diff options
Diffstat (limited to 'tests/validation/fixtures/BatchNormalizationLayerFixture.h')
| -rw-r--r-- | tests/validation/fixtures/BatchNormalizationLayerFixture.h | 43 |
1 files changed, 23 insertions, 20 deletions
diff --git a/tests/validation/fixtures/BatchNormalizationLayerFixture.h b/tests/validation/fixtures/BatchNormalizationLayerFixture.h index 359752f14e..54a0ed9e09 100644 --- a/tests/validation/fixtures/BatchNormalizationLayerFixture.h +++ b/tests/validation/fixtures/BatchNormalizationLayerFixture.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017-2018 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 BatchNormalizationLayerValidationFixture : public framework::Fixture { public: - template <typename...> void setup(TensorShape shape0, TensorShape shape1, float epsilon, bool use_beta, bool use_gamma, ActivationLayerInfo act_info, DataType dt, DataLayout data_layout) { _data_type = dt; @@ -59,10 +58,14 @@ protected: template <typename U> void fill(U &&src_tensor, U &&mean_tensor, U &&var_tensor, U &&beta_tensor, U &&gamma_tensor) { - 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_var(0, max_bound); + static_assert(std::is_floating_point<T>::value || std::is_same<T, half>::value, "Only floating point data types supported."); + using DistributionType = typename std::conditional<std::is_same<T, half>::value, arm_compute::utils::uniform_real_distribution_16bit<T>, std::uniform_real_distribution<T>>::type; + + const T min_bound = T(-1.f); + const T max_bound = T(1.f); + DistributionType distribution{ min_bound, max_bound }; + DistributionType distribution_var{ T(0.f), max_bound }; + library->fill(src_tensor, distribution, 0); library->fill(mean_tensor, distribution, 1); library->fill(var_tensor, distribution_var, 0); @@ -73,7 +76,7 @@ protected: else { // Fill with default value 0.f - library->fill_tensor_value(beta_tensor, 0.f); + library->fill_tensor_value(beta_tensor, T(0.f)); } if(_use_gamma) { @@ -82,7 +85,7 @@ protected: else { // Fill with default value 1.f - library->fill_tensor_value(gamma_tensor, 1.f); + library->fill_tensor_value(gamma_tensor, T(1.f)); } } @@ -107,12 +110,12 @@ protected: TensorType *gamma_ptr = _use_gamma ? &gamma : nullptr; norm.configure(&src, &dst, &mean, &var, beta_ptr, gamma_ptr, epsilon, act_info); - 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(var.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(beta.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(gamma.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(var.info()->is_resizable()); + ARM_COMPUTE_ASSERT(beta.info()->is_resizable()); + ARM_COMPUTE_ASSERT(gamma.info()->is_resizable()); // Allocate tensors src.allocator()->allocate(); @@ -122,12 +125,12 @@ protected: beta.allocator()->allocate(); gamma.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(!var.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(!beta.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(!gamma.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(!var.info()->is_resizable()); + ARM_COMPUTE_ASSERT(!beta.info()->is_resizable()); + ARM_COMPUTE_ASSERT(!gamma.info()->is_resizable()); // Fill tensors fill(AccessorType(src), AccessorType(mean), AccessorType(var), AccessorType(beta), AccessorType(gamma)); |