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Diffstat (limited to 'tests/validation/fixtures/dynamic_fusion/operators/ActivationFixture.h')
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diff --git a/tests/validation/fixtures/dynamic_fusion/operators/ActivationFixture.h b/tests/validation/fixtures/dynamic_fusion/operators/ActivationFixture.h new file mode 100644 index 0000000000..c9ffbccbc7 --- /dev/null +++ b/tests/validation/fixtures/dynamic_fusion/operators/ActivationFixture.h @@ -0,0 +1,207 @@ +/* + * Copyright (c) 2023-2024 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_OPERATORS_ACTIVATIONFIXTURE_H +#define ACL_TESTS_VALIDATION_FIXTURES_DYNAMIC_FUSION_OPERATORS_ACTIVATIONFIXTURE_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/validation/reference/ActivationLayer.h" + +using namespace arm_compute::experimental::dynamic_fusion; + +namespace arm_compute +{ +namespace test +{ +namespace validation +{ +template <typename TensorType, typename AccessorType, typename FunctionType, typename T, typename... TArgs> +class DynamicFusionActivationValidationFixture : public framework::Fixture +{ +public: + void setup(TensorShape shape, bool fuse, DataType data_type, ActivationLayerInfo act_info, TArgs... args) + { + _fuse = fuse; + _data_type = data_type; + _function = act_info.activation(); + _target = compute_target(shape, args...); + _reference = compute_reference(shape, act_info); + } + +protected: + std::vector<T> get_boundary_values(T min, T max) + { + // This function will return a vector filled with the following values that can + // represent two partitions derived from equivalent partitioning. + // * Lower partition: min, min + delta, lower quarter (nominal), center - delta + // * Upper partition: center, center + delta, upper quarter (nominal), max - delta, max + const auto delta = is_data_type_float(_data_type) ? T(0.1f) : T(1); + const auto center_value = (min + max) / 2; + const auto lower_quarter = (min + center_value) / 2; + const auto upper_quarter = (center_value + max) / 2; + + std::vector<T> boundary_values{}; + + // To ensure all the inserted values are within the given range after subtracing/adding delta + auto insert_values = [&boundary_values, &min, &max](const std::initializer_list<T> &new_values) + { + for (auto &v : new_values) + { + if (v >= min && v <= max) + { + boundary_values.emplace_back(v); + } + } + }; + + insert_values({min, static_cast<T>(min + delta), static_cast<T>(lower_quarter), + static_cast<T>(center_value - delta)}); // lower partition + insert_values({static_cast<T>(center_value), static_cast<T>(center_value + delta), + static_cast<T>(upper_quarter), static_cast<T>(max - delta), max}); // upper partition + + return boundary_values; + } + + template <typename U> + void fill(U &&tensor) + { + float min_bound = 0; + float max_bound = 0; + std::tie(min_bound, max_bound) = get_activation_layer_test_bounds<T>(_function, _data_type); + library->fill_static_values(tensor, get_boundary_values(static_cast<T>(min_bound), static_cast<T>(max_bound))); + } + + TensorType compute_target(const TensorShape &shape, TArgs... args) + { + // Create a new workload sketch + CLCompileContext cl_compile_ctx = CLKernelLibrary::get().get_compile_context(); + GpuWorkloadContext context{&cl_compile_ctx}; + GpuWorkloadSketch sketch{&context}; + + // Create sketch tensors + ITensorInfo *src_info = context.create_tensor_info(TensorInfo(shape, 1, _data_type)); + ITensorInfo *dst_info = context.create_tensor_info(TensorInfo(shape, 1, _data_type)); + + ITensorInfo *ans_0_info = FunctionType::create_op(sketch, src_info, args...); + if (_fuse) + { + ITensorInfo *ans_1_info = FunctionType::create_op(sketch, ans_0_info, args...); + GpuOutput::create_op(sketch, ans_1_info, dst_info); + } + else + { + GpuOutput::create_op(sketch, ans_0_info, dst_info); + } + + // Configure runtime + ClWorkloadRuntime runtime; + runtime.configure(sketch); + + // Construct user tensors + TensorType t_src{}; + TensorType t_dst{}; + + // Initialize user tensors + t_src.allocator()->init(*src_info); + t_dst.allocator()->init(*dst_info); + + // Allocate and fill user tensors + t_src.allocator()->allocate(); + t_dst.allocator()->allocate(); + + fill(AccessorType(t_src)); + + // Run runtime + runtime.run({&t_src, &t_dst}); + + return t_dst; + } + + SimpleTensor<T> compute_reference(const TensorShape &shape, ActivationLayerInfo act_info) + { + // Create reference + SimpleTensor<T> src{shape, _data_type, 1}; + + // Fill reference + fill(src); + + auto tmp = reference::activation_layer<T>(src, act_info); + + if (_fuse) + { + auto dst = reference::activation_layer<T>(tmp, act_info); + return dst; + } + else + { + return tmp; + } + } + +protected: + ActivationLayerInfo::ActivationFunction _function{}; + bool _fuse{false}; + DataType _data_type{}; + TensorType _target{}; + SimpleTensor<T> _reference{}; +}; + +template <typename TensorType, typename AccessorType, typename FunctionType, typename T> +class DynamicFusionSigmoidValidationFixture + : public DynamicFusionActivationValidationFixture<TensorType, AccessorType, FunctionType, T> +{ +public: + void setup(TensorShape shape, bool fuse, DataType data_type) + { + ActivationLayerInfo act_info{ActivationLayerInfo::ActivationFunction::LOGISTIC}; + DynamicFusionActivationValidationFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, fuse, + data_type, act_info); + } +}; + +template <typename TensorType, typename AccessorType, typename FunctionType, typename T> +class DynamicFusionTanhValidationFixture + : public DynamicFusionActivationValidationFixture<TensorType, AccessorType, FunctionType, T> +{ +public: + void setup(TensorShape shape, bool fuse, DataType data_type) + { + ActivationLayerInfo act_info{ActivationLayerInfo::ActivationFunction::TANH, 1.0f, 1.0f}; + DynamicFusionActivationValidationFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, fuse, + data_type, act_info); + } +}; + +} // namespace validation +} // namespace test +} // namespace arm_compute + +#endif // ACL_TESTS_VALIDATION_FIXTURES_DYNAMIC_FUSION_OPERATORS_ACTIVATIONFIXTURE_H |