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authorGiorgio Arena <giorgio.arena@arm.com>2020-12-17 16:47:07 +0000
committerGiorgio Arena <giorgio.arena@arm.com>2021-01-07 16:41:34 +0000
commit4bdd177c75789451cad9ba1ecf929214ed75c009 (patch)
treea6a8ea96045a13af4b29e9c81014516dfe929715 /tests/validation/fixtures/NormalizePlanarYUVLayerFixture.h
parent4d9383e179ed6be8cdb117e6353a0dea1c40be93 (diff)
downloadComputeLibrary-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/NormalizePlanarYUVLayerFixture.h')
-rw-r--r--tests/validation/fixtures/NormalizePlanarYUVLayerFixture.h12
1 files changed, 7 insertions, 5 deletions
diff --git a/tests/validation/fixtures/NormalizePlanarYUVLayerFixture.h b/tests/validation/fixtures/NormalizePlanarYUVLayerFixture.h
index bd846927d3..0189261949 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) 2017-2020 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -56,12 +56,14 @@ 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_fp16, 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);