| /* |
| * Copyright (c) 2017-2021 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, |
| bool align_corners, bool mixed_layout) |
| { |
| _shape = shape; |
| _policy = policy; |
| _border_mode = border_mode; |
| _sampling_policy = sampling_policy; |
| _data_type = data_type; |
| _quantization_info = quantization_info; |
| _align_corners = align_corners; |
| _mixed_layout = mixed_layout; |
| |
| generate_scale(shape); |
| |
| std::mt19937 generator(library->seed()); |
| std::uniform_int_distribution<uint8_t> distribution_u8(0, 255); |
| _constant_border_value = static_cast<T>(distribution_u8(generator)); |
| |
| _target = compute_target(shape, data_layout); |
| _reference = compute_reference(shape); |
| } |
| |
| protected: |
| void mix_layout(FunctionType &layer, TensorType &src, TensorType &dst) |
| { |
| const DataLayout data_layout = src.info()->data_layout(); |
| // Test Multi DataLayout graph cases, when the data layout changes after configure |
| src.info()->set_data_layout(data_layout == DataLayout::NCHW ? DataLayout::NHWC : DataLayout::NCHW); |
| dst.info()->set_data_layout(data_layout == DataLayout::NCHW ? DataLayout::NHWC : DataLayout::NCHW); |
| |
| // Compute Convolution function |
| layer.run(); |
| |
| // Reinstating original data layout for the test suite to properly check the values |
| src.info()->set_data_layout(data_layout); |
| dst.info()->set_data_layout(data_layout); |
| } |
| |
| void generate_scale(const TensorShape &shape) |
| { |
| static constexpr float _min_scale{ 0.25f }; |
| static constexpr float _max_scale{ 3.f }; |
| |
| constexpr float max_width{ 8192.0f }; |
| constexpr float max_height{ 6384.0f }; |
| const float min_width{ 1.f }; |
| const float min_height{ 1.f }; |
| |
| std::mt19937 generator(library->seed()); |
| std::uniform_real_distribution<float> distribution_float(_min_scale, _max_scale); |
| |
| auto generate = [&](size_t input_size, float min_output, float max_output) -> float |
| { |
| const float generated_scale = distribution_float(generator); |
| const float output_size = utility::clamp(static_cast<float>(input_size) * generated_scale, min_output, max_output); |
| return output_size / input_size; |
| }; |
| |
| // Input shape is always given in NCHW layout. NHWC is dealt by permute in compute_target() |
| const int idx_width = get_data_layout_dimension_index(DataLayout::NCHW, DataLayoutDimension::WIDTH); |
| const int idx_height = get_data_layout_dimension_index(DataLayout::NCHW, DataLayoutDimension::HEIGHT); |
| |
| _scale_x = generate(shape[idx_width], min_width, max_width); |
| _scale_y = generate(shape[idx_height], min_height, max_height); |
| } |
| |
| template <typename U> |
| void fill(U &&tensor) |
| { |
| if(tensor.data_type() == DataType::F32) |
| { |
| std::uniform_real_distribution<float> distribution(-5.0f, 5.0f); |
| library->fill(tensor, distribution, 0); |
| } |
| else if(tensor.data_type() == DataType::F16) |
| { |
| arm_compute::utils::uniform_real_distribution_16bit<half> distribution{ -5.0f, 5.0f }; |
| library->fill(tensor, distribution, 0); |
| } |
| else if(is_data_type_quantized(tensor.data_type())) |
| { |
| std::uniform_int_distribution<> distribution(0, 100); |
| library->fill(tensor, distribution, 0); |
| } |
| else |
| { |
| library->fill_tensor_uniform(tensor, 0); |
| } |
| } |
| |
| TensorType compute_target(TensorShape shape, DataLayout data_layout) |
| { |
| // 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, /* apply_dim_correction = */ false); |
| shape_scaled.set(idx_height, shape[idx_height] * _scale_y, /* apply_dim_correction = */ false); |
| TensorType dst = create_tensor<TensorType>(shape_scaled, _data_type, 1, _quantization_info, data_layout); |
| |
| // Create and configure function |
| FunctionType scale; |
| |
| scale.configure(&src, &dst, ScaleKernelInfo{ _policy, _border_mode, _constant_border_value, _sampling_policy, /* use_padding */ false, _align_corners }); |
| |
| ARM_COMPUTE_ASSERT(src.info()->is_resizable()); |
| ARM_COMPUTE_ASSERT(dst.info()->is_resizable()); |
| |
| add_padding_x({ &src, &dst }, data_layout); |
| |
| // Allocate tensors |
| src.allocator()->allocate(); |
| dst.allocator()->allocate(); |
| ARM_COMPUTE_ASSERT(!src.info()->is_resizable()); |
| ARM_COMPUTE_ASSERT(!dst.info()->is_resizable()); |
| |
| // Fill tensors |
| fill(AccessorType(src)); |
| |
| if(_mixed_layout) |
| { |
| mix_layout(scale, src, dst); |
| } |
| else |
| { |
| // Compute function |
| scale.run(); |
| } |
| return dst; |
| } |
| |
| SimpleTensor<T> compute_reference(const TensorShape &shape) |
| { |
| // 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, /* ceil_policy_scale */ false, _align_corners); |
| } |
| |
| TensorType _target{}; |
| SimpleTensor<T> _reference{}; |
| TensorShape _shape{}; |
| InterpolationPolicy _policy{}; |
| BorderMode _border_mode{}; |
| T _constant_border_value{}; |
| SamplingPolicy _sampling_policy{}; |
| DataType _data_type{}; |
| QuantizationInfo _quantization_info{}; |
| bool _align_corners{ false }; |
| bool _mixed_layout{ false }; |
| float _scale_x{ 1.f }; |
| float _scale_y{ 1.f }; |
| }; |
| |
| template <typename TensorType, typename AccessorType, typename FunctionType, typename T, bool mixed_layout = false> |
| 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, |
| bool align_corners) |
| { |
| ScaleValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, |
| data_type, |
| quantization_info, |
| data_layout, |
| policy, |
| border_mode, |
| sampling_policy, |
| align_corners, |
| mixed_layout); |
| } |
| }; |
| template <typename TensorType, typename AccessorType, typename FunctionType, typename T, bool mixed_layout = false> |
| 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, bool align_corners) |
| { |
| ScaleValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, |
| data_type, |
| QuantizationInfo(), |
| data_layout, |
| policy, |
| border_mode, |
| sampling_policy, |
| align_corners, |
| mixed_layout); |
| } |
| }; |
| } // namespace validation |
| } // namespace test |
| } // namespace arm_compute |
| #endif /* ARM_COMPUTE_TEST_SCALE_FIXTURE */ |