arm_compute v19.08
diff --git a/docs/00_introduction.dox b/docs/00_introduction.dox
index cbfd456..ca9e7e3 100644
--- a/docs/00_introduction.dox
+++ b/docs/00_introduction.dox
@@ -236,6 +236,65 @@
@subsection S2_2_changelog Changelog
+v19.08 Public major release
+ - Various bug fixes.
+ - Various optimisations.
+ - Deprecated NEON functions
+ - NEDepthConcatenateLayer
+ - NEWidthConcatenateLayer
+ - Deprecated OpenCL kernels / functions
+ - CLDepthConcatenateLayer
+ - CLGEMMInterleave4x4Kernel / CLGEMMInterleave4x4
+ - CLGEMMTranspose1xWKernel / CLGEMMTranspose1xW
+ - CLWidthConcatenateLayer
+ - New NEON kernels / functions:
+ - @ref NEAbsLayer
+ - @ref NECast
+ - @ref NEElementwisePower
+ - @ref NELogLayer
+ - @ref NELSTMLayerQuantized
+ - @ref NENegLayer
+ - @ref NEPReluLayer
+ - @ref NESinLayer
+ - @ref NEBatchConcatenateLayerKernel
+ - @ref NEDepthToSpaceLayerKernel / @ref NEDepthToSpaceLayer
+ - @ref NEDepthwiseConvolutionLayerNativeKernel
+ - @ref NEGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel
+ - @ref NEMeanStdDevNormalizationKernel / @ref NEMeanStdDevNormalizationLayer
+ - @ref NESpaceToDepthLayerKernel / @ref NESpaceToDepthLayer
+ - New OpenCL kernels / functions:
+ - @ref CLAbsLayer
+ - @ref CLElementwisePower
+ - @ref CLLogLayer
+ - @ref CLLSTMLayerQuantized
+ - @ref CLNegLayer
+ - @ref CLPReluLayer
+ - @ref CLSinLayer
+ - @ref CLBatchConcatenateLayerKernel
+ - @ref CLDepthToSpaceLayerKernel / @ref CLDepthToSpaceLayer
+ - @ref CLGEMMLowpMatrixMultiplyNativeKernel
+ - @ref CLGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel
+ - @ref CLGEMMMatrixMultiplyNativeKernel
+ - @ref CLMeanStdDevNormalizationKernel / @ref CLMeanStdDevNormalizationLayer
+ - @ref CLSpaceToDepthLayerKernel / @ref CLSpaceToDepthLayer
+ - New examples:
+ - neon_opticalflow
+ - cl_cache
+ - neon_permute
+ - Added support for FP16 in @ref NEDeconvolutionLayer
+ - Added support for FP16 in @ref CLDeconvolutionLayer
+ - Added support for REDUCE_MIN and REDUCE_MAX in @ref ReductionOperation
+ - Enable the fusion of batch normalization with convolution and depthwise convolution layer for FP32 in the graph API (OpenCL only)
+ - Added support for fusing activation function and broadcast addition with the matrix multiplication for FP32 (OpenCL only)
+ - Re-factored the depthwise convolution layer kernel on NEON for generic cases
+ - 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.
+ - 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
+
v19.05 Public major release
- Various bug fixes.
- Various optimisations.
@@ -271,13 +330,13 @@
- New OpenGLES kernels / functions:
- @ref GCConcatenateLayer
- Deprecated functions/interfaces
- - @ref GCDepthConcatenateLayer
- - @ref NEWidthConcatenateLayer
- - @ref NEDepthConcatenateLayer
- - @ref CLWidthConcatenateLayer
- - @ref CLDepthConcatenateLayer
- - @ref CLGEMMInterleave4x4
- - @ref CLGEMMTranspose1xW
+ - GCDepthConcatenateLayer
+ - NEWidthConcatenateLayer
+ - NEDepthConcatenateLayer
+ - CLWidthConcatenateLayer
+ - CLDepthConcatenateLayer
+ - CLGEMMInterleave4x4
+ - CLGEMMTranspose1xW
- Support different quantization info in CLConcatLayer.
- Add checks on different input/output quantization info were not supported.
- Tensors have different quantization information.
@@ -428,7 +487,7 @@
- Added documentation for add a new function or kernel.
- Improved doxygen documentation adding a list of the existing functions.
- Add 4D tensors support to
- - @ref CLWidthConcatenateLayer
+ - CLWidthConcatenateLayer
- @ref CLFlattenLayer
- @ref CLSoftmaxLayer
- Add dot product support for @ref CLDepthwiseConvolutionLayer3x3NHWCKernel non-unit stride
@@ -457,7 +516,7 @@
- Removed support for QS8/QS16 data types.
- Added support for grouped convolution in @ref CLConvolutionLayer.
- Added NHWC data layout support to:
- - @ref NEDepthConcatenateLayer / @ref CLDepthConcatenateLayer
+ - NEDepthConcatenateLayer / CLDepthConcatenateLayer
- @ref NEWinogradConvolutionLayer / @ref CLWinogradConvolutionLayer
- @ref CLDepthwiseConvolutionLayer
- @ref CLDirectConvolutionLayer
@@ -500,7 +559,7 @@
- @ref CLCopy / @ref CLCopyKernel
- @ref CLLSTMLayer
- @ref CLRNNLayer
- - @ref CLWidthConcatenateLayer / @ref CLWidthConcatenateLayerKernel
+ - CLWidthConcatenateLayer / @ref CLWidthConcatenateLayerKernel
- @ref CLWinogradFilterTransformKernel / @ref CLWinogradInputTransformKernel / @ref CLWinogradConvolutionLayer
- @ref CLWinogradInputTransformKernel / @ref CLWinogradInputTransform
- New Neon kernels / functions:
@@ -623,7 +682,7 @@
- @ref GCActivationLayerKernel / @ref GCActivationLayer
- @ref GCBatchNormalizationLayerKernel / @ref GCBatchNormalizationLayer
- @ref GCCol2ImKernel
- - @ref GCDepthConcatenateLayerKernel / @ref GCDepthConcatenateLayer
+ - @ref GCDepthConcatenateLayerKernel / GCDepthConcatenateLayer
- @ref GCDirectConvolutionLayerKernel / @ref GCDirectConvolutionLayer
- @ref GCDropoutLayerKernel / @ref GCDropoutLayer
- @ref GCFillBorderKernel / @ref GCFillBorder
@@ -692,7 +751,7 @@
- @ref CLDirectConvolutionLayerKernel / @ref CLDirectConvolutionLayer
- @ref CLFlattenLayer
- @ref CLFloorKernel / @ref CLFloor
- - @ref CLGEMMTranspose1xW
+ - CLGEMMTranspose1xW
- @ref CLGEMMMatrixVectorMultiplyKernel
- @ref CLL2NormalizeLayerKernel / @ref CLL2NormalizeLayer
- @ref CLQuantizationLayerKernel @ref CLMinMaxLayerKernel / @ref CLQuantizationLayer
@@ -711,7 +770,7 @@
- User can specify his own scheduler by implementing the @ref IScheduler interface.
- New OpenCL kernels / functions:
- @ref CLBatchNormalizationLayerKernel / @ref CLBatchNormalizationLayer
- - @ref CLDepthConcatenateLayerKernel / @ref CLDepthConcatenateLayer
+ - @ref CLDepthConcatenateLayerKernel / CLDepthConcatenateLayer
- @ref CLHOGOrientationBinningKernel @ref CLHOGBlockNormalizationKernel, @ref CLHOGDetectorKernel / @ref CLHOGDescriptor @ref CLHOGDetector @ref CLHOGGradient @ref CLHOGMultiDetection
- @ref CLLocallyConnectedMatrixMultiplyKernel / @ref CLLocallyConnectedLayer
- @ref CLWeightsReshapeKernel / @ref CLConvolutionLayerReshapeWeights
@@ -719,7 +778,7 @@
- @ref CPPDetectionWindowNonMaximaSuppressionKernel
- New NEON kernels / functions:
- @ref NEBatchNormalizationLayerKernel / @ref NEBatchNormalizationLayer
- - @ref NEDepthConcatenateLayerKernel / @ref NEDepthConcatenateLayer
+ - @ref NEDepthConcatenateLayerKernel / NEDepthConcatenateLayer
- @ref NEDirectConvolutionLayerKernel / @ref NEDirectConvolutionLayer
- @ref NELocallyConnectedMatrixMultiplyKernel / @ref NELocallyConnectedLayer
- @ref NEWeightsReshapeKernel / @ref NEConvolutionLayerReshapeWeights
@@ -770,7 +829,7 @@
v17.03 Sources preview
- New OpenCL kernels / functions:
- @ref CLGradientKernel, @ref CLEdgeNonMaxSuppressionKernel, @ref CLEdgeTraceKernel / @ref CLCannyEdge
- - GEMM refactoring + FP16 support: @ref CLGEMMInterleave4x4Kernel, @ref CLGEMMTranspose1xWKernel, @ref CLGEMMMatrixMultiplyKernel, @ref CLGEMMMatrixAdditionKernel / @ref CLGEMM
+ - GEMM refactoring + FP16 support: CLGEMMInterleave4x4Kernel, CLGEMMTranspose1xWKernel, @ref CLGEMMMatrixMultiplyKernel, @ref CLGEMMMatrixAdditionKernel / @ref CLGEMM
- @ref CLGEMMMatrixAccumulateBiasesKernel / @ref CLFullyConnectedLayer
- @ref CLTransposeKernel / @ref CLTranspose
- @ref CLLKTrackerInitKernel, @ref CLLKTrackerStage0Kernel, @ref CLLKTrackerStage1Kernel, @ref CLLKTrackerFinalizeKernel / @ref CLOpticalFlow
@@ -1236,20 +1295,20 @@
@subsubsection S3_5_1_ubuntu_on_windows Bash on Ubuntu on Windows
-The best and easiest option is to use
-<a href="https://msdn.microsoft.com/en-gb/commandline/wsl/about">Ubuntu on Windows</a>.
+The best and easiest option is to use
+<a href="https://msdn.microsoft.com/en-gb/commandline/wsl/about">Ubuntu on Windows</a>.
This feature is still marked as *beta* and thus might not be available.
However, if it is building the library is as simple as opening a *Bash on
Ubuntu on Windows* shell and following the general guidelines given above.
@subsubsection S3_5_2_cygwin Cygwin
-If the Windows subsystem for Linux is not available <a href="https://www.cygwin.com/">Cygwin</a>
-can be used to install and run `scons`. In addition to the default packages
-installed by Cygwin `scons` has to be selected in the installer. (`git` might
+If the Windows subsystem for Linux is not available <a href="https://www.cygwin.com/">Cygwin</a>
+can be used to install and run `scons`, the minimum Cygwin version must be 3.0.7 or later. In addition
+to the default packages installed by Cygwin `scons` has to be selected in the installer. (`git` might
also be useful but is not strictly required if you already have got the source
-code of the library.) Linaro provides pre-built versions of
-<a href="http://releases.linaro.org/components/toolchain/binaries/">GCC cross-compilers</a>
+code of the library.) Linaro provides pre-built versions of
+<a href="http://releases.linaro.org/components/toolchain/binaries/">GCC cross-compilers</a>
that can be used from the Cygwin terminal. When building for Android the
compiler is included in the Android standalone toolchain. After everything has
been set up in the Cygwin terminal the general guide on building the library