diff options
Diffstat (limited to 'tests/validation/fixtures/SoftmaxLayerFixture.h')
| -rw-r--r-- | tests/validation/fixtures/SoftmaxLayerFixture.h | 28 |
1 files changed, 17 insertions, 11 deletions
diff --git a/tests/validation/fixtures/SoftmaxLayerFixture.h b/tests/validation/fixtures/SoftmaxLayerFixture.h index 30356d648d..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 * @@ -46,7 +46,6 @@ 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; @@ -59,16 +58,25 @@ 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(-10.f, 10.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, @@ -82,15 +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)); @@ -122,7 +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, @@ -137,7 +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, |