diff options
Diffstat (limited to 'tests/validation/fixtures/BatchNormalizationLayerFusionFixture.h')
| -rw-r--r-- | tests/validation/fixtures/BatchNormalizationLayerFusionFixture.h | 56 |
1 files changed, 29 insertions, 27 deletions
diff --git a/tests/validation/fixtures/BatchNormalizationLayerFusionFixture.h b/tests/validation/fixtures/BatchNormalizationLayerFusionFixture.h index 39c7d46114..161eeb0ef4 100644 --- a/tests/validation/fixtures/BatchNormalizationLayerFusionFixture.h +++ b/tests/validation/fixtures/BatchNormalizationLayerFusionFixture.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2018 ARM Limited. + * Copyright (c) 2018-2021, 2023 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -45,7 +45,6 @@ template <typename TensorType, typename AccessorType, typename ConvolutionFuncti class BatchNormalizationLayerFusionValidationFixture : public framework::Fixture { public: - template <typename...> void setup(TensorShape src_shape, TensorShape w_shape, TensorShape b_shape, TensorShape dst_shape, PadStrideInfo info, Size2D dilation, bool use_conv_b, bool use_beta, bool use_gamma, float epsilon, DataType dt, DataLayout data_layout) { @@ -65,16 +64,19 @@ protected: template <typename U> void fill(U &&src, U &&w_tensor, U &&b_tensor, U &&mean_tensor, U &&var_tensor, U &&beta_tensor, U &&gamma_tensor) { - std::uniform_real_distribution<> distribution(-1.f, 1.f); - std::uniform_real_distribution<> distribution_gz(0, 1.f); + 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; + + DistributionType distribution{ T(-1.f), T(1.f) }; + DistributionType distribution_gz{ T(0.f), T(1.f) }; library->fill(src, distribution, 0); library->fill(w_tensor, distribution, 1); library->fill(mean_tensor, distribution, 2); library->fill(var_tensor, distribution_gz, 3); - _use_conv_b ? library->fill(b_tensor, distribution, 4) : library->fill_tensor_value(b_tensor, 0.f); - _use_beta ? library->fill(beta_tensor, distribution, 5) : library->fill_tensor_value(beta_tensor, 0.f); - _use_gamma ? library->fill(gamma_tensor, distribution, 6) : library->fill_tensor_value(gamma_tensor, 1.f); + _use_conv_b ? library->fill(b_tensor, distribution, 4) : library->fill_tensor_value(b_tensor, T(0.f)); + _use_beta ? library->fill(beta_tensor, distribution, 5) : library->fill_tensor_value(beta_tensor, T(0.f)); + _use_gamma ? library->fill(gamma_tensor, distribution, 6) : library->fill_tensor_value(gamma_tensor, T(1.f)); } TensorType compute_target(TensorShape src_shape, TensorShape w_shape, TensorShape b_shape, TensorShape dst_shape, PadStrideInfo info, float epsilon) @@ -107,16 +109,16 @@ protected: fuse_fn.configure(&conv_w, &bn_mean, &bn_var, &fused_w, &fused_b, conv_b_ptr, beta_ptr, gamma_ptr, epsilon); conv_fn.configure(&src, &fused_w, &fused_b, &dst, info); - ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(conv_w.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(conv_b.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(bn_mean.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(bn_var.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(bn_beta.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(bn_gamma.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(fused_w.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(fused_b.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(conv_w.info()->is_resizable()); + ARM_COMPUTE_ASSERT(conv_b.info()->is_resizable()); + ARM_COMPUTE_ASSERT(bn_mean.info()->is_resizable()); + ARM_COMPUTE_ASSERT(bn_var.info()->is_resizable()); + ARM_COMPUTE_ASSERT(bn_beta.info()->is_resizable()); + ARM_COMPUTE_ASSERT(bn_gamma.info()->is_resizable()); + ARM_COMPUTE_ASSERT(fused_w.info()->is_resizable()); + ARM_COMPUTE_ASSERT(fused_b.info()->is_resizable()); + ARM_COMPUTE_ASSERT(dst.info()->is_resizable()); // Allocate tensors src.allocator()->allocate(); @@ -130,16 +132,16 @@ protected: fused_b.allocator()->allocate(); dst.allocator()->allocate(); - ARM_COMPUTE_EXPECT(!src.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(!conv_w.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(!conv_b.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(!bn_mean.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(!bn_var.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(!bn_beta.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(!bn_gamma.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(!fused_w.info()->is_resizable(), framework::LogLevel::ERRORS); - ARM_COMPUTE_EXPECT(!fused_b.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(!conv_w.info()->is_resizable()); + ARM_COMPUTE_ASSERT(!conv_b.info()->is_resizable()); + ARM_COMPUTE_ASSERT(!bn_mean.info()->is_resizable()); + ARM_COMPUTE_ASSERT(!bn_var.info()->is_resizable()); + ARM_COMPUTE_ASSERT(!bn_beta.info()->is_resizable()); + ARM_COMPUTE_ASSERT(!bn_gamma.info()->is_resizable()); + ARM_COMPUTE_ASSERT(!fused_w.info()->is_resizable()); + ARM_COMPUTE_ASSERT(!fused_b.info()->is_resizable()); + ARM_COMPUTE_ASSERT(!dst.info()->is_resizable()); // Fill tensors fill(AccessorType(src), |