Port Arm(R) Neon(TM) Scale to new API
Partially resolves: COMPMID-4190
Change-Id: I0c1e32ff6176775c9b7bf547899a791fd318ba0a
Signed-off-by: Manuel Bottini <manuel.bottini@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/5192
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: TeresaARM <teresa.charlinreyes@arm.com>
Reviewed-by: Michele Di Giorgio <michele.digiorgio@arm.com>
Reviewed-by: Sheri Zhang <sheri.zhang@arm.com>
diff --git a/docs/00_introduction.dox b/docs/00_introduction.dox
index 1bab6e5..d877236 100644
--- a/docs/00_introduction.dox
+++ b/docs/00_introduction.dox
@@ -180,7 +180,7 @@
- Add macOS support
- Add Armv8-R AArch64 architecture support
- Add SVE/SVE2 support for:
- - @ref NEScaleKernel
+ - NEScaleKernel
- @ref NEActivationLayer
- @ref NEArithmeticAddition
- @ref NEBatchNormalizationLayerKernel
@@ -260,7 +260,7 @@
- @ref NERemapKernel
- @ref NEGEMMInterleave4x4Kernel
- @ref NEDirectConvolutionLayerKernel
- - @ref NEScaleKernel
+ - NEScaleKernel
- NELocallyConnectedMatrixMultiplyKernel
- @ref NEGEMMLowpOffsetContributionKernel
- @ref NEGEMMTranspose1xWKernel
@@ -534,7 +534,7 @@
- @ref NECropKernel
- CLCropKernel
- Added aligh_corner support for nearest neighbor interpolation in:
- - @ref NEScaleKernel
+ - NEScaleKernel
- CLScaleKernel
- New OpenCL kernels / functions:
- @ref CLMaxUnpoolingLayerKernel
@@ -621,7 +621,7 @@
- @ref CLReductionOperation
- @ref CLReduceMean
- @ref NEScale
- - @ref NEScaleKernel
+ - NEScaleKernel
- NEUpsampleLayer
- @ref NECast
- @ref NEReductionOperation
@@ -1139,7 +1139,7 @@
- Added support for the memory manager in the graph API.
- Enabled Winograd Convolution method in the graph API.
- Added support for grouped convolutions in the graph API.
- - Replaced NEDeconvolutionLayerUpsampleKernel with @ref NEScaleKernel in @ref NEDeconvolutionLayer.
+ - Replaced NEDeconvolutionLayerUpsampleKernel with NEScaleKernel in @ref NEDeconvolutionLayer.
- Added fast maths flag in @ref CLConvolutionLayer.
- Added new tests and benchmarks in validation and benchmark frameworks
- Merge Activation layer with Convolution Layer (Neon. CL, GLES)