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/*
* Copyright (c) 2017 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 "SoftmaxLayer.h"
#include "tests/validation/FixedPoint.h"
#include "tests/validation/half.h"
namespace arm_compute
{
namespace test
{
namespace validation
{
namespace reference
{
template <typename T, typename std::enable_if<is_floating_point<T>::value, int>::type>
SimpleTensor<T> softmax_layer(const SimpleTensor<T> &src)
{
// Create reference
SimpleTensor<T> dst{ src.shape(), src.data_type(), 1, src.fixed_point_position() };
// Compute reference
const int cols = src.shape()[0];
const int upper_dims = src.num_elements() / cols;
for(int r = 0; r < upper_dims; ++r)
{
const T *src_row_ptr = src.data() + r * cols;
T *dst_row_ptr = dst.data() + r * cols;
// Find max
const T max = *std::max_element(src_row_ptr, src_row_ptr + cols);
// Regularize
T sum(0.f);
std::transform(src_row_ptr, src_row_ptr + cols, dst_row_ptr, [&sum, max](T val)
{
const T res(std::exp(val - max));
sum += res;
return res;
});
// Normalize
std::transform(dst_row_ptr, dst_row_ptr + cols, dst_row_ptr, [sum](T val)
{
return val / sum;
});
}
return dst;
}
template <typename T, typename std::enable_if<std::is_integral<T>::value, int>::type>
SimpleTensor<T> softmax_layer(const SimpleTensor<T> &src)
{
using namespace fixed_point_arithmetic;
// Create reference
SimpleTensor<T> dst{ src.shape(), src.data_type(), 1, src.fixed_point_position() };
// Compute reference
const int cols = src.shape()[0];
const int upper_dims = src.num_elements() / cols;
for(int r = 0; r < upper_dims; ++r)
{
const T *src_row_ptr = src.data() + r * cols;
T *dst_row_ptr = dst.data() + r * cols;
// Find max
const fixed_point<T> max(*std::max_element(src_row_ptr, src_row_ptr + cols), src.fixed_point_position(), true);
// Regularize
using promoted_type = fixed_point_arithmetic::traits::promote_t<T>;
fixed_point<promoted_type> sum(0, src.fixed_point_position(), true);
std::transform(src_row_ptr, src_row_ptr + cols, dst_row_ptr, [&](T val)
{
const fixed_point<T> res = exp(fixed_point<T>(val, src.fixed_point_position(), true) - max);
sum = add(sum, fixed_point<promoted_type>(res.raw(), src.fixed_point_position(), true));
return res.raw();
});
// Normalize
fixed_point<T> saturated_sum(sum);
std::transform(dst_row_ptr, dst_row_ptr + cols, dst_row_ptr, [&](T val)
{
return div(fixed_point<T>(val, src.fixed_point_position(), true), saturated_sum).raw();
});
}
return dst;
}
template SimpleTensor<float> softmax_layer(const SimpleTensor<float> &src);
template SimpleTensor<half_float::half> softmax_layer(const SimpleTensor<half_float::half> &src);
template SimpleTensor<qint8_t> softmax_layer(const SimpleTensor<qint8_t> &src);
template SimpleTensor<qint16_t> softmax_layer(const SimpleTensor<qint16_t> &src);
} // namespace reference
} // namespace validation
} // namespace test
} // namespace arm_compute
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