diff options
Diffstat (limited to 'tests/validation/fixtures/NormalizePlanarYUVLayerFixture.h')
| -rw-r--r-- | tests/validation/fixtures/NormalizePlanarYUVLayerFixture.h | 31 |
1 files changed, 15 insertions, 16 deletions
diff --git a/tests/validation/fixtures/NormalizePlanarYUVLayerFixture.h b/tests/validation/fixtures/NormalizePlanarYUVLayerFixture.h index b46bd3c407..5f2c865950 100644 --- a/tests/validation/fixtures/NormalizePlanarYUVLayerFixture.h +++ b/tests/validation/fixtures/NormalizePlanarYUVLayerFixture.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017-2019 ARM Limited. + * Copyright (c) 2017-2021, 2023 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -44,7 +44,6 @@ template <typename TensorType, typename AccessorType, typename FunctionType, typ class NormalizePlanarYUVLayerValidationGenericFixture : public framework::Fixture { public: - template <typename...> void setup(TensorShape shape0, TensorShape shape1, DataType dt, DataLayout data_layout, QuantizationInfo quantization_info) { _data_type = dt; @@ -56,12 +55,14 @@ protected: template <typename U> void fill(U &&src_tensor, U &&mean_tensor, U &&std_tensor) { + using FloatDistributionType = typename std::conditional<std::is_same<T, half>::value, arm_compute::utils::uniform_real_distribution_16bit<T>, std::uniform_real_distribution<float>>::type; + if(is_data_type_float(_data_type)) { - const float min_bound = -1.f; - const float max_bound = 1.f; - std::uniform_real_distribution<> distribution(min_bound, max_bound); - std::uniform_real_distribution<> distribution_std(0.1, max_bound); + const T min_bound = T(-1.f); + const T max_bound = T(1.f); + FloatDistributionType distribution(min_bound, max_bound); + FloatDistributionType distribution_std(T(0.1f), max_bound); library->fill(src_tensor, distribution, 0); library->fill(mean_tensor, distribution, 1); library->fill(std_tensor, distribution_std, 2); @@ -95,10 +96,10 @@ protected: FunctionType norm; norm.configure(&src, &dst, &mean, &std); - ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(mean.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(std.info()->is_resizable(), framework::LogLevel::ERRORS); + ARM_COMPUTE_ASSERT(src.info()->is_resizable()); + ARM_COMPUTE_ASSERT(dst.info()->is_resizable()); + ARM_COMPUTE_ASSERT(mean.info()->is_resizable()); + ARM_COMPUTE_ASSERT(std.info()->is_resizable()); // Allocate tensors src.allocator()->allocate(); @@ -106,10 +107,10 @@ protected: mean.allocator()->allocate(); std.allocator()->allocate(); - ARM_COMPUTE_EXPECT(!src.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(!dst.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(!mean.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(!std.info()->is_resizable(), framework::LogLevel::ERRORS); + ARM_COMPUTE_ASSERT(!src.info()->is_resizable()); + ARM_COMPUTE_ASSERT(!dst.info()->is_resizable()); + ARM_COMPUTE_ASSERT(!mean.info()->is_resizable()); + ARM_COMPUTE_ASSERT(!std.info()->is_resizable()); // Fill tensors fill(AccessorType(src), AccessorType(mean), AccessorType(std)); @@ -142,7 +143,6 @@ template <typename TensorType, typename AccessorType, typename FunctionType, typ class NormalizePlanarYUVLayerValidationFixture : public NormalizePlanarYUVLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T> { public: - template <typename...> void setup(TensorShape shape0, TensorShape shape1, DataType dt, DataLayout data_layout) { NormalizePlanarYUVLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(shape0, shape1, dt, data_layout, QuantizationInfo()); @@ -153,7 +153,6 @@ template <typename TensorType, typename AccessorType, typename FunctionType, typ class NormalizePlanarYUVLayerValidationQuantizedFixture : public NormalizePlanarYUVLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T> { public: - template <typename...> void setup(TensorShape shape0, TensorShape shape1, DataType dt, DataLayout data_layout, QuantizationInfo quantization_info) { NormalizePlanarYUVLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(shape0, shape1, dt, data_layout, quantization_info); |