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/*
* Copyright (c) 2020 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 "BroadcastToLayer.h"
#include <cker/operation/BroadcastTo.h>
namespace onert
{
namespace backend
{
namespace cpu
{
namespace ops
{
BroadcastToLayer::BroadcastToLayer() : _input(nullptr), _shape(nullptr), _output(nullptr)
{
// DO NOTHING
}
void BroadcastToLayer::configure(const IPortableTensor *input, const IPortableTensor *shape,
IPortableTensor *output)
{
_input = input;
_shape = shape;
_output = output;
}
void BroadcastToLayer::run()
{
// NOTE : It was implemented follows tf.broadcast_to operation works and
// Api Document(https://www.tensorflow.org/api_docs/python/tf/broadcast_to)
switch (_output->data_type())
{
// ToDo : It need to support INT8 and UINT8 also when will be applied quantization.
case OperandType::FLOAT32:
nnfw::cker::BroadcastTo<float>(getShape(_input), reinterpret_cast<float *>(_input->buffer()),
getShape(_output), getBuffer<float>(_output));
break;
case OperandType::INT32:
nnfw::cker::BroadcastTo<int32_t>(getShape(_input),
reinterpret_cast<int32_t *>(_input->buffer()),
getShape(_output), getBuffer<int32_t>(_output));
break;
case OperandType::UINT32:
nnfw::cker::BroadcastTo<uint32_t>(getShape(_input),
reinterpret_cast<uint32_t *>(_input->buffer()),
getShape(_output), getBuffer<uint32_t>(_output));
break;
default:
throw std::runtime_error{"BroadcastToLayer: unsupported data type"};
}
}
} // namespace ops
} // namespace cpu
} // namespace backend
} // namespace onert
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