From 05069f07bcf95676597698a79926327555276362 Mon Sep 17 00:00:00 2001 From: Manuel Bottini Date: Thu, 26 Sep 2019 17:18:26 +0100 Subject: COMPMID-2515: Merge optimized depthwise convolution to the generic depthwise convolution function 3RDPARTY_UPDATE Change-Id: Iff9e915c5329c617527b6f5042979f4e21a8b2b8 Signed-off-by: Manuel Bottini Reviewed-on: https://review.mlplatform.org/c/2022 Comments-Addressed: Arm Jenkins Reviewed-by: Giorgio Arena Tested-by: Arm Jenkins Reviewed-by: Georgios Pinitas --- docs/00_introduction.dox | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) (limited to 'docs/00_introduction.dox') diff --git a/docs/00_introduction.dox b/docs/00_introduction.dox index 6430411f5b..7179c0d822 100644 --- a/docs/00_introduction.dox +++ b/docs/00_introduction.dox @@ -246,6 +246,7 @@ v19.11 Public major release - NEDepthwiseWeightsReshapeKernel - NEDepthwiseIm2ColKernel - NEDepthwiseVectorToTensorKernel + - NEDepthwiseConvolutionLayer3x3 v19.08 Public major release - Various bug fixes. @@ -301,7 +302,8 @@ v19.08 Public major release - Added an optimized depthwise convolution layer kernel for 5x5 filters (NEON only) - Added support to enable OpenCL kernel cache. Added example showing how to load the prebuilt OpenCL kernels from a binary cache file - Altered @ref QuantizationInfo interface to support per-channel quantization. - - The @ref NEDepthwiseConvolutionLayer3x3 will be replaced by @ref NEDepthwiseConvolutionLayerOptimized to accommodate for future optimizations. + - The @ref CLDepthwiseConvolutionLayer3x3 will be included by @ref CLDepthwiseConvolutionLayer to accommodate for future optimizations. + - The @ref NEDepthwiseConvolutionLayerOptimized will be included by @ref NEDepthwiseConvolutionLayer to accommodate for future optimizations. - Removed inner_border_right and inner_border_top parameters from @ref CLDeconvolutionLayer interface - Removed inner_border_right and inner_border_top parameters from @ref NEDeconvolutionLayer interface - Optimized the NEON assembly kernel for GEMMLowp. The new implementation fuses the output stage and quantization with the matrix multiplication kernel -- cgit v1.2.1