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/*
* Copyright (c) 2018 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 "TensorBuilder.h"
#include <cassert>
#include "operand/Object.h"
#include "util/logging.h"
namespace neurun
{
namespace backend
{
namespace cpu
{
TensorBuilder::TensorBuilder() : _mem_planner(std::make_shared<FirstFitPlanner>())
{
// DO NOTHING
}
void TensorBuilder::registerTensorInfo(const model::operand::Index &ind,
const compiler::TensorInfo &info)
{
_tensor_info_map.insert({ind, info});
}
void TensorBuilder::registerSubTensorInfo(const model::operand::Index &,
const compiler::SubTensorInfo &)
{
// Not supported yet
assert(false);
}
void TensorBuilder::notifyFirstUse(const model::operand::Index &ind)
{
assert(_tensor_info_map.find(ind) != _tensor_info_map.end());
const auto &info = _tensor_info_map.at(ind);
const auto size = info.total_size();
_mem_planner->claim(ind, size);
}
void TensorBuilder::notifyLastUse(const model::operand::Index &ind) { _mem_planner->release(ind); }
void TensorBuilder::prepare(void)
{
assert(_tensors.size() == 0);
_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;
const auto &info = _tensor_info_map[ind];
uint8_t *buffer = _mem_alloc->base() + mem_blk.offset;
auto tensor = std::make_shared<operand::Tensor>(info);
tensor->setBuffer(buffer);
_tensors[ind] = tensor;
VERBOSE(CPU_TENSORBUILDER) << "TENSOR(#" << ind.value() << "): " << static_cast<void *>(buffer)
<< std::endl;
// If we do not make tensor here currently, stages would cause segment fault
}
}
void TensorBuilder::allocate(void)
{
// NOTE For now nothing to do. Allocation is done in prepare stage, which is wrong
}
std::shared_ptr<::neurun::backend::operand::ITensor>
TensorBuilder::tensorAt(const model::operand::Index &ind)
{
return _tensors.at(ind);
}
std::shared_ptr<backend::operand::IObject>
TensorBuilder::wrapTensor(const model::operand::Index &ind)
{
if (_objects.find(ind) != _objects.end())
{
return _objects.at(ind);
}
else
{
return _objects[ind] = std::make_shared<operand::Object>(_tensors.at(ind));
}
}
void TensorBuilder::iterate(const IterateFunction &fn)
{
for (auto it : _tensors)
{
fn(it.first);
}
}
std::shared_ptr<operand::Tensor> TensorBuilder::at(const ::neurun::model::operand::Index &ind)
{
return _tensors.at(ind);
}
} // namespace cpu
} // namespace backend
} // namespace neurun
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