include "Tensor.h"
namespace neurun
{
namespace exec
{
namespace interp
{
/**
* @brief Class to gather interpreter execution environment
* Each interpreter instance own execution environment
*/
class ExecEnv
{
public:
/**
* @brief Construct a new Exec Env object (deleted)
*/
ExecEnv(void) = delete;
/**
* @brief Construct a new ExecEnv object
* @param[in] graph Graph to execute by interpreter
*/
explicit ExecEnv(const ir::Graph &graph) : _graph(graph)
{
// DO NOTHING
}
public:
/**
* @brief Return graph to execute
* @return Graph
*/
const ir::Graph &graph(void) const { return _graph; }
/**
* @brief Assign tensor to environment which have allocated or assigned buffer
* @param[in] index Tensor index
* @param[in] tensor Tensor
*/
void assignTensor(const ir::OperandIndex index, std::shared_ptr<ITensor> tensor)
{
assert(tensor->bufferRO() != nullptr);
_tensors.emplace(index, tensor);
}
/**
* @brief Return tensor pointer in environment
* @param[in] index Tensor index
* @return Tensor pointer
*/
const ITensor *tensorAt(const ir::OperandIndex index) const { return _tensors.at(index).get(); }
/**
* @brief Check environment contains tensor
* @param[in] index Tensor index
* @return @c true if environment contain tensor, otherwise @c false
*/
bool contains(const ir::OperandIndex index) const
{
return (_tensors.find(index) != _tensors.end());
}
/**
* @brief Allocate tensor using operand info
* @param[in] index Tensor index
* @param[in] info Operand info
* @note If already allocated, just return
* @TODO More smart allocation policy
*/
void allocateIfNeeded(const ir::OperandIndex index, const ir::OperandInfo &info)
{
// already allocated, or constant
if (contains(index))
{
return;
}
auto tensor = std::make_shared<Tensor>(info);
tensor->setBuffer(std::make_shared<InternalBuffer>(tensor->total_size()));
assignTensor(index, tensor);
_buffers.insert(index);
}
/**
* @brief Allocate read-only tensor and share data with other tensor
* @param[in] index Tensor index
* @param[in] info Operand info
* @param[in] index_to_share Tensor index that have data to share
*/
void allocateAndShareIfNeeded(const ir::OperandIndex index, const ir::OperandInfo &info,
const ir::OperandIndex index_to_share)
{
if (!contains(index_to_share))
{
throw std::runtime_error{"Cannot find tensor to share data"};
}
// already allocated
if (contains(index))
{
return;
}
else
{
auto tensor = std::make_shared<ROTensor>(info);
tensor->setData(tensorAt(index_to_share)->shareData());
assignTensor(index, tensor);
_buffers.insert(index);
}
}
/**
* @brief Free buffer if allocated by allocateIfNeed
* @param[in] index Tensor index
* @note If allocated by outside, just return
*/
void freeIfAllocated(const ir::OperandIndex index)
{
if (_buffers.find(index) != _buffers.end())
{
_tensors.at(index)->releaseData();
}
}
private:
const ir::Graph &_graph;
// Tensor map to use in interpreter
// It should map tensors that have allocated or assigned buffer pointer
std::unordered_map<ir::OperandIndex, std::shared_ptr<ITensor>> _tensors;
// Tensors allocated by allocateIfNeed (buffer)
std::unordered_set<ir::OperandIndex> _buffers;
};
} // namespace interp
} // namespace exec
} // namespace neurun
#endif // __NEURUN_EXEC_INTERP_EXEC_ENV_H_
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