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Diffstat (limited to 'tests/validation/fixtures/dynamic_fusion/gpu/cl/ElementwiseBinaryFixture.h')
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diff --git a/tests/validation/fixtures/dynamic_fusion/gpu/cl/ElementwiseBinaryFixture.h b/tests/validation/fixtures/dynamic_fusion/gpu/cl/ElementwiseBinaryFixture.h new file mode 100644 index 0000000000..d11237748f --- /dev/null +++ b/tests/validation/fixtures/dynamic_fusion/gpu/cl/ElementwiseBinaryFixture.h @@ -0,0 +1,284 @@ +/* + * Copyright (c) 2022 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 TESTS_VALIDATION_FIXTURES_DYNAMIC_FUSION_GPU_CL_ELEMENTWISEBINARYFIXTURE +#define TESTS_VALIDATION_FIXTURES_DYNAMIC_FUSION_GPU_CL_ELEMENTWISEBINARYFIXTURE + +#include "arm_compute/core/CL/CLKernelLibrary.h" +#include "arm_compute/core/TensorInfo.h" +#include "arm_compute/core/Types.h" +#include "arm_compute/dynamic_fusion/runtime/gpu/cl/ClWorkloadRuntime.h" +#include "arm_compute/dynamic_fusion/sketch/gpu/GpuWorkloadSketch.h" + +#include "tests/CL/CLAccessor.h" +#include "tests/framework/Fixture.h" +#include "tests/framework/Macros.h" +#include "tests/validation/Validation.h" +#include "tests/validation/reference/ElementwiseOperations.h" +#include "tests/validation/reference/Permute.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 DynamicFusionGpuElementwiseBinaryValidationGenericFixture : public framework::Fixture +{ +public: + template <typename...> + void setup(ArithmeticOperation op, TensorShape shape0, TensorShape shape1, TensorShape shape2, const DataType data_type, const bool is_inplace) + { + _op = op; + _is_inplace = is_inplace; + _data_type = data_type; + _fuse = shape2.total_size() != 0; + ARM_COMPUTE_ERROR_ON_MSG(_fuse && _is_inplace, "In place for fusing case not supported yet."); + _target = compute_target(shape0, shape1, shape2); + _reference = compute_reference(shape0, shape1, shape2); + } + +protected: + template <typename U> + void fill(U &&tensor, int i) + { + if(is_data_type_float(tensor.data_type())) + { + switch(_op) + { + case ArithmeticOperation::DIV: + library->fill_tensor_uniform_ranged(tensor, i, { std::pair<float, float>(-0.001f, 0.001f) }); + break; + case ArithmeticOperation::POWER: + library->fill_tensor_uniform(tensor, i, 0.0f, 5.0f); + break; + default: + library->fill_tensor_uniform(tensor, i); + } + } + else if(tensor.data_type() == DataType::S32) + { + switch(_op) + { + case ArithmeticOperation::DIV: + library->fill_tensor_uniform_ranged(tensor, i, { std::pair<int32_t, int32_t>(-1U, 1U) }); + break; + default: + library->fill_tensor_uniform(tensor, i); + } + } + else + { + library->fill_tensor_uniform(tensor, i); + } + } + + TensorType compute_target(TensorShape shape0, TensorShape shape1, TensorShape shape2) + { + // 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 }; + TensorInfo dst_info{}; + TensorInfo dst_info_fuse{}; + + // Fuse first element wise binary Op + auto lhs_info = sketch.create_tensor_info(shape0, 1, _data_type); + auto rhs_info = sketch.create_tensor_info(TensorInfo(shape1, 1, _data_type)); + TensorInfo rhs_info_fuse; + + // Testing root case while in-place + if(!_is_inplace) + { + dst_info = sketch.create_tensor_info(TensorInfo(1, _data_type)); + + FunctionType::create_op(sketch, &lhs_info, &rhs_info, &dst_info); + } + else + { + FunctionType::create_op(sketch, &lhs_info, &rhs_info, &lhs_info); + } + + if(_fuse) + { + // Fuse first element wise binary Op + rhs_info_fuse = sketch.create_tensor_info(TensorInfo(shape2, 1, _data_type)); + dst_info_fuse = sketch.create_tensor_info(); + FunctionType::create_op(sketch, &dst_info, &rhs_info_fuse, &dst_info_fuse); + } + + // Configure runtime + ClWorkloadRuntime runtime; + runtime.configure(sketch); + + // (Important) Allocate auxiliary tensor memory if there are any + for(auto &data : runtime.get_auxiliary_tensors()) + { + TensorType *tensor = data.first; + AuxMemoryInfo aux_mem_req = data.second; + tensor->allocator()->init(*data.first->info(), aux_mem_req.alignment); + tensor->allocator()->allocate(); + } + + // Construct user tensors + TensorType t_lhs{}; + TensorType t_rhs{}; + TensorType t_rhs_fuse{}; + TensorType t_dst{}; + TensorType t_dst_fuse{}; + + // Initialize user tensors + t_lhs.allocator()->init(lhs_info); + t_rhs.allocator()->init(rhs_info); + if(!_is_inplace) + { + t_dst.allocator()->init(dst_info); + if(_fuse) + { + t_rhs_fuse.allocator()->init(rhs_info_fuse); + t_dst_fuse.allocator()->init(dst_info_fuse); + } + } + + // Allocate and fill user tensors + // Instead of using ACL allocator, the user can choose to import memory into the tensors + t_lhs.allocator()->allocate(); + t_rhs.allocator()->allocate(); + if(!_is_inplace) + { + t_dst.allocator()->allocate(); + if(_fuse) + { + t_rhs_fuse.allocator()->allocate(); + t_dst_fuse.allocator()->allocate(); + } + } + + fill(AccessorType(t_lhs), 0); + fill(AccessorType(t_rhs), 1); + if(_fuse) + { + fill(AccessorType(t_rhs_fuse), 2); + } + // Run runtime + if(_is_inplace) + { + runtime.run({ &t_lhs, &t_rhs, &t_lhs }); + } + else + { + if(_fuse) + { + runtime.run({ &t_lhs, &t_rhs, &t_rhs_fuse, &t_dst_fuse }); + } + else + { + runtime.run({ &t_lhs, &t_rhs, &t_dst }); + } + } + + if(_is_inplace) + { + return t_lhs; + } + else if(_fuse) + { + return t_dst_fuse; + } + return t_dst; + } + + SimpleTensor<T> compute_reference(TensorShape shape0, TensorShape shape1, TensorShape shape2) + { + const TensorShape out_shape = TensorShape::broadcast_shape(shape0, shape1); + const TensorShape out_shape_fuse = TensorShape::broadcast_shape(out_shape, shape1); + + // Create reference + SimpleTensor<T> ref_lhs{ shape0, _data_type, 1, QuantizationInfo() }; + SimpleTensor<T> ref_rhs{ shape1, _data_type, 1, QuantizationInfo() }; + SimpleTensor<T> ref_rhs_fuse{ shape2, _data_type, 1, QuantizationInfo() }; + SimpleTensor<T> ref_dst{ out_shape, _data_type, 1, QuantizationInfo() }; + SimpleTensor<T> ref_dst_fuse{ out_shape_fuse, _data_type, 1, QuantizationInfo() }; + // Fill reference + fill(ref_lhs, 0); + fill(ref_rhs, 1); + + reference::arithmetic_operation<T>(_op, ref_lhs, ref_rhs, ref_dst, ConvertPolicy::WRAP); + if(_fuse) + { + fill(ref_rhs_fuse, 2); + reference::arithmetic_operation<T>(_op, ref_dst, ref_rhs_fuse, ref_dst_fuse, ConvertPolicy::WRAP); + } + SimpleTensor<T> *ret = _fuse ? &ref_dst_fuse : &ref_dst; + return *ret; + } + + ArithmeticOperation _op{ ArithmeticOperation::ADD }; + TensorType _target{}; + SimpleTensor<T> _reference{}; + DataType _data_type{}; + DataLayout _data_layout{}; + bool _is_inplace{ false }; + bool _fuse{ false }; +}; + +template <typename TensorType, typename AccessorType, typename FunctionType, typename T> +class DynamicFusionGpuElementwiseBinaryOneOpValidationFixture : public DynamicFusionGpuElementwiseBinaryValidationGenericFixture<TensorType, AccessorType, FunctionType, T> +{ +public: + template <typename...> + void setup(ArithmeticOperation op, TensorShape shape, const DataType data_type, const bool is_inplace) + { + DynamicFusionGpuElementwiseBinaryValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(op, shape, shape, TensorShape(), data_type, is_inplace); + } +}; + +template <typename TensorType, typename AccessorType, typename FunctionType, typename T> +class DynamicFusionGpuElementwiseBinaryBroadcastOneOpValidationFixture : public DynamicFusionGpuElementwiseBinaryValidationGenericFixture<TensorType, AccessorType, FunctionType, T> +{ +public: + template <typename...> + void setup(ArithmeticOperation op, TensorShape shape0, TensorShape shape1, const DataType data_type, const bool is_inplace) + { + DynamicFusionGpuElementwiseBinaryValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(op, shape0, shape1, TensorShape(), data_type, is_inplace); + } +}; + +template <typename TensorType, typename AccessorType, typename FunctionType, typename T> +class DynamicFusionGpuElementwiseBinaryTwoOpsValidationFixture : public DynamicFusionGpuElementwiseBinaryValidationGenericFixture<TensorType, AccessorType, FunctionType, T> +{ +public: + template <typename...> + void setup(ArithmeticOperation op, TensorShape shape0, TensorShape shape1, TensorShape shape2, const DataType data_type, const bool is_inplace) + { + DynamicFusionGpuElementwiseBinaryValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(op, shape0, shape1, shape2, data_type, is_inplace); + } +}; + +} // namespace validation +} // namespace test +} // namespace arm_compute +#endif /* TESTS_VALIDATION_FIXTURES_DYNAMIC_FUSION_GPU_CL_ELEMENTWISEBINARYFIXTURE */ |