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Diffstat (limited to 'tests/validation/fixtures/dynamic_fusion/gpu/cl/ElementwiseBinaryFixture.h')
| -rw-r--r-- | tests/validation/fixtures/dynamic_fusion/gpu/cl/ElementwiseBinaryFixture.h | 273 |
1 files changed, 273 insertions, 0 deletions
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..69bd0efbdc --- /dev/null +++ b/tests/validation/fixtures/dynamic_fusion/gpu/cl/ElementwiseBinaryFixture.h @@ -0,0 +1,273 @@ +/* + * Copyright (c) 2022-2024 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 ACL_TESTS_VALIDATION_FIXTURES_DYNAMIC_FUSION_GPU_CL_ELEMENTWISEBINARYFIXTURE_H +#define ACL_TESTS_VALIDATION_FIXTURES_DYNAMIC_FUSION_GPU_CL_ELEMENTWISEBINARYFIXTURE_H + +#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 "arm_compute/dynamic_fusion/sketch/gpu/operators/GpuOutput.h" + +#include "tests/framework/Fixture.h" +#include "tests/framework/Macros.h" +#include "tests/validation/reference/ElementwiseOperations.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: + void setup(ArithmeticOperation ref_op, + const TensorShape &shape0, + const TensorShape &shape1, + const TensorShape &shape2, + DataType data_type, + bool is_inplace, + bool fuse_two_ops = false) + { + _ref_op = ref_op; + _is_inplace = is_inplace; + _data_type = data_type; + _fuse = fuse_two_ops; + ARM_COMPUTE_ERROR_ON_MSG(_fuse && shape2.total_size() == 0, "No shape2 provided for fusion of two ops."); + 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 (_ref_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 (_ref_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(const TensorShape &shape0, const TensorShape &shape1, const TensorShape &shape2) + { + // Create a new workload sketch + auto cl_compile_ctx = CLKernelLibrary::get().get_compile_context(); + auto context = GpuWorkloadContext{&cl_compile_ctx}; + GpuWorkloadSketch sketch{&context}; + + // Fuse first element wise binary Op + ITensorInfo *lhs_info = context.create_tensor_info(TensorInfo(shape0, 1, _data_type)); + ITensorInfo *rhs_info = context.create_tensor_info(TensorInfo(shape1, 1, _data_type)); + ITensorInfo *dst_info = context.create_tensor_info(); + + ITensorInfo *rhs_info_fuse = nullptr; + + ITensorInfo *ans_info = FunctionType::create_op(sketch, lhs_info, rhs_info); + + if (_fuse) + { + rhs_info_fuse = context.create_tensor_info(TensorInfo(shape2, 1, _data_type)); + ITensorInfo *ans2_info = FunctionType::create_op(sketch, ans_info, rhs_info_fuse); + GpuOutput::create_op(sketch, ans2_info, dst_info); + } + else + { + GpuOutput::create_op(sketch, ans_info, dst_info); + } + + // Configure runtime + ClWorkloadRuntime runtime; + runtime.configure(sketch); + + // (Important) Allocate auxiliary tensor memory if there are any + for (auto &data : runtime.get_auxiliary_tensors()) + { + CLTensor *tensor = std::get<0>(data); + TensorInfo info = std::get<1>(data); + AuxMemoryInfo aux_mem_req = std::get<2>(data); + tensor->allocator()->init(info, aux_mem_req.alignment); + tensor->allocator()->allocate(); // Use ACL allocated memory + } + + // Construct user tensors + TensorType t_lhs{}; + TensorType t_rhs{}; + TensorType t_rhs_fuse{}; + TensorType t_dst{}; + + // Initialize user tensors + t_lhs.allocator()->init(*lhs_info); + t_rhs.allocator()->init(*rhs_info); + t_dst.allocator()->init(*dst_info); + if (_fuse) + { + t_rhs_fuse.allocator()->init(*rhs_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(); + t_dst.allocator()->allocate(); + if (_fuse) + { + t_rhs_fuse.allocator()->allocate(); + } + + fill(AccessorType(t_lhs), 0); + fill(AccessorType(t_rhs), 1); + if (_fuse) + { + fill(AccessorType(t_rhs_fuse), 2); + } + + // Run runtime + if (_fuse) + { + runtime.run({&t_lhs, &t_rhs, &t_rhs_fuse, &t_dst}); + } + else + { + runtime.run({&t_lhs, &t_rhs, &t_dst}); + } + + return t_dst; + } + + SimpleTensor<T> compute_reference(const TensorShape &shape0, const TensorShape &shape1, const 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>(_ref_op, ref_lhs, ref_rhs, ref_dst, ConvertPolicy::WRAP); + if (_fuse) + { + fill(ref_rhs_fuse, 2); + reference::arithmetic_operation<T>(_ref_op, ref_dst, ref_rhs_fuse, ref_dst_fuse, ConvertPolicy::WRAP); + } + SimpleTensor<T> *ret = _fuse ? &ref_dst_fuse : &ref_dst; + return *ret; + } + + ArithmeticOperation _ref_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: + void setup(ArithmeticOperation ref_op, const TensorShape &shape0, DataType data_type, bool is_inplace) + { + DynamicFusionGpuElementwiseBinaryValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup( + ref_op, shape0, shape0, TensorShape(), data_type, is_inplace); + } +}; + +template <typename TensorType, typename AccessorType, typename FunctionType, typename T> +class DynamicFusionGpuElementwiseBinaryBroadcastOneOpValidationFixture + : public DynamicFusionGpuElementwiseBinaryValidationGenericFixture<TensorType, AccessorType, FunctionType, T> +{ +public: + void setup(ArithmeticOperation ref_op, + const TensorShape &shape0, + const TensorShape &shape1, + DataType data_type, + bool is_inplace) + { + DynamicFusionGpuElementwiseBinaryValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup( + ref_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: + void setup(ArithmeticOperation ref_op, + const TensorShape &shape0, + const TensorShape &shape1, + const TensorShape &shape2, + DataType data_type, + bool is_inplace, + bool fuse_two_ops) + { + DynamicFusionGpuElementwiseBinaryValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup( + ref_op, shape0, shape1, shape2, data_type, is_inplace, fuse_two_ops); + } +}; + +} // namespace validation +} // namespace test +} // namespace arm_compute +#endif // ACL_TESTS_VALIDATION_FIXTURES_DYNAMIC_FUSION_GPU_CL_ELEMENTWISEBINARYFIXTURE_H |