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authorMurray Kornelsen <murray.kornelsen@mail.mcgill.ca>2022-07-22 18:04:59 -0400
committerPablo Marquez Tello <pablo.tello@arm.com>2022-09-02 10:44:06 +0000
commit552fe4c67d3cd2994cdbd5662cde79da5caf0c4d (patch)
tree501cc20a0f878e5d7542977180c843b1b7778784 /tests/datasets
parent1257131193fdb9b6940055a41691320e37a208b5 (diff)
downloadComputeLibrary-552fe4c67d3cd2994cdbd5662cde79da5caf0c4d.tar.gz
F16 Specialization for MeanStdDevNorm
Ran into issues with f16 meanstddevnorm. Essentially, with large enough tensors and/or large values in tensors, output becomes all 0. This is due to the variance computation. In f16, it reaches infinity quite easily, then the division results in 0. This change modifies the OpenCL and NEON implementations to compute the sum of squares and the variance using f32, while other operations remain f16. Update: Found that the square operation also benefits from f32, rather than squaring in f16 and accumulating f32. Signed-off-by: Murray Kornelsen <murray.kornelsen@mail.mcgill.ca> Change-Id: Ide00afd84ec6d26fec4d53b073e295814f08ba46 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/7959 Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com> Comments-Addressed: Pablo Marquez Tello <pablo.tello@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Benchmark: Arm Jenkins <bsgcomp@arm.com>
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