| /* |
| * 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 |
| * 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_OPERATORS_MULFIXTURE |
| #define TESTS_VALIDATION_FIXTURES_DYNAMIC_FUSION_OPERATORS_MULFIXTURE |
| |
| #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/Globals.h" |
| #include "tests/framework/Fixture.h" |
| #include "tests/framework/Macros.h" |
| #include "tests/validation/reference/PixelWiseMultiplication.h" |
| |
| using namespace arm_compute::experimental::dynamic_fusion; |
| |
| namespace arm_compute |
| { |
| namespace test |
| { |
| namespace validation |
| { |
| /* We use a separate test fixture for Multiplication op instead of reusing ElementwiseBinaryFixture to avoid exposing |
| * the internal enum ElementwiseOp to the public utils/TypePrinters.h as required by the data test case macros |
| * to print the test data. |
| */ |
| template <typename TensorType, typename AccessorType, typename FunctionType, typename T> |
| class DynamicFusionMulValidationFixture : public framework::Fixture |
| { |
| public: |
| template <typename...> |
| void setup(const TensorShape &shape0, const TensorShape &shape1, const TensorShape &shape2, DataType data_type, bool is_inplace, bool fuse_two_ops = false) |
| { |
| _data_type = data_type; |
| _is_inplace = is_inplace; |
| _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) |
| { |
| 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 gpu_ctx = GpuWorkloadContext{ &cl_compile_ctx }; |
| GpuWorkloadSketch sketch{ &gpu_ctx }; |
| |
| // Fuse first multiplication op |
| TensorInfo lhs_info = sketch.create_tensor_info(TensorInfo(shape0, 1, _data_type)); |
| TensorInfo rhs_info = sketch.create_tensor_info(TensorInfo(shape1, 1, _data_type)); |
| TensorInfo dst_info = sketch.create_tensor_info(); |
| |
| TensorInfo rhs_info_fuse; |
| |
| ITensorInfo *ans_info = FunctionType::create_op(sketch, &lhs_info, &rhs_info); |
| |
| if(_fuse) |
| { |
| rhs_info_fuse = sketch.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) |
| { |
| // 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() }; |
| |
| // Fill reference |
| fill(ref_lhs, 0); |
| fill(ref_rhs, 1); |
| SimpleTensor<T> ref_dst = reference::pixel_wise_multiplication<T, T, T>(ref_lhs, |
| ref_rhs, |
| 1.f, |
| ConvertPolicy::SATURATE, |
| RoundingPolicy::TO_NEAREST_UP, |
| _data_type, |
| QuantizationInfo()); |
| if(_fuse) |
| { |
| fill(ref_rhs_fuse, 2); |
| SimpleTensor<T> ref_dst_fuse = reference::pixel_wise_multiplication<T, T, T>(ref_dst, |
| ref_rhs_fuse, |
| 1.f, |
| ConvertPolicy::SATURATE, |
| RoundingPolicy::TO_NEAREST_UP, |
| _data_type, |
| QuantizationInfo()); |
| return ref_dst_fuse; |
| } |
| return ref_dst; |
| } |
| |
| TensorType _target{}; |
| SimpleTensor<T> _reference{}; |
| DataType _data_type{}; |
| bool _is_inplace{ false }; |
| bool _fuse{ false }; |
| }; |
| |
| template <typename TensorType, typename AccessorType, typename FunctionType, typename T> |
| class DynamicFusionMulOneOpValidationFixture : public DynamicFusionMulValidationFixture<TensorType, AccessorType, FunctionType, T> |
| { |
| public: |
| template <typename...> |
| void setup(const TensorShape &shape0, DataType data_type, bool is_inplace) |
| { |
| DynamicFusionMulValidationFixture<TensorType, AccessorType, FunctionType, T>::setup(shape0, shape0, TensorShape(), data_type, is_inplace); |
| } |
| }; |
| |
| template <typename TensorType, typename AccessorType, typename FunctionType, typename T> |
| class DynamicFusionMulBroadcastValidationFixture : public DynamicFusionMulValidationFixture<TensorType, AccessorType, FunctionType, T> |
| { |
| public: |
| template <typename...> |
| void setup(const TensorShape &shape0, const TensorShape &shape1, DataType data_type, bool is_inplace) |
| { |
| DynamicFusionMulValidationFixture<TensorType, AccessorType, FunctionType, T>::setup(shape0, shape1, TensorShape(), data_type, is_inplace); |
| } |
| }; |
| |
| template <typename TensorType, typename AccessorType, typename FunctionType, typename T> |
| class DynamicFusionMulTwoOpsValidationFixture : public DynamicFusionMulValidationFixture<TensorType, AccessorType, FunctionType, T> |
| { |
| public: |
| template <typename...> |
| void setup(const TensorShape &shape0, const TensorShape &shape1, const TensorShape &shape2, DataType data_type, bool is_inplace, bool fuse_two_ops) |
| { |
| DynamicFusionMulValidationFixture<TensorType, AccessorType, FunctionType, T>::setup(shape0, shape1, shape2, data_type, is_inplace, fuse_two_ops); |
| } |
| }; |
| |
| } // namespace validation |
| } // namespace test |
| } // namespace arm_compute |
| #endif /* TESTS_VALIDATION_FIXTURES_DYNAMIC_FUSION_OPERATORS_MULFIXTURE */ |