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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 "LogSoftMaxLayer.h"
#include "OperationUtils.h"
#include <cker/operation/LogSoftMax.h>
namespace onert
{
namespace backend
{
namespace cpu
{
namespace ops
{
LogSoftMaxLayer::LogSoftMaxLayer() : _input(nullptr), _output(nullptr), _beta(0.0), _axis(0)
{
// DO NOTHING
}
void LogSoftMaxLayer::logsoftmaxFloat32()
{
nnfw::cker::SoftmaxParams op_params;
op_params.beta = _beta;
op_params.axis = _axis;
nnfw::cker::LogSoftmax(op_params, getTensorShape(_input),
reinterpret_cast<const float *>(_input->buffer()), getTensorShape(_output),
reinterpret_cast<float *>(_output->buffer()));
}
void LogSoftMaxLayer::logsoftmaxQuant8()
{
// NYI
}
void LogSoftMaxLayer::configure(const IPortableTensor *input, const float beta, const int axis,
IPortableTensor *output)
{
_input = input;
_output = output;
_beta = beta;
_axis = axis;
}
void LogSoftMaxLayer::run()
{
if (_input->data_type() == OperandType::FLOAT32)
{
logsoftmaxFloat32();
}
else if (_input->data_type() == OperandType::QUANT_UINT8_ASYMM)
{
throw std::runtime_error{"LogSoftmax : NYI"};
}
else
{
throw std::runtime_error{"LogSoftmax : unsupported data type"};
}
}
} // namespace ops
} // namespace cpu
} // namespace backend
} // namespace onert
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