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Diffstat (limited to 'tests/validation/CPP/BatchNormalizationLayer.cpp')
| -rw-r--r-- | tests/validation/CPP/BatchNormalizationLayer.cpp | 125 |
1 files changed, 0 insertions, 125 deletions
diff --git a/tests/validation/CPP/BatchNormalizationLayer.cpp b/tests/validation/CPP/BatchNormalizationLayer.cpp deleted file mode 100644 index e4446d1694..0000000000 --- a/tests/validation/CPP/BatchNormalizationLayer.cpp +++ /dev/null @@ -1,125 +0,0 @@ -/* - * 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 |