diff options
Diffstat (limited to 'tests/validation/fixtures/dynamic_fusion/operators/ActivationFixture.h')
-rw-r--r-- | tests/validation/fixtures/dynamic_fusion/operators/ActivationFixture.h | 76 |
1 files changed, 41 insertions, 35 deletions
diff --git a/tests/validation/fixtures/dynamic_fusion/operators/ActivationFixture.h b/tests/validation/fixtures/dynamic_fusion/operators/ActivationFixture.h index 18c3b6bfbb..2f0b13329d 100644 --- a/tests/validation/fixtures/dynamic_fusion/operators/ActivationFixture.h +++ b/tests/validation/fixtures/dynamic_fusion/operators/ActivationFixture.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2023 Arm Limited. + * Copyright (c) 2023-2024 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -22,8 +22,8 @@ * SOFTWARE. */ -#ifndef TESTS_VALIDATION_FIXTURES_DYNAMIC_FUSION_OPERATORS_ACTIVATIONFIXTURE -#define TESTS_VALIDATION_FIXTURES_DYNAMIC_FUSION_OPERATORS_ACTIVATIONFIXTURE +#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" @@ -49,11 +49,11 @@ 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); + _fuse = fuse; + _data_type = data_type; + _function = act_info.activation(); + _target = compute_target(shape, args...); + _reference = compute_reference(shape, act_info); } protected: @@ -73,17 +73,19 @@ protected: // 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) + for (auto &v : new_values) { - if(v >= min && v <= max) + 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 + 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; } @@ -91,8 +93,8 @@ protected: template <typename U> void fill(U &&tensor) { - float min_bound = 0; - float max_bound = 0; + 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))); } @@ -101,22 +103,22 @@ protected: { // Create a new workload sketch CLCompileContext cl_compile_ctx = CLKernelLibrary::get().get_compile_context(); - GpuWorkloadContext context{ &cl_compile_ctx }; - GpuWorkloadSketch sketch{ &context }; + GpuWorkloadContext context{&cl_compile_ctx}; + GpuWorkloadSketch sketch{&context}; // Create sketch tensors - TensorInfo src_info = context.create_tensor_info(TensorInfo(shape, 1, _data_type)); - TensorInfo dst_info = context.create_tensor_info(TensorInfo(shape, 1, _data_type)); + 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_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); + GpuOutput::create_op(sketch, ans_1_info, dst_info); } else { - GpuOutput::create_op(sketch, ans_0_info, &dst_info); + GpuOutput::create_op(sketch, ans_0_info, dst_info); } // Configure runtime @@ -128,8 +130,8 @@ protected: TensorType t_dst{}; // Initialize user tensors - t_src.allocator()->init(src_info); - t_dst.allocator()->init(dst_info); + t_src.allocator()->init(*src_info); + t_dst.allocator()->init(*dst_info); // Allocate and fill user tensors t_src.allocator()->allocate(); @@ -138,7 +140,7 @@ protected: fill(AccessorType(t_src)); // Run runtime - runtime.run({ &t_src, &t_dst }); + runtime.run({&t_src, &t_dst}); return t_dst; } @@ -146,14 +148,14 @@ protected: SimpleTensor<T> compute_reference(const TensorShape &shape, ActivationLayerInfo act_info) { // Create reference - SimpleTensor<T> src{ shape, _data_type, 1 }; + SimpleTensor<T> src{shape, _data_type, 1}; // Fill reference fill(src); auto tmp = reference::activation_layer<T>(src, act_info); - if(_fuse) + if (_fuse) { auto dst = reference::activation_layer<T>(tmp, act_info); return dst; @@ -166,31 +168,35 @@ protected: protected: ActivationLayerInfo::ActivationFunction _function{}; - bool _fuse{ false }; + 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> +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); + 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> +class DynamicFusionTanhValidationFixture + : public DynamicFusionActivationValidationFixture<TensorType, AccessorType, FunctionType, T> { public: void setup(TensorShape shape, bool fuse, DataType data_type) { - ActivationLayerInfo act_info{ ActivationLayerInfo::ActivationFunction::TANH }; - DynamicFusionActivationValidationFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, fuse, data_type, act_info); + ActivationLayerInfo act_info{ActivationLayerInfo::ActivationFunction::TANH}; + DynamicFusionActivationValidationFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, fuse, + data_type, act_info); } }; @@ -198,4 +204,4 @@ public: } // namespace test } // namespace arm_compute -#endif /* TESTS_VALIDATION_FIXTURES_DYNAMIC_FUSION_OPERATORS_ACTIVATIONFIXTURE */ +#endif // ACL_TESTS_VALIDATION_FIXTURES_DYNAMIC_FUSION_OPERATORS_ACTIVATIONFIXTURE_H |