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authorGian Marco <gianmarco.iodice@arm.com>2017-11-21 10:57:50 +0000
committerAnthony Barbier <anthony.barbier@arm.com>2018-11-02 16:41:17 +0000
commit05288a2b871ef99f544771621c3bba409b2f70df (patch)
tree21e3d2a9927ef31f6d5bcdd5523c4c8e933047a6 /arm_compute/core/NEON/kernels/NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel.h
parentc82799003fbfdc5bb9526ff944e41eaae23e3f03 (diff)
downloadComputeLibrary-05288a2b871ef99f544771621c3bba409b2f70df.tar.gz
COMPMID-697 - Rework GEMMLowp interface on OpenCL
Reworked the interface of GemmLowp in order to make easy the integration in Android NN - Added support for different output stage - Added validation for both matrix multiplication and output stage - Added bounded relu support in the output stage - Added in32_t bias support - Added optimized path for vector by matrix case This rework is required for: - Convolution quantized - Fully connected quantized Change-Id: I512283d406099cf8c614dd89d0a97ed411143afc Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/110625 Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com> Tested-by: BSG Visual Compute Jenkins server to access repositories on http://mpd-gerrit.cambridge.arm.com <bsgcomp@arm.com>
Diffstat (limited to 'arm_compute/core/NEON/kernels/NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel.h')
-rw-r--r--arm_compute/core/NEON/kernels/NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel.h2
1 files changed, 1 insertions, 1 deletions
diff --git a/arm_compute/core/NEON/kernels/NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel.h b/arm_compute/core/NEON/kernels/NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel.h
index 7684350c0f..a522069330 100644
--- a/arm_compute/core/NEON/kernels/NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel.h
+++ b/arm_compute/core/NEON/kernels/NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel.h
@@ -30,7 +30,7 @@ namespace arm_compute
{
class ITensor;
-/* NEON kernel used to quantize down the int32 accumulator values of GEMMLowp to QASYMM8
+/** NEON kernel used to quantize down the int32 accumulator values of GEMMLowp to QASYMM8
*
* This kernel takes a final int32 accumulator value (the output of @ref NEGEMMLowpMatrixMultiplyKernel), and processes it to obtain the final QASYMM8 value.
* The following computations will be performed by the kernel: