diff options
Diffstat (limited to 'tests/validation/fixtures/BatchNormalizationLayerFusionFixture.h')
| -rw-r--r-- | tests/validation/fixtures/BatchNormalizationLayerFusionFixture.h | 15 |
1 files changed, 9 insertions, 6 deletions
diff --git a/tests/validation/fixtures/BatchNormalizationLayerFusionFixture.h b/tests/validation/fixtures/BatchNormalizationLayerFusionFixture.h index 2df7f47ff3..3f7f97a29c 100644 --- a/tests/validation/fixtures/BatchNormalizationLayerFusionFixture.h +++ b/tests/validation/fixtures/BatchNormalizationLayerFusionFixture.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2018 Arm Limited. + * Copyright (c) 2018-2020 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -65,16 +65,19 @@ 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_fp16, 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) |