| /* |
| * Copyright (c) 2023 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 |
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| * 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 |
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| * 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 TESTS_VALIDATION_FIXTURES_DYNAMIC_FUSION_GPU_CL_POOL2DFIXTURE |
| #define TESTS_VALIDATION_FIXTURES_DYNAMIC_FUSION_GPU_CL_POOL2DFIXTURE |
| |
| #include "arm_compute/core/CL/CLKernelLibrary.h" |
| #include "arm_compute/core/TensorInfo.h" |
| #include "arm_compute/core/Types.h" |
| #include "arm_compute/core/utils/misc/ShapeCalculator.h" |
| |
| #include "arm_compute/dynamic_fusion/runtime/gpu/cl/ClWorkloadRuntime.h" |
| #include "arm_compute/dynamic_fusion/sketch/attributes/Pool2dAttributes.h" |
| #include "arm_compute/dynamic_fusion/sketch/gpu/GpuWorkloadSketch.h" |
| #include "arm_compute/dynamic_fusion/sketch/gpu/operators/GpuPool2d.h" |
| #include "src/dynamic_fusion/utils/Utils.h" |
| |
| #include "tests/CL/CLAccessor.h" |
| #include "tests/framework/Fixture.h" |
| #include "tests/validation/reference/PoolingLayer.h" |
| |
| using namespace arm_compute::experimental::dynamic_fusion; |
| |
| namespace arm_compute |
| { |
| namespace test |
| { |
| namespace validation |
| { |
| template <typename TensorType, typename AccessorType, typename FunctionType, typename T> |
| class DynamicFusionGpuPool2dValidationGenericFixture : public framework::Fixture |
| { |
| public: |
| template <typename...> |
| void setup(TensorShape input_shape, const Pool2dAttributes &pool_attr, DataType data_type, bool mixed_precision) |
| { |
| _target = compute_target(input_shape, pool_attr, data_type, mixed_precision); |
| _reference = compute_reference(input_shape, convert_pool_attr_to_pool_info(pool_attr, mixed_precision), data_type); |
| } |
| |
| protected: |
| template <typename U> |
| void fill(U &&tensor, int i) |
| { |
| switch(tensor.data_type()) |
| { |
| case DataType::F16: |
| { |
| arm_compute::utils::uniform_real_distribution_16bit<half> distribution{ -1.0f, 1.0f }; |
| library->fill(tensor, distribution, i); |
| break; |
| } |
| case DataType::F32: |
| { |
| std::uniform_real_distribution<float> distribution(-1.0f, 1.0f); |
| library->fill(tensor, distribution, i); |
| break; |
| } |
| default: |
| library->fill_tensor_uniform(tensor, i); |
| } |
| } |
| |
| // Given input is in nchw format |
| TensorType compute_target(TensorShape input_shape, const Pool2dAttributes &pool_attr, const DataType data_type, bool mixed_precision) |
| { |
| CLScheduler::get().default_reinit(); |
| |
| // Change shape due to NHWC data layout, test shapes are NCHW |
| permute(input_shape, PermutationVector(2U, 0U, 1U)); |
| |
| // Create a new workload sketch |
| auto cl_compile_ctx = CLKernelLibrary::get().get_compile_context(); |
| auto gpu_ctx = GpuWorkloadContext{ &cl_compile_ctx }; |
| GpuWorkloadSketch sketch{ &gpu_ctx }; |
| |
| // Create sketch tensors |
| auto input_info = sketch.create_tensor_info(TensorInfo(input_shape, 1, data_type, DataLayout::NHWC)); |
| auto dst_info = sketch.create_tensor_info(); |
| |
| // Create Pool2dSettings |
| GpuPool2dSettings pool_settings = GpuPool2dSettings().mixed_precision(mixed_precision); |
| |
| FunctionType::create_op(sketch, &input_info, &dst_info, pool_attr, pool_settings); |
| |
| // Configure runtime |
| ClWorkloadRuntime runtime; |
| runtime.configure(sketch); |
| // (Important) Allocate auxiliary tensor memory if there are any |
| for(auto &data : runtime.get_auxiliary_tensors()) |
| { |
| auto tensor = data.first; |
| const auto aux_mem_req = data.second; |
| tensor->allocator()->init(*data.first->info(), aux_mem_req.alignment); |
| tensor->allocator()->allocate(); // Use ACL allocated memory |
| } |
| // Construct user tensors |
| TensorType t_input{}; |
| TensorType t_dst{}; |
| |
| // Initialize user tensors |
| t_input.allocator()->init(input_info); |
| t_dst.allocator()->init(dst_info); |
| |
| // Allocate and fill user tensors |
| t_input.allocator()->allocate(); |
| t_dst.allocator()->allocate(); |
| |
| fill(AccessorType(t_input), 0); |
| |
| // Run runtime |
| runtime.run({ &t_input, &t_dst }); |
| return t_dst; |
| } |
| |
| SimpleTensor<T> compute_reference(TensorShape shape, PoolingLayerInfo pool_info, DataType data_type) |
| { |
| // Create reference |
| SimpleTensor<T> src(shape, data_type, 1, QuantizationInfo()); |
| // Fill reference |
| fill(src, 0); |
| return reference::pooling_layer<T>(src, pool_info, QuantizationInfo(), nullptr, DataLayout::NCHW); |
| } |
| |
| TensorType _target{}; |
| SimpleTensor<T> _reference{}; |
| }; |
| |
| template <typename TensorType, typename AccessorType, typename FunctionType, typename T> |
| class DynamicFusionGpuPool2dValidationFixture : public DynamicFusionGpuPool2dValidationGenericFixture<TensorType, AccessorType, FunctionType, T> |
| { |
| public: |
| template <typename...> |
| void setup(TensorShape input_shape, PoolingType pool_type, Size2D pool_size, Padding2D pad, Size2D stride, bool exclude_padding, DataType data_type) |
| { |
| DynamicFusionGpuPool2dValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, |
| Pool2dAttributes().pool_type(pool_type).pool_size(pool_size).pad(pad).stride(stride).exclude_padding(exclude_padding), |
| data_type, false); |
| } |
| }; |
| |
| template <typename TensorType, typename AccessorType, typename FunctionType, typename T> |
| class DynamicFusionGpuPool2dMixedPrecisionValidationFixture : public DynamicFusionGpuPool2dValidationGenericFixture<TensorType, AccessorType, FunctionType, T> |
| { |
| public: |
| template <typename...> |
| void setup(TensorShape input_shape, PoolingType pool_type, Size2D pool_size, Padding2D pad, Size2D stride, bool exclude_padding, DataType data_type, bool mixed_precision) |
| { |
| DynamicFusionGpuPool2dValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, |
| Pool2dAttributes().pool_type(pool_type).pool_size(pool_size).pad(pad).stride(stride).exclude_padding(exclude_padding), |
| data_type, mixed_precision); |
| } |
| }; |
| |
| template <typename TensorType, typename AccessorType, typename FunctionType, typename T> |
| class DynamicFusionGpuPool2dSpecialValidationFixture : public DynamicFusionGpuPool2dValidationGenericFixture<TensorType, AccessorType, FunctionType, T> |
| { |
| public: |
| template <typename...> |
| void setup(TensorShape input_shape, Pool2dAttributes pool_attr, DataType data_type) |
| { |
| DynamicFusionGpuPool2dValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(input_shape, pool_attr, data_type, false); |
| } |
| }; |
| |
| } // namespace validation |
| } // namespace test |
| } // namespace arm_compute |
| |
| #endif /* TESTS_VALIDATION_FIXTURES_DYNAMIC_FUSION_GPU_CL_POOL2DFIXTURE */ |