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Diffstat (limited to 'tests/validation_old/Helpers.h')
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1 files changed, 273 insertions, 0 deletions
diff --git a/tests/validation_old/Helpers.h b/tests/validation_old/Helpers.h new file mode 100644 index 0000000000..e109edee2a --- /dev/null +++ b/tests/validation_old/Helpers.h @@ -0,0 +1,273 @@ +/* + * 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__ */ |