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| author | Michalis Spyrou <michalis.spyrou@arm.com> | 2018-06-20 10:16:31 +0100 |
|---|---|---|
| committer | Anthony Barbier <anthony.barbier@arm.com> | 2018-11-02 16:53:09 +0000 |
| commit | f5f0ecca39c905bc8c1f90e7469eed2221ca662f (patch) | |
| tree | 685161fc3094aed68d09a9fcb9fb6e6777cdd087 | |
| parent | 7210fe8bb3fefc13b14ded356a9acb0a57aef277 (diff) | |
| download | ComputeLibrary-f5f0ecca39c905bc8c1f90e7469eed2221ca662f.tar.gz | |
COMPMID-1246 Increase tolerance in CLArithmeticDivision for FP16
Also change the random distribution range to not include values
close to zero which will produce inf.
Change-Id: I75f72c57b5cc66b4b305501b7f9c6a63c6cc30eb
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/136351
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
Reviewed-by: Pablo Tello <pablo.tello@arm.com>
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
| -rw-r--r-- | tests/validation/CL/ArithmeticDivision.cpp | 2 | ||||
| -rw-r--r-- | tests/validation/fixtures/ArithmeticDivisionFixture.h | 3 |
2 files changed, 3 insertions, 2 deletions
diff --git a/tests/validation/CL/ArithmeticDivision.cpp b/tests/validation/CL/ArithmeticDivision.cpp index dab3f75018..42e2d223c2 100644 --- a/tests/validation/CL/ArithmeticDivision.cpp +++ b/tests/validation/CL/ArithmeticDivision.cpp @@ -44,7 +44,7 @@ namespace validation namespace { RelativeTolerance<float> tolerance_fp32(0.000001f); -RelativeTolerance<float> tolerance_fp16(0.0001f); +RelativeTolerance<float> tolerance_fp16(0.001f); } // namespace TEST_SUITE(CL) diff --git a/tests/validation/fixtures/ArithmeticDivisionFixture.h b/tests/validation/fixtures/ArithmeticDivisionFixture.h index d113977ca8..cf9db9505b 100644 --- a/tests/validation/fixtures/ArithmeticDivisionFixture.h +++ b/tests/validation/fixtures/ArithmeticDivisionFixture.h @@ -55,7 +55,8 @@ protected: template <typename U> void fill(U &&tensor, int i) { - library->fill_tensor_uniform(tensor, i); + std::uniform_real_distribution<> distribution(1.0f, 5.0f); + library->fill(tensor, distribution, i); } TensorType compute_target(const TensorShape &shape0, const TensorShape &shape1, DataType data_type) |