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Diffstat (limited to 'tests/validation_old/Helpers.h')
-rw-r--r-- | tests/validation_old/Helpers.h | 273 |
1 files changed, 0 insertions, 273 deletions
diff --git a/tests/validation_old/Helpers.h b/tests/validation_old/Helpers.h deleted file mode 100644 index e109edee2a..0000000000 --- a/tests/validation_old/Helpers.h +++ /dev/null @@ -1,273 +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. - */ -#ifndef __ARM_COMPUTE_TEST_VALIDATION_HELPERS_H__ -#define __ARM_COMPUTE_TEST_VALIDATION_HELPERS_H__ - -#include "arm_compute/core/Types.h" -#include "tests/Globals.h" -#include "tests/ILutAccessor.h" -#include "tests/Types.h" -#include "tests/validation_old/ValidationUserConfiguration.h" -#include "tests/validation_old/half.h" - -#include <array> -#include <cstring> -#include <random> -#include <type_traits> -#include <utility> -#include <vector> - -namespace arm_compute -{ -namespace test -{ -namespace validation -{ -/** Helper function to fill one or more tensors with the uniform distribution with int values. - * - * @param[in] dist Distribution to be used to get the values for the tensor. - * @param[in] seeds List of seeds to be used to fill each tensor. - * @param[in,out] tensor Tensor to be initialized with the values of the distribution. - * @param[in,out] other_tensors (Optional) One or more tensors to be filled. - * - */ -template <typename D, typename T, typename... Ts> -void fill_tensors(D &&dist, std::initializer_list<int> seeds, T &&tensor, Ts &&... other_tensors) -{ - const std::array < T, 1 + sizeof...(Ts) > tensors{ { std::forward<T>(tensor), std::forward<Ts>(other_tensors)... } }; - std::vector<int> vs(seeds); - ARM_COMPUTE_ERROR_ON(vs.size() != tensors.size()); - int k = 0; - for(auto tp : tensors) - { - library->fill(*tp, std::forward<D>(dist), vs[k++]); - } -} - -/** Helper function to get the testing range for each activation layer. - * - * @param[in] activation Activation function to test. - * @param[in] fixed_point_position (Optional) Number of bits for the fractional part. Defaults to 1. - * - * @return A pair containing the lower upper testing bounds for a given function. - */ -template <typename T> -inline std::pair<T, T> get_activation_layer_test_bounds(ActivationLayerInfo::ActivationFunction activation, int fixed_point_position = 1) -{ - bool is_float = std::is_same<T, float>::value; - is_float = is_float || std::is_same<T, half_float::half>::value; - - std::pair<T, T> bounds; - - // Set initial values - if(is_float) - { - bounds = std::make_pair(-255.f, 255.f); - } - else - { - bounds = std::make_pair(std::numeric_limits<T>::lowest(), std::numeric_limits<T>::max()); - } - - // Reduce testing ranges - switch(activation) - { - case ActivationLayerInfo::ActivationFunction::LOGISTIC: - case ActivationLayerInfo::ActivationFunction::SOFT_RELU: - // Reduce range as exponent overflows - if(is_float) - { - bounds.first = -40.f; - bounds.second = 40.f; - } - else - { - bounds.first = -(1 << (fixed_point_position)); - bounds.second = 1 << (fixed_point_position); - } - break; - case ActivationLayerInfo::ActivationFunction::TANH: - // Reduce range as exponent overflows - if(!is_float) - { - bounds.first = -(1 << (fixed_point_position)); - bounds.second = 1 << (fixed_point_position); - } - break; - case ActivationLayerInfo::ActivationFunction::SQRT: - // Reduce range as sqrt should take a non-negative number - bounds.first = (is_float) ? 0 : 1; - break; - default: - break; - } - return bounds; -} -/** Helper function to get the testing range for batch normalization layer. - * - * @param[in] fixed_point_position (Optional) Number of bits for the fractional part. Defaults to 1. - * - * @return A pair containing the lower upper testing bounds. - */ -template <typename T> -std::pair<T, T> get_batchnormalization_layer_test_bounds(int fixed_point_position = 1) -{ - bool is_float = std::is_floating_point<T>::value; - std::pair<T, T> bounds; - - // Set initial values - if(is_float) - { - bounds = std::make_pair(-1.f, 1.f); - } - else - { - bounds = std::make_pair(1, 1 << (fixed_point_position)); - } - - return bounds; -} - -/** Fill mask with the corresponding given pattern. - * - * @param[in,out] mask Mask to be filled according to pattern - * @param[in] cols Columns (width) of mask - * @param[in] rows Rows (height) of mask - * @param[in] pattern Pattern to fill the mask according to - */ -inline void fill_mask_from_pattern(uint8_t *mask, int cols, int rows, MatrixPattern pattern) -{ - unsigned int v = 0; - std::mt19937 gen(user_config.seed.get()); - std::bernoulli_distribution dist(0.5); - - for(int r = 0; r < rows; ++r) - { - for(int c = 0; c < cols; ++c, ++v) - { - uint8_t val = 0; - - switch(pattern) - { - case MatrixPattern::BOX: - val = 255; - break; - case MatrixPattern::CROSS: - val = ((r == (rows / 2)) || (c == (cols / 2))) ? 255 : 0; - break; - case MatrixPattern::DISK: - val = (((r - rows / 2.0f + 0.5f) * (r - rows / 2.0f + 0.5f)) / ((rows / 2.0f) * (rows / 2.0f)) + ((c - cols / 2.0f + 0.5f) * (c - cols / 2.0f + 0.5f)) / ((cols / 2.0f) * - (cols / 2.0f))) <= 1.0f ? 255 : 0; - break; - case MatrixPattern::OTHER: - val = (dist(gen) ? 0 : 255); - break; - default: - return; - } - - mask[v] = val; - } - } - - if(pattern == MatrixPattern::OTHER) - { - std::uniform_int_distribution<uint8_t> distribution_u8(0, ((cols * rows) - 1)); - mask[distribution_u8(gen)] = 255; - } -} - -/** Calculate output tensor shape give a vector of input tensor to concatenate - * - * @param[in] input_shapes Shapes of the tensors to concatenate across depth. - * - * @return The shape of output concatenated tensor. - */ -inline TensorShape calculate_depth_concatenate_shape(std::vector<TensorShape> input_shapes) -{ - TensorShape out_shape = input_shapes.at(0); - - unsigned int max_x = 0; - unsigned int max_y = 0; - unsigned int depth = 0; - - for(auto const &shape : input_shapes) - { - max_x = std::max<unsigned int>(shape.x(), max_x); - max_y = std::max<unsigned int>(shape.y(), max_y); - depth += shape.z(); - } - - out_shape.set(0, max_x); - out_shape.set(1, max_y); - out_shape.set(2, depth); - - return out_shape; -} - -/** Fill matrix random. - * - * @param[in,out] matrix Matrix - * @param[in] cols Columns (width) of matrix - * @param[in] rows Rows (height) of matrix - */ -template <std::size_t SIZE> -inline void fill_warp_matrix(std::array<float, SIZE> &matrix, int cols, int rows) -{ - std::mt19937 gen(user_config.seed.get()); - std::uniform_real_distribution<float> dist(-1, 1); - - for(int v = 0, r = 0; r < rows; ++r) - { - for(int c = 0; c < cols; ++c, ++v) - { - matrix[v] = dist(gen); - } - } - if(SIZE == 9) - { - matrix[(cols * rows) - 1] = 1; - } -} - -/** Helper function to fill the Lut random by a ILutAccessor. - * - * @param[in,out] table Accessor at the Lut. - * - */ -template <typename T> -void fill_lookuptable(T &&table) -{ - std::mt19937 generator(user_config.seed.get()); - std::uniform_int_distribution<typename T::value_type> distribution(std::numeric_limits<typename T::value_type>::min(), std::numeric_limits<typename T::value_type>::max()); - - for(int i = std::numeric_limits<typename T::value_type>::min(); i <= std::numeric_limits<typename T::value_type>::max(); i++) - { - table[i] = distribution(generator); - } -} -} // namespace validation -} // namespace test -} // namespace arm_compute -#endif /* __ARM_COMPUTE_TEST_VALIDATION_HELPERS_H__ */ |