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diff --git a/tests/validation/fixtures/ConvolutionFixture.h b/tests/validation/fixtures/ConvolutionFixture.h
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--- a/tests/validation/fixtures/ConvolutionFixture.h
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-/*
- * Copyright (c) 2017-2020 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_CONVOLUTION_FIXTURE
-#define ARM_COMPUTE_TEST_CONVOLUTION_FIXTURE
-
-#include "arm_compute/core/TensorShape.h"
-#include "arm_compute/core/Types.h"
-#include "tests/AssetsLibrary.h"
-#include "tests/Globals.h"
-#include "tests/IAccessor.h"
-#include "tests/framework/Asserts.h"
-#include "tests/framework/Fixture.h"
-#include "tests/validation/reference/Convolution.h"
-
-#include <random>
-
-namespace arm_compute
-{
-namespace test
-{
-namespace validation
-{
-template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
-class ConvolutionValidationFixture : public framework::Fixture
-{
-protected:
- template <typename...>
- void setup(TensorShape shape, DataType output_data_type, BorderMode border_mode, const unsigned int width, const unsigned int height, const bool is_separable = false)
- {
- std::mt19937 gen(library->seed());
- std::uniform_int_distribution<uint8_t> distribution(0, 255);
- std::uniform_int_distribution<uint8_t> scale_distribution(1, 255);
- const uint8_t constant_border_value = distribution(gen);
-
- // Generate random scale value between 1 and 255.
- const uint32_t scale = scale_distribution(gen);
-
- ARM_COMPUTE_ERROR_ON(3 != width && 5 != width && 7 != width && 9 != width);
- ARM_COMPUTE_ERROR_ON(3 != height && 5 != height && 7 != height && 9 != height);
-
- std::vector<int16_t> conv(width * height);
-
- _width = width;
- _height = height;
-
- if(is_separable)
- {
- init_separable_conv(conv.data(), width, height, library->seed());
- }
- else
- {
- init_conv(conv.data(), width, height, library->seed());
- }
-
- _target = compute_target(shape, output_data_type, conv.data(), scale, border_mode, constant_border_value);
- _reference = compute_reference(shape, output_data_type, conv.data(), scale, border_mode, constant_border_value);
- }
-
- template <typename U>
- void fill(U &&tensor, int i)
- {
- library->fill_tensor_uniform(tensor, i);
- }
-
- SimpleTensor<T> compute_reference(const TensorShape &shape, DataType output_data_type, const int16_t *conv, uint32_t scale, BorderMode border_mode, uint8_t constant_border_value)
- {
- // Create reference
- SimpleTensor<uint8_t> src{ shape, DataType::U8 };
-
- // Fill reference
- fill(src, 0);
-
- // Compute reference
- return reference::convolution<T>(src, output_data_type, conv, scale, border_mode, constant_border_value, _width, _height);
- }
-
- virtual TensorType compute_target(const TensorShape &shape, DataType output_data_type, const int16_t *conv, uint32_t scale, BorderMode border_mode, uint8_t constant_border_value) = 0;
-
- BorderMode _border_mode{};
- TensorType _target{};
- SimpleTensor<T> _reference{};
- unsigned int _width{};
- unsigned int _height{};
-};
-
-template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
-class ConvolutionSquareValidationFixture : public ConvolutionValidationFixture<TensorType, AccessorType, FunctionType, T>
-{
-public:
- template <typename...>
- void setup(TensorShape shape, DataType output_data_type, BorderMode border_mode, const unsigned int width)
- {
- ConvolutionValidationFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, output_data_type, border_mode, width, width);
- }
-
-protected:
- TensorType compute_target(const TensorShape &shape, DataType output_data_type, const int16_t *conv, uint32_t scale, BorderMode border_mode, uint8_t constant_border_value)
- {
- // Create tensors
- TensorType src = create_tensor<TensorType>(shape, DataType::U8);
- TensorType dst = create_tensor<TensorType>(shape, output_data_type);
-
- // Create and configure function
- FunctionType convolution;
- convolution.configure(&src, &dst, conv, scale, border_mode, constant_border_value);
-
- ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
- ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);
-
- // Allocate tensors
- src.allocator()->allocate();
- dst.allocator()->allocate();
-
- ARM_COMPUTE_EXPECT(!src.info()->is_resizable(), framework::LogLevel::ERRORS);
- ARM_COMPUTE_EXPECT(!dst.info()->is_resizable(), framework::LogLevel::ERRORS);
-
- // Fill tensors
- this->fill(AccessorType(src), 0);
- this->fill(AccessorType(dst), 1);
-
- // Compute function
- convolution.run();
-
- return dst;
- }
-};
-
-template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
-class ConvolutionSeparableValidationFixture : public ConvolutionValidationFixture<TensorType, AccessorType, FunctionType, T>
-{
-public:
- template <typename...>
- void setup(TensorShape shape, DataType output_data_type, BorderMode border_mode, const unsigned int width)
- {
- ConvolutionValidationFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, output_data_type, border_mode, width, width, true);
- }
-
-protected:
- TensorType compute_target(const TensorShape &shape, DataType output_data_type, const int16_t *conv, uint32_t scale, BorderMode border_mode, uint8_t constant_border_value)
- {
- // Create tensors
- TensorType src = create_tensor<TensorType>(shape, DataType::U8);
- TensorType dst = create_tensor<TensorType>(shape, output_data_type);
-
- // Create and configure function
- FunctionType convolution;
- convolution.configure(&src, &dst, conv, scale, border_mode, constant_border_value);
-
- ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
- ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);
-
- // Allocate tensors
- src.allocator()->allocate();
- dst.allocator()->allocate();
-
- ARM_COMPUTE_EXPECT(!src.info()->is_resizable(), framework::LogLevel::ERRORS);
- ARM_COMPUTE_EXPECT(!dst.info()->is_resizable(), framework::LogLevel::ERRORS);
-
- // Fill tensors
- this->fill(AccessorType(src), 0);
- this->fill(AccessorType(dst), 1);
-
- // Compute function
- convolution.run();
-
- return dst;
- }
-};
-
-template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
-class ConvolutionRectangleValidationFixture : public ConvolutionValidationFixture<TensorType, AccessorType, FunctionType, T>
-{
-public:
- template <typename...>
- void setup(TensorShape shape, DataType output_data_type, BorderMode border_mode, const unsigned int width, const unsigned int height)
- {
- ConvolutionValidationFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, output_data_type, border_mode, width, height);
- }
-
-protected:
- TensorType compute_target(const TensorShape &shape, DataType output_data_type, const int16_t *conv, uint32_t scale, BorderMode border_mode, uint8_t constant_border_value)
- {
- // Create tensors
- TensorType src = create_tensor<TensorType>(shape, DataType::U8);
- TensorType dst = create_tensor<TensorType>(shape, output_data_type);
-
- // Create and configure function
- FunctionType convolution;
- convolution.configure(&src, &dst, conv, this->_width, this->_height, scale, border_mode, constant_border_value);
-
- ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
- ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);
-
- // Allocate tensors
- src.allocator()->allocate();
- dst.allocator()->allocate();
-
- ARM_COMPUTE_EXPECT(!src.info()->is_resizable(), framework::LogLevel::ERRORS);
- ARM_COMPUTE_EXPECT(!dst.info()->is_resizable(), framework::LogLevel::ERRORS);
-
- // Fill tensors
- this->fill(AccessorType(src), 0);
- this->fill(AccessorType(dst), 1);
-
- // Compute function
- convolution.run();
-
- return dst;
- }
-};
-} // namespace validation
-} // namespace test
-} // namespace arm_compute
-#endif /* ARM_COMPUTE_TEST_CONVOLUTION_FIXTURE */
generated by cgit v1.2.1 (git 2.23.0) at 2024-05-05 16:29:06 +0000