diff options
Diffstat (limited to 'tests/validation/fixtures/SoftmaxLayerFixture.h')
| -rw-r--r-- | tests/validation/fixtures/SoftmaxLayerFixture.h | 41 |
1 files changed, 20 insertions, 21 deletions
diff --git a/tests/validation/fixtures/SoftmaxLayerFixture.h b/tests/validation/fixtures/SoftmaxLayerFixture.h index aeff777776..f4bf8df9c0 100644 --- a/tests/validation/fixtures/SoftmaxLayerFixture.h +++ b/tests/validation/fixtures/SoftmaxLayerFixture.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017-2020 ARM Limited. + * Copyright (c) 2017-2021, 2023 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -32,7 +32,6 @@ #include "tests/IAccessor.h" #include "tests/framework/Asserts.h" #include "tests/framework/Fixture.h" -#include "tests/validation/reference/LogSoftmaxLayer.h" #include "tests/validation/reference/SoftmaxLayer.h" #include <random> @@ -47,29 +46,37 @@ template <typename TensorType, typename AccessorType, typename FunctionType, typ class SoftmaxValidationGenericFixture : public framework::Fixture { public: - template <typename...> void setup(TensorShape shape, DataType data_type, QuantizationInfo quantization_info, float beta, size_t axis) { _quantization_info = quantization_info; - _target = compute_target(shape, data_type, quantization_info, beta, axis); _reference = compute_reference(shape, data_type, quantization_info, beta, axis); + _target = compute_target(shape, data_type, quantization_info, beta, axis); } protected: template <typename U> void fill(U &&tensor) { - if(!is_data_type_quantized(tensor.data_type())) + if(tensor.data_type() == DataType::F32) { - std::uniform_real_distribution<> distribution(-1000.f, 1000.f); + std::uniform_real_distribution<float> distribution(-10.0f, 10.0f); library->fill(tensor, distribution, 0); } - else // data type is quantized_asymmetric (signed or unsigned) + else if(tensor.data_type() == DataType::F16) + { + arm_compute::utils::uniform_real_distribution_16bit<half> distribution{ -10.0f, 10.0f }; + library->fill(tensor, distribution, 0); + } + else if(!is_data_type_quantized(tensor.data_type())) { std::uniform_int_distribution<> distribution(0, 100); library->fill(tensor, distribution, 0); } + else + { + library->fill_tensor_uniform(tensor, 0); + } } TensorType compute_target(const TensorShape &shape, DataType data_type, @@ -83,15 +90,15 @@ protected: FunctionType smx_layer; smx_layer.configure(&src, &dst, beta, axis); - ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS); + ARM_COMPUTE_ASSERT(src.info()->is_resizable()); + ARM_COMPUTE_ASSERT(dst.info()->is_resizable()); // Allocate tensors src.allocator()->allocate(); dst.allocator()->allocate(); - ARM_COMPUTE_EXPECT(!src.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(!dst.info()->is_resizable(), framework::LogLevel::ERRORS); + ARM_COMPUTE_ASSERT(!src.info()->is_resizable()); + ARM_COMPUTE_ASSERT(!dst.info()->is_resizable()); // Fill tensors fill(AccessorType(src)); @@ -111,14 +118,7 @@ protected: // Fill reference fill(src); - if(IS_LOG) - { - return reference::log_softmax_layer<T>(src, beta, axis); - } - else - { - return reference::softmax_layer<T>(src, beta, axis); - } + return reference::softmax_layer<T>(src, beta, axis, IS_LOG); } TensorType _target{}; @@ -130,7 +130,6 @@ template <typename TensorType, typename AccessorType, typename FunctionType, typ class SoftmaxValidationFixture : public SoftmaxValidationGenericFixture<TensorType, AccessorType, FunctionType, T, IS_LOG> { public: - template <typename...> void setup(TensorShape shape, DataType data_type, float beta, size_t axis) { SoftmaxValidationGenericFixture<TensorType, AccessorType, FunctionType, T, IS_LOG>::setup(shape, @@ -145,7 +144,6 @@ template <typename TensorType, typename AccessorType, typename FunctionType, typ class SoftmaxValidationQuantizedFixture : public SoftmaxValidationGenericFixture<TensorType, AccessorType, FunctionType, T, IS_LOG> { public: - template <typename...> void setup(TensorShape shape, DataType data_type, QuantizationInfo quantization_info, float beta, size_t axis) { SoftmaxValidationGenericFixture<TensorType, AccessorType, FunctionType, T, IS_LOG>::setup(shape, @@ -155,6 +153,7 @@ public: axis); } }; + } // namespace validation } // namespace test } // namespace arm_compute |