| /* |
| * 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_NORMALIZE_PLANAR_YUV_LAYER_FIXTURE |
| #define ARM_COMPUTE_TEST_NORMALIZE_PLANAR_YUV_LAYER_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/Helpers.h" |
| #include "tests/validation/reference/NormalizePlanarYUVLayer.h" |
| |
| namespace arm_compute |
| { |
| namespace test |
| { |
| namespace validation |
| { |
| template <typename TensorType, typename AccessorType, typename FunctionType, typename T> |
| class NormalizePlanarYUVLayerValidationGenericFixture : public framework::Fixture |
| { |
| public: |
| template <typename...> |
| void setup(TensorShape shape0, TensorShape shape1, DataType dt, DataLayout data_layout, QuantizationInfo quantization_info) |
| { |
| _data_type = dt; |
| _target = compute_target(shape0, shape1, dt, data_layout, quantization_info); |
| _reference = compute_reference(shape0, shape1, dt, quantization_info); |
| } |
| |
| protected: |
| template <typename U> |
| void fill(U &&src_tensor, U &&mean_tensor, U &&std_tensor) |
| { |
| using FloatDistributionType = typename std::conditional<std::is_same<T, half>::value, arm_compute::utils::uniform_real_distribution_16bit<T>, std::uniform_real_distribution<float>>::type; |
| |
| if(is_data_type_float(_data_type)) |
| { |
| const T min_bound = T(-1.f); |
| const T max_bound = T(1.f); |
| FloatDistributionType distribution(min_bound, max_bound); |
| FloatDistributionType distribution_std(T(0.1f), max_bound); |
| library->fill(src_tensor, distribution, 0); |
| library->fill(mean_tensor, distribution, 1); |
| library->fill(std_tensor, distribution_std, 2); |
| } |
| else if(is_data_type_quantized_asymmetric(_data_type)) |
| { |
| const QuantizationInfo quant_info = src_tensor.quantization_info(); |
| std::pair<int, int> bounds = get_quantized_bounds(quant_info, -1.f, 1.0f); |
| std::uniform_int_distribution<> distribution(bounds.first, bounds.second); |
| std::uniform_int_distribution<> distribution_std(quantize_qasymm8(0.1f, quant_info.uniform()), bounds.second); |
| library->fill(src_tensor, distribution, 0); |
| library->fill(mean_tensor, distribution, 1); |
| library->fill(std_tensor, distribution_std, 2); |
| } |
| } |
| |
| TensorType compute_target(TensorShape shape0, const TensorShape &shape1, DataType dt, DataLayout data_layout, QuantizationInfo quantization_info) |
| { |
| if(data_layout == DataLayout::NHWC) |
| { |
| permute(shape0, PermutationVector(2U, 0U, 1U)); |
| } |
| |
| // Create tensors |
| TensorType src = create_tensor<TensorType>(shape0, dt, 1, quantization_info, data_layout); |
| TensorType mean = create_tensor<TensorType>(shape1, dt, 1, quantization_info); |
| TensorType std = create_tensor<TensorType>(shape1, dt, 1, quantization_info); |
| TensorType dst; |
| |
| // Create and configure function |
| FunctionType norm; |
| norm.configure(&src, &dst, &mean, &std); |
| |
| ARM_COMPUTE_ASSERT(src.info()->is_resizable()); |
| ARM_COMPUTE_ASSERT(dst.info()->is_resizable()); |
| ARM_COMPUTE_ASSERT(mean.info()->is_resizable()); |
| ARM_COMPUTE_ASSERT(std.info()->is_resizable()); |
| |
| // Allocate tensors |
| src.allocator()->allocate(); |
| dst.allocator()->allocate(); |
| mean.allocator()->allocate(); |
| std.allocator()->allocate(); |
| |
| ARM_COMPUTE_ASSERT(!src.info()->is_resizable()); |
| ARM_COMPUTE_ASSERT(!dst.info()->is_resizable()); |
| ARM_COMPUTE_ASSERT(!mean.info()->is_resizable()); |
| ARM_COMPUTE_ASSERT(!std.info()->is_resizable()); |
| |
| // Fill tensors |
| fill(AccessorType(src), AccessorType(mean), AccessorType(std)); |
| |
| // Compute function |
| norm.run(); |
| |
| return dst; |
| } |
| |
| SimpleTensor<T> compute_reference(const TensorShape &shape0, const TensorShape &shape1, DataType dt, QuantizationInfo quantization_info) |
| { |
| // Create reference |
| SimpleTensor<T> ref_src{ shape0, dt, 1, quantization_info }; |
| SimpleTensor<T> ref_mean{ shape1, dt, 1, quantization_info }; |
| SimpleTensor<T> ref_std{ shape1, dt, 1, quantization_info }; |
| |
| // Fill reference |
| fill(ref_src, ref_mean, ref_std); |
| |
| return reference::normalize_planar_yuv_layer(ref_src, ref_mean, ref_std); |
| } |
| |
| TensorType _target{}; |
| SimpleTensor<T> _reference{}; |
| DataType _data_type{}; |
| }; |
| |
| template <typename TensorType, typename AccessorType, typename FunctionType, typename T> |
| class NormalizePlanarYUVLayerValidationFixture : public NormalizePlanarYUVLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T> |
| { |
| public: |
| template <typename...> |
| void setup(TensorShape shape0, TensorShape shape1, DataType dt, DataLayout data_layout) |
| { |
| NormalizePlanarYUVLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(shape0, shape1, dt, data_layout, QuantizationInfo()); |
| } |
| }; |
| |
| template <typename TensorType, typename AccessorType, typename FunctionType, typename T> |
| class NormalizePlanarYUVLayerValidationQuantizedFixture : public NormalizePlanarYUVLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T> |
| { |
| public: |
| template <typename...> |
| void setup(TensorShape shape0, TensorShape shape1, DataType dt, DataLayout data_layout, QuantizationInfo quantization_info) |
| { |
| NormalizePlanarYUVLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(shape0, shape1, dt, data_layout, quantization_info); |
| } |
| }; |
| } // namespace validation |
| } // namespace test |
| } // namespace arm_compute |
| #endif /* ARM_COMPUTE_TEST_NORMALIZE_PLANAR_YUV_LAYER_FIXTURE */ |