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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 "MinLayer.h"
#include "OperationUtils.h"
#include <cker/operation/MaxMin.h>
namespace onert
{
namespace backend
{
namespace cpu
{
namespace kernel
{
void MinLayer::minFloat32()
{
nnfw::cker::Min<float>(
convertTensorToCkerShape(_lhs), reinterpret_cast<const float *>(_lhs->buffer()),
convertTensorToCkerShape(_rhs), reinterpret_cast<const float *>(_rhs->buffer()),
convertTensorToCkerShape(_output), reinterpret_cast<float *>(_output->buffer()));
}
void MinLayer::minQuant8()
{
// TODO Check whether cker for quant8 min produces correct results
// nnfw::cker::Min<uint8_t>(
// convertTensorToCkerShape(_lhs), reinterpret_cast<const uint8_t*>(_lhs->buffer()),
// convertTensorToCkerShape(_rhs), reinterpret_cast<const uint8_t*>(_rhs->buffer()),
// convertTensorToCkerShape(_output), reinterpret_cast<uint8_t*>(_output->buffer()));
throw std::runtime_error("Min NYI for quantized");
}
void MinLayer::configure(const operand::Tensor *lhs, const operand::Tensor *rhs,
operand::Tensor *output)
{
assert(lhs != nullptr);
assert(rhs != nullptr);
assert(output != nullptr);
_lhs = lhs;
_rhs = rhs;
_output = output;
}
void MinLayer::run()
{
if (_lhs->data_type() == OperandType::FLOAT32)
{
minFloat32();
}
else if (_lhs->data_type() == OperandType::QUANT8_ASYMM)
{
minQuant8();
}
}
} // namespace kernel
} // namespace cpu
} // namespace backend
} // namespace onert
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