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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.
*/
#include "MemoryManager.h"
#include <cassert>
#include "MemoryPlannerFactory.h"
#include <backend/operand/Object.h>
#include "util/logging.h"
#include "util/ConfigSource.h"
namespace neurun
{
namespace backend
{
namespace cpu
{
MemoryManager::MemoryManager() : _mem_planner{createMemoryPlanner()}
{
// DO NOTHING
}
IMemoryPlanner *MemoryManager::createMemoryPlanner()
{
auto planner_id = util::getConfigString(util::config::CPU_MEMORY_PLANNER);
return MemoryPlannerFactory::instance().create(planner_id);
}
void MemoryManager::buildTensor(const model::OperandIndex &ind, const model::OperandInfo &info)
{
auto tensor = std::make_shared<operand::Tensor>(info);
_tensors[ind] = tensor;
}
void MemoryManager::claimPlan(const model::OperandIndex &ind, uint32_t size)
{
_mem_planner->claim(ind, size);
}
void MemoryManager::releasePlan(const model::OperandIndex &ind) { _mem_planner->release(ind); }
void MemoryManager::allocate(void)
{
_mem_alloc = std::make_shared<Allocator>(_mem_planner->capacity());
assert(_mem_alloc->base());
for (auto &mem_plan : _mem_planner->memory_plans())
{
auto ind = mem_plan.first;
auto mem_blk = mem_plan.second;
uint8_t *buffer = _mem_alloc->base() + mem_blk.offset;
auto tensor = _tensors[ind];
tensor->setBuffer(buffer);
VERBOSE(CPU_MEMORYMANAGER) << "TENSOR(#" << ind.value() << "): " << static_cast<void *>(buffer)
<< std::endl;
// If we do not make tensor here currently, kernel generation would cause segmentation fault.
// See also : Comments in `allocate` method.
}
}
std::shared_ptr<backend::operand::IObject> MemoryManager::wrapTensor(const model::OperandIndex &ind)
{
if (_objects.find(ind) != _objects.end())
{
return _objects.at(ind);
}
else
{
return _objects[ind] = std::make_shared<::neurun::backend::operand::Object>(_tensors.at(ind));
}
}
} // namespace cpu
} // namespace backend
} // namespace neurun
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