Raise tolerance number for NEDeconvolutionLayer fp16 tests
Tolerance number was too strict for fp16
Resolves COMPMID-6254
Signed-off-by: SiCong Li <sicong.li@arm.com>
Change-Id: I42a5df21c2545c38ea7234497effd232b43aabf8
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/9635
Reviewed-by: Jakub Sujak <jakub.sujak@arm.com>
Reviewed-by: Omar Al Khatib <omar.alkhatib@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
diff --git a/tests/validation/NEON/DeconvolutionLayer.cpp b/tests/validation/NEON/DeconvolutionLayer.cpp
index a42042b..af25543 100644
--- a/tests/validation/NEON/DeconvolutionLayer.cpp
+++ b/tests/validation/NEON/DeconvolutionLayer.cpp
@@ -47,7 +47,7 @@
constexpr AbsoluteTolerance<float> tolerance_quantized(1.0f); /**< Tolerance value for comparing reference's output against implementation's output for quantized data types */
#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
const RelativeTolerance<half_float::half> tolerance_fp16(half_float::half(0.2f)); /**< Relative tolerance value for comparing reference's output against implementation's output for DataType::F16 */
-constexpr float tolerance_num_fp16 = 0.01f; /**< Tolerance number for FP16 tests -- follows a slightly stricter approach compared to ConvolutionLayer tests */
+constexpr float tolerance_num_fp16 = 0.02f; /**< Tolerance number for FP16 tests -- follows a slightly stricter approach compared to ConvolutionLayer tests */
#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC*/
constexpr float tolerance_num_quant = 0.07f; /**< Tolerance number for quantized types */