95 lines
3.3 KiB
C++
95 lines
3.3 KiB
C++
/*
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* Copyright (c) 2019-2020 Arm Limited.
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*
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* SPDX-License-Identifier: MIT
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*
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* Permission is hereby granted, free of charge, to any person obtaining a copy
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* of this software and associated documentation files (the "Software"), to
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* deal in the Software without restriction, including without limitation the
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* rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
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* sell copies of the Software, and to permit persons to whom the Software is
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* furnished to do so, subject to the following conditions:
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*
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* The above copyright notice and this permission notice shall be included in all
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* copies or substantial portions of the Software.
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*
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* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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* SOFTWARE.
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*/
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#include "InstanceNormalizationLayer.h"
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#include "tests/validation/Helpers.h"
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#include <algorithm>
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#include <cmath>
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namespace arm_compute
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{
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namespace test
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{
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namespace validation
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{
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namespace reference
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{
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template <typename T>
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SimpleTensor<T> instance_normalization(const SimpleTensor<T> &src, float gamma, float beta, float epsilon)
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{
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SimpleTensor<T> dst{ src.shape(), src.data_type() };
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//NCHW
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const size_t w_size = src.shape()[0];
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const size_t h_size = src.shape()[1];
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const size_t c_size = src.shape()[2];
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const size_t n_size = src.shape()[3];
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#if defined(_OPENMP)
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#pragma omp parallel for collapse(2)
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#endif /* _OPENMP */
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for(size_t n_i = 0; n_i < n_size; ++n_i)
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{
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for(size_t c_i = 0; c_i < c_size; ++c_i)
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{
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float sum_h_w = 0;
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float sum_sq_h_w = 0;
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for(size_t h_i = 0; h_i < h_size; ++h_i)
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{
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for(size_t w_i = 0; w_i < w_size; ++w_i)
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{
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float val = src[coord2index(src.shape(), Coordinates(w_i, h_i, c_i, n_i))];
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sum_h_w += val;
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sum_sq_h_w += val * val;
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}
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}
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//Compute mean
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const float mean_h_w = sum_h_w / (h_size * w_size);
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//Compute variance
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const float var_h_w = sum_sq_h_w / (h_size * w_size) - mean_h_w * mean_h_w;
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;
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//Apply mean
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for(size_t h_i = 0; h_i < h_size; ++h_i)
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{
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for(size_t w_i = 0; w_i < w_size; ++w_i)
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{
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//Compute output
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size_t index = coord2index(src.shape(), Coordinates(w_i, h_i, c_i, n_i));
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dst[index] = (src[index] - mean_h_w) * gamma / std::sqrt(var_h_w + epsilon) + beta;
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}
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}
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}
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}
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return dst;
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}
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template SimpleTensor<float> instance_normalization(const SimpleTensor<float> &src, float gamma, float beta, float epsilon);
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template SimpleTensor<half> instance_normalization(const SimpleTensor<half> &src, float gamma, float beta, float epsilon);
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} // namespace reference
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} // namespace validation
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} // namespace test
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} // namespace arm_compute
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