| /* | |
| * Copyright (c) 2019, 2022 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 "MeanStdDevNormalizationLayer.h" | |
| #include "arm_compute/core/Types.h" | |
| namespace arm_compute | |
| { | |
| namespace test | |
| { | |
| namespace validation | |
| { | |
| namespace reference | |
| { | |
| template <typename T> | |
| SimpleTensor<T> mean_std_normalization_layer(const SimpleTensor<T> &src, float epsilon) | |
| { | |
| // Create reference | |
| SimpleTensor<T> dst{ src.shape(), src.data_type(), 1 }; | |
| const int cols = src.shape()[0]; | |
| const int batch_size = src.shape()[1]; | |
| for(int i = 0; i < batch_size; ++i) | |
| { | |
| T sum = static_cast<T>(0.f); | |
| T sum_sq = static_cast<T>(0.f); | |
| for(int j = 0; j < cols; ++j) | |
| { | |
| const T value = src[j + i * cols]; | |
| sum += value; | |
| sum_sq += value * value; | |
| } | |
| const T mean = sum / static_cast<T>(cols); | |
| const T var = ((sum_sq / static_cast<T>(cols)) - (mean * mean)) + static_cast<T>(epsilon); | |
| const T stddev_inv = static_cast<T>(1.f) / static_cast<T>(std::sqrt(var)); | |
| for(int j = 0; j < cols; ++j) | |
| { | |
| dst[j + i * cols] = (src[j + i * cols] - mean) * stddev_inv; | |
| } | |
| } | |
| return dst; | |
| } | |
| template <> | |
| SimpleTensor<uint8_t> mean_std_normalization_layer(const SimpleTensor<uint8_t> &src, float epsilon) | |
| { | |
| SimpleTensor<float> src_tmp = convert_from_asymmetric(src); | |
| SimpleTensor<float> dst_tmp = mean_std_normalization_layer<float>(src_tmp, epsilon); | |
| SimpleTensor<uint8_t> dst = convert_to_asymmetric<uint8_t>(dst_tmp, src.quantization_info()); | |
| return dst; | |
| } | |
| template SimpleTensor<float> mean_std_normalization_layer(const SimpleTensor<float> &src, float epsilon); | |
| template SimpleTensor<half> mean_std_normalization_layer(const SimpleTensor<half> &src, float epsilon); | |
| } // namespace reference | |
| } // namespace validation | |
| } // namespace test | |
| } // namespace arm_compute |