| /* |
| * 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 "BatchNormalizationLayer.h" |
| |
| #include "tests/validation/FixedPoint.h" |
| #include "tests/validation/Helpers.h" |
| |
| namespace arm_compute |
| { |
| namespace test |
| { |
| namespace validation |
| { |
| namespace reference |
| { |
| // Batch Normalization Layer for fixed point type |
| template <typename T, typename std::enable_if<std::is_integral<T>::value, int>::type *> |
| SimpleTensor<T> batch_normalization_layer(const SimpleTensor<T> &src, const SimpleTensor<T> &mean, const SimpleTensor<T> &var, const SimpleTensor<T> &beta, const SimpleTensor<T> &gamma, float epsilon, |
| int fixed_point_position) |
| { |
| SimpleTensor<T> result(src.shape(), src.data_type()); |
| |
| const auto cols = static_cast<int>(src.shape()[0]); |
| const auto rows = static_cast<int>(src.shape()[1]); |
| const auto depth = static_cast<int>(src.shape()[2]); |
| const int upper_dims = src.shape().total_size() / (cols * rows * depth); |
| |
| for(int r = 0; r < upper_dims; ++r) |
| { |
| for(int i = 0; i < depth; ++i) |
| { |
| for(int k = 0; k < rows; ++k) |
| { |
| for(int l = 0; l < cols; ++l) |
| { |
| const int pos = l + k * cols + i * rows * cols + r * cols * rows * depth; |
| |
| fixed_point_arithmetic::fixed_point<T> src_qs(src[pos], fixed_point_position, true); |
| fixed_point_arithmetic::fixed_point<T> var_qs(var[i], fixed_point_position, true); |
| fixed_point_arithmetic::fixed_point<T> mean_qs(mean[i], fixed_point_position, true); |
| fixed_point_arithmetic::fixed_point<T> beta_qs(beta[i], fixed_point_position, true); |
| fixed_point_arithmetic::fixed_point<T> gamma_qs(gamma[i], fixed_point_position, true); |
| fixed_point_arithmetic::fixed_point<T> epsilon_qs(epsilon, fixed_point_position); |
| |
| auto denominator = fixed_point_arithmetic::inv_sqrt(var_qs + epsilon_qs); |
| auto numerator = src_qs - mean_qs; |
| auto x_bar = numerator * denominator; |
| x_bar = beta_qs + x_bar * gamma_qs; |
| result[pos] = x_bar.raw(); |
| } |
| } |
| } |
| } |
| |
| return result; |
| } |
| |
| // Batch Normalization Layer for floating point type |
| template <typename T, typename std::enable_if<is_floating_point<T>::value, int>::type *> |
| SimpleTensor<T> batch_normalization_layer(const SimpleTensor<T> &src, const SimpleTensor<T> &mean, const SimpleTensor<T> &var, const SimpleTensor<T> &beta, const SimpleTensor<T> &gamma, float epsilon, |
| int fixed_point_position) |
| { |
| ARM_COMPUTE_UNUSED(fixed_point_position); |
| |
| SimpleTensor<T> result(src.shape(), src.data_type()); |
| |
| const auto cols = static_cast<int>(src.shape()[0]); |
| const auto rows = static_cast<int>(src.shape()[1]); |
| const auto depth = static_cast<int>(src.shape()[2]); |
| const int upper_dims = src.shape().total_size() / (cols * rows * depth); |
| |
| for(int r = 0; r < upper_dims; ++r) |
| { |
| for(int i = 0; i < depth; ++i) |
| { |
| for(int k = 0; k < rows; ++k) |
| { |
| for(int l = 0; l < cols; ++l) |
| { |
| const int pos = l + k * cols + i * rows * cols + r * cols * rows * depth; |
| const float denominator = sqrt(var[i] + epsilon); |
| const float numerator = src[pos] - mean[i]; |
| const float x_bar = numerator / denominator; |
| result[pos] = beta[i] + x_bar * gamma[i]; |
| } |
| } |
| } |
| } |
| return result; |
| } |
| template SimpleTensor<float> batch_normalization_layer(const SimpleTensor<float> &src, const SimpleTensor<float> &mean, const SimpleTensor<float> &var, const SimpleTensor<float> &beta, |
| const SimpleTensor<float> &gamma, float epsilon, int fixed_point_position); |
| template SimpleTensor<int8_t> batch_normalization_layer(const SimpleTensor<int8_t> &src, const SimpleTensor<int8_t> &mean, const SimpleTensor<int8_t> &var, const SimpleTensor<int8_t> &beta, |
| const SimpleTensor<int8_t> &gamma, float epsilon, int fixed_point_position); |
| template SimpleTensor<int16_t> batch_normalization_layer(const SimpleTensor<int16_t> &src, const SimpleTensor<int16_t> &mean, const SimpleTensor<int16_t> &var, const SimpleTensor<int16_t> &beta, |
| const SimpleTensor<int16_t> &gamma, float epsilon, int fixed_point_position); |
| template SimpleTensor<half> batch_normalization_layer(const SimpleTensor<half> &src, const SimpleTensor<half> &mean, const SimpleTensor<half> &var, |
| const SimpleTensor<half> &beta, |
| const SimpleTensor<half> &gamma, float epsilon, int fixed_point_position); |
| |
| } // namespace reference |
| } // namespace validation |
| } // namespace test |
| } // namespace arm_compute |