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| author | Giorgio Arena <giorgio.arena@arm.com> | 2020-12-17 16:47:07 +0000 |
|---|---|---|
| committer | Giorgio Arena <giorgio.arena@arm.com> | 2021-01-07 16:41:34 +0000 |
| commit | 4bdd177c75789451cad9ba1ecf929214ed75c009 (patch) | |
| tree | a6a8ea96045a13af4b29e9c81014516dfe929715 /tests/validation/fixtures/BatchToSpaceLayerFixture.h | |
| parent | 4d9383e179ed6be8cdb117e6353a0dea1c40be93 (diff) | |
| download | ComputeLibrary-4bdd177c75789451cad9ba1ecf929214ed75c009.tar.gz | |
Fix fill() for FP data type in fixtures - Part 2
Resolves: COMPMID-4056
Signed-off-by: Giorgio Arena <giorgio.arena@arm.com>
Change-Id: I6623eb9c0e66e52af4e0e9fb386031f4a09125b7
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/4722
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Michele Di Giorgio <michele.digiorgio@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Diffstat (limited to 'tests/validation/fixtures/BatchToSpaceLayerFixture.h')
| -rw-r--r-- | tests/validation/fixtures/BatchToSpaceLayerFixture.h | 11 |
1 files changed, 7 insertions, 4 deletions
diff --git a/tests/validation/fixtures/BatchToSpaceLayerFixture.h b/tests/validation/fixtures/BatchToSpaceLayerFixture.h index ca6d20a838..a8d132753c 100644 --- a/tests/validation/fixtures/BatchToSpaceLayerFixture.h +++ b/tests/validation/fixtures/BatchToSpaceLayerFixture.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2018 Arm Limited. + * Copyright (c) 2018-2020 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -50,7 +50,10 @@ protected: template <typename U> void fill(U &&tensor, int i) { - std::uniform_real_distribution<> distribution(-1.0f, 1.0f); + 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(-1.0f), T(1.0f) }; library->fill(tensor, distribution, i); } TensorType compute_target(TensorShape input_shape, TensorShape block_shape_shape, TensorShape output_shape, @@ -87,8 +90,8 @@ protected: // Fill tensors fill(AccessorType(input), 0); { - auto block_shape_data = AccessorType(block_shape); - const int idx_width = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH); + auto block_shape_data = AccessorType(block_shape); + const int idx_width = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH); for(unsigned int i = 0; i < block_shape_shape.x(); ++i) { static_cast<int32_t *>(block_shape_data.data())[i] = output_shape[i + idx_width] / input_shape[i + idx_width]; |