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/*
* Copyright (c) 2017-2020 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to
* deal in the Software without restriction, including without limitation the
* rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
* sell copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#include "DequantizationLayer.h"
#include "Permute.h"
namespace arm_compute
{
namespace test
{
namespace validation
{
namespace reference
{
namespace
{
template <typename TOut>
TOut dequantize(int8_t val, const UniformQuantizationInfo qinfo, DataType dt)
{
if(dt == DataType::QSYMM8 || dt == DataType::QSYMM8_PER_CHANNEL)
{
return static_cast<TOut>(dequantize_qsymm8(val, qinfo));
}
else
{
return static_cast<TOut>(dequantize_qasymm8_signed(val, qinfo));
}
}
template <typename TOut>
TOut dequantize(uint8_t val, const UniformQuantizationInfo qinfo, DataType dt)
{
ARM_COMPUTE_UNUSED(dt);
return static_cast<TOut>(dequantize_qasymm8(val, qinfo));
}
template <typename TOut>
TOut dequantize(int16_t val, const UniformQuantizationInfo qinfo, DataType dt)
{
ARM_COMPUTE_UNUSED(dt);
return static_cast<TOut>(dequantize_qsymm16(val, qinfo));
}
} // namespace
template <typename TOut, typename TIn>
SimpleTensor<TOut> dequantization_layer(const SimpleTensor<TIn> &src)
{
const DataType src_data_type = src.data_type();
const DataType dst_data_type = std::is_same<TOut, float>::value ? DataType::F32 : DataType::F16;
SimpleTensor<TOut> dst{ src.shape(), dst_data_type };
if(is_data_type_quantized_per_channel(src_data_type))
{
const int WH = src.shape().x() * src.shape().y();
const int C = src.shape().z();
const int N = src.shape().total_size() / (WH * C);
const std::vector<float> qscales = src.quantization_info().scale();
#if defined(_OPENMP)
#pragma omp parallel for collapse(2)
#endif /* _OPENMP */
for(int n = 0; n < N; ++n)
{
for(int c = 0; c < C; ++c)
{
const size_t idx = n * C * WH + c * WH;
const UniformQuantizationInfo channel_qinfo = { qscales[c], 0 };
// Dequantize slice
for(int s = 0; s < WH; ++s)
{
dst[idx + s] = dequantize<TOut>(static_cast<TIn>(src[idx + s]), channel_qinfo, src_data_type);
}
}
}
}
else
{
const UniformQuantizationInfo &quantization_info = src.quantization_info().uniform();
ARM_COMPUTE_ERROR_ON(quantization_info.offset != 0 && src_data_type == DataType::QSYMM8);
#if defined(_OPENMP)
#pragma omp parallel for
#endif /* _OPENMP */
for(int i = 0; i < src.num_elements(); ++i)
{
dst[i] = static_cast<TOut>(dequantize<TOut>(static_cast<TIn>(src[i]), quantization_info, src_data_type));
}
}
return dst;
}
template SimpleTensor<half> dequantization_layer(const SimpleTensor<uint8_t> &src);
template SimpleTensor<float> dequantization_layer(const SimpleTensor<uint8_t> &src);
template SimpleTensor<half> dequantization_layer(const SimpleTensor<int8_t> &src);
template SimpleTensor<float> dequantization_layer(const SimpleTensor<int8_t> &src);
template SimpleTensor<half> dequantization_layer(const SimpleTensor<int16_t> &src);
template SimpleTensor<float> dequantization_layer(const SimpleTensor<int16_t> &src);
} // namespace reference
} // namespace validation
} // namespace test
} // namespace arm_compute
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