| /* |
| * Copyright (c) 2017-2018 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_SCALE_FIXTURE |
| #define ARM_COMPUTE_TEST_SCALE_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/Permute.h" |
| #include "tests/validation/reference/Scale.h" |
| |
| namespace arm_compute |
| { |
| namespace test |
| { |
| namespace validation |
| { |
| template <typename TensorType, typename AccessorType, typename FunctionType, typename T> |
| class ScaleValidationGenericFixture : public framework::Fixture |
| { |
| public: |
| template <typename...> |
| void setup(TensorShape shape, DataType data_type, QuantizationInfo quantization_info, DataLayout data_layout, InterpolationPolicy policy, BorderMode border_mode, SamplingPolicy sampling_policy) |
| { |
| constexpr float max_width = 8192.0f; |
| constexpr float max_height = 6384.0f; |
| |
| _shape = shape; |
| _policy = policy; |
| _border_mode = border_mode; |
| _sampling_policy = sampling_policy; |
| _data_type = data_type; |
| _quantization_info = quantization_info; |
| |
| std::mt19937 generator(library->seed()); |
| std::uniform_real_distribution<float> distribution_float(0.25, 3); |
| float scale_x = distribution_float(generator); |
| float scale_y = distribution_float(generator); |
| |
| const int idx_width = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH); |
| const int idx_height = get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT); |
| |
| scale_x = ((shape[idx_width] * scale_x) > max_width) ? (max_width / shape[idx_width]) : scale_x; |
| scale_y = ((shape[idx_height] * scale_y) > max_height) ? (max_height / shape[idx_height]) : scale_y; |
| |
| std::uniform_int_distribution<uint8_t> distribution_u8(0, 255); |
| T constant_border_value = static_cast<T>(distribution_u8(generator)); |
| |
| _target = compute_target(shape, data_layout, scale_x, scale_y, policy, border_mode, constant_border_value, sampling_policy, quantization_info); |
| _reference = compute_reference(shape, scale_x, scale_y, policy, border_mode, constant_border_value, sampling_policy, quantization_info); |
| } |
| |
| protected: |
| template <typename U> |
| void fill(U &&tensor) |
| { |
| if(is_data_type_float(_data_type)) |
| { |
| library->fill_tensor_uniform(tensor, 0); |
| } |
| else if(is_data_type_quantized(tensor.data_type())) |
| { |
| std::uniform_int_distribution<> distribution(0, 100); |
| library->fill(tensor, distribution, 0); |
| } |
| else |
| { |
| // Restrict range for float to avoid any floating point issues |
| std::uniform_real_distribution<> distribution(-5.0f, 5.0f); |
| library->fill(tensor, distribution, 0); |
| } |
| } |
| |
| TensorType compute_target(TensorShape shape, DataLayout data_layout, const float scale_x, const float scale_y, |
| InterpolationPolicy policy, BorderMode border_mode, T constant_border_value, SamplingPolicy sampling_policy, |
| QuantizationInfo quantization_info) |
| { |
| // Change shape in case of NHWC. |
| if(data_layout == DataLayout::NHWC) |
| { |
| permute(shape, PermutationVector(2U, 0U, 1U)); |
| } |
| |
| // Create tensors |
| TensorType src = create_tensor<TensorType>(shape, _data_type, 1, quantization_info, data_layout); |
| |
| const int idx_width = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH); |
| const int idx_height = get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT); |
| |
| TensorShape shape_scaled(shape); |
| shape_scaled.set(idx_width, shape[idx_width] * scale_x); |
| shape_scaled.set(idx_height, shape[idx_height] * scale_y); |
| TensorType dst = create_tensor<TensorType>(shape_scaled, _data_type, 1, quantization_info, data_layout); |
| |
| // Create and configure function |
| FunctionType scale; |
| |
| scale.configure(&src, &dst, policy, border_mode, constant_border_value, sampling_policy); |
| |
| 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 |
| fill(AccessorType(src)); |
| |
| // Compute function |
| scale.run(); |
| |
| return dst; |
| } |
| |
| SimpleTensor<T> compute_reference(const TensorShape &shape, const float scale_x, const float scale_y, |
| InterpolationPolicy policy, BorderMode border_mode, T constant_border_value, SamplingPolicy sampling_policy, |
| QuantizationInfo quantization_info) |
| { |
| // Create reference |
| SimpleTensor<T> src{ shape, _data_type, 1, quantization_info }; |
| |
| // Fill reference |
| fill(src); |
| |
| return reference::scale<T>(src, scale_x, scale_y, policy, border_mode, constant_border_value, sampling_policy); |
| } |
| |
| TensorType _target{}; |
| SimpleTensor<T> _reference{}; |
| TensorShape _shape{}; |
| InterpolationPolicy _policy{}; |
| BorderMode _border_mode{}; |
| SamplingPolicy _sampling_policy{}; |
| DataType _data_type{}; |
| QuantizationInfo _quantization_info{}; |
| }; |
| |
| template <typename TensorType, typename AccessorType, typename FunctionType, typename T> |
| class ScaleValidationQuantizedFixture : public ScaleValidationGenericFixture<TensorType, AccessorType, FunctionType, T> |
| { |
| public: |
| template <typename...> |
| void setup(TensorShape shape, DataType data_type, QuantizationInfo quantization_info, DataLayout data_layout, InterpolationPolicy policy, BorderMode border_mode, SamplingPolicy sampling_policy) |
| { |
| ScaleValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, |
| data_type, |
| quantization_info, |
| data_layout, |
| policy, |
| border_mode, |
| sampling_policy); |
| } |
| }; |
| template <typename TensorType, typename AccessorType, typename FunctionType, typename T> |
| class ScaleValidationFixture : public ScaleValidationGenericFixture<TensorType, AccessorType, FunctionType, T> |
| { |
| public: |
| template <typename...> |
| void setup(TensorShape shape, DataType data_type, DataLayout data_layout, InterpolationPolicy policy, BorderMode border_mode, SamplingPolicy sampling_policy) |
| { |
| ScaleValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, |
| data_type, |
| QuantizationInfo(), |
| data_layout, |
| policy, |
| border_mode, |
| sampling_policy); |
| } |
| }; |
| } // namespace validation |
| } // namespace test |
| } // namespace arm_compute |
| #endif /* ARM_COMPUTE_TEST_SCALE_FIXTURE */ |