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-/*
- * 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__ */
generated by cgit v1.2.1 (git 2.23.0) at 2024-06-08 21:11:12 +0000