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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"
namespace neurun
{
namespace backend
{
namespace cpu
{
TensorBuilder::TensorBuilder()
{
// DO NOTHING
}
void TensorBuilder::mark(const ::neurun::graph::operand::Index &ind)
{
assert(_tensors.size() == 0);
_inds.insert(ind);
}
void TensorBuilder::prepare(codegen::Plan &plan,
const std::map<int, ::arm_compute::TensorInfo> &tensor_info_ctx)
{
assert(_tensors.size() == 0);
for (auto ind_int : _inds)
{
::neurun::graph::operand::Index ind{ind_int};
auto tensor = std::make_shared<operand::Tensor>(tensor_info_ctx.at(ind.asInt()));
// TODO Fix allocation here. When Tensor object is created the memory for tensor is also
// allocated, and this must be fixed.
plan.operands().set(ind, std::make_shared<operand::Object>(tensor));
_tensors[ind] = tensor;
}
}
void TensorBuilder::allocate(void)
{
assert(_inds.size() == _tensors.size());
// NOTE For now nothing to do. Allocation is done in prepare stage, which is wrong
// See also: comment in `prepare()`
}
std::shared_ptr<operand::Tensor> TensorBuilder::at(const ::neurun::graph::operand::Index &ind)
{
return _tensors.at(ind);
}
} // namespace cpu
} // namespace backend
} // namespace neurun
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