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| author | SiCong Li <sicong.li@arm.com> | 2020-08-28 11:18:47 +0100 |
|---|---|---|
| committer | Georgios Pinitas <georgios.pinitas@arm.com> | 2020-09-09 12:01:59 +0000 |
| commit | bb88f89b7a12e83eea2fc701f1f82aabf7dfcf7a (patch) | |
| tree | dc9339328346fc539f45ee2b7b39a0786cadbc3a /docs/00_introduction.dox | |
| parent | d64444ba197c2f95dcf4d205f50a196d5a29cdeb (diff) | |
| download | ComputeLibrary-bb88f89b7a12e83eea2fc701f1f82aabf7dfcf7a.tar.gz | |
COMPMID-3581 Add S32 support to NEPixelWiseMultiplication
* Add S32 support to NEPixelWiseMultiplication and NEPixelWiseMultiplicationKernel
* Scale == 1/255 is not supported for S32, as on non-aarch64 the
precision requirement is not met, and scale is a non-standard
parameter anyway.
* Fix the data types validation logics to also test for all invalid data
type combinations.
* Add validation tests for S32 NEON PixelWiseMultiplication
* The wrap tolerance for ScaleOther (scale == 1/2^n) cases is set to
1 instead of 0 because the reference uses floating point division
followed by rounding, which is isn't bit accurate.
Change-Id: I28839afda7a4f98c985d1763620e08d98f740142
Signed-off-by: SiCong Li <sicong.li@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/3923
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Michele Di Giorgio <michele.digiorgio@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Diffstat (limited to 'docs/00_introduction.dox')
| -rw-r--r-- | docs/00_introduction.dox | 2 |
1 files changed, 2 insertions, 0 deletions
diff --git a/docs/00_introduction.dox b/docs/00_introduction.dox index f8f07906a8..bfe5799362 100644 --- a/docs/00_introduction.dox +++ b/docs/00_introduction.dox @@ -241,6 +241,8 @@ v20.11 Public major release - Added new data type S32 support for: - @ref NEArithmeticSubtraction - @ref NEArithmeticSubtractionKernel + - @ref NEPixelWiseMultiplication + - @ref NEPixelWiseMultiplicationKernel - Interface change - Properly support softmax axis to have the same meaning as other major frameworks. That is, axis now defines the dimension on which Softmax/Logsoftmax is performed. E.g. for input of shape 4x5x6 and axis=1, softmax will be applied to 4x6=24 vectors of size 5. |