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author | Michele Di Giorgio <michele.digiorgio@arm.com> | 2020-03-12 19:34:33 +0000 |
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committer | Michele Di Giorgio <michele.digiorgio@arm.com> | 2020-03-16 09:42:36 +0000 |
commit | a602f03f4c66e5ee2480f1a3fc66847968fc1076 (patch) | |
tree | a2752ca0de84f7920dd7296151d14e5edc8cacc0 /arm_compute/runtime | |
parent | 0ec53a0e54ae0be0ed9c4e4c14a5fd10ed5f48a8 (diff) | |
download | ComputeLibrary-a602f03f4c66e5ee2480f1a3fc66847968fc1076.tar.gz |
COMPMID-3237: Extend GEMMLowpReduction kernels to multiply reductions by a scalar value
Change-Id: If2a242f52aea753591525d30a4cb64c1a766bf8d
Signed-off-by: Michele Di Giorgio <michele.digiorgio@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/2881
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Sang-Hoon Park <sang-hoon.park@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Diffstat (limited to 'arm_compute/runtime')
-rw-r--r-- | arm_compute/runtime/NEON/functions/NEGEMM.h | 4 | ||||
-rw-r--r-- | arm_compute/runtime/NEON/functions/NEGEMMConvolutionLayer.h | 10 |
2 files changed, 7 insertions, 7 deletions
diff --git a/arm_compute/runtime/NEON/functions/NEGEMM.h b/arm_compute/runtime/NEON/functions/NEGEMM.h index c87e806d0c..8dc6b88bb0 100644 --- a/arm_compute/runtime/NEON/functions/NEGEMM.h +++ b/arm_compute/runtime/NEON/functions/NEGEMM.h @@ -74,7 +74,7 @@ public: * @note GEMM: General Matrix Multiply - [alpha * A * B + beta * C]. * @note GEMM: The tensors a, b, c, d must have the same data type. You should not mix data types when calling this function. * - * @param[in] a First input tensor (Matrix A or Vector A). Data type supported: BLOAT16/F16/F32 + * @param[in] a First input tensor (Matrix A or Vector A). Data type supported: BFLOAT16/F16/F32 * @param[in] b Second input tensor (Matrix B). Data type supported: same as @p a * @param[in] c Third input tensor (Matrix C). It can be a nullptr if just the multiplication between @p a and @p b is needed. Data type supported: same as @p a * @param[out] d Output tensor. Data type supported: same as @p a @@ -86,7 +86,7 @@ public: void configure(const ITensor *a, const ITensor *b, const ITensor *c, ITensor *d, float alpha, float beta, const GEMMInfo &gemm_info = GEMMInfo()); /** Static function to check if given info will lead to a valid configuration of @ref NEGEMM. * - * @param[in] a First input tensor info (Matrix or Vector A). Data types supported: BLOAT16/F16/F32 + * @param[in] a First input tensor info (Matrix or Vector A). Data types supported: BFLOAT16/F16/F32 * @param[in] b Second input tensor info (Matrix B). Data type supported: same as @p a. * @param[in] c Third input tensor info (Matrix C). It can be a nullptr if just the multiplication between @p a and @p b is needed. Data type supported: same as @p a. * @param[out] output Output tensor info. Data type supported: same as @p a diff --git a/arm_compute/runtime/NEON/functions/NEGEMMConvolutionLayer.h b/arm_compute/runtime/NEON/functions/NEGEMMConvolutionLayer.h index 5368384b19..e7da1006e0 100644 --- a/arm_compute/runtime/NEON/functions/NEGEMMConvolutionLayer.h +++ b/arm_compute/runtime/NEON/functions/NEGEMMConvolutionLayer.h @@ -66,9 +66,9 @@ public: * @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. * Data type supported: QASYMM8/QASYMM8_SIGNED/QSYMM8_PER_CHANNEL/BFLOAT16/F16/F32. * @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. - * Data type supported: Same as @p weights, S32 if @p weights is QASYMM8/QASYMM8_SIGNED, FP32 if @p weights is BLOAT16 + * Data type supported: Same as @p weights, S32 if @p weights is QASYMM8/QASYMM8_SIGNED, FP32 if @p weights is BFLOAT16 * @param[out] output Destination tensor. - * Data types supported: Same as @p weights, FP32 if @p weights is BLOAT16 + * Data types supported: Same as @p weights, FP32 if @p weights is BFLOAT16 */ void configure(const ITensor *weights, const ITensor *biases, ITensor *output); /** Static function to check if given info will lead to a valid configuration of @ref NEConvolutionLayerReshapeWeights @@ -76,9 +76,9 @@ public: * @param[in] weights Weights tensor info. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. * Data type supported: QASYMM8/QASYMM8_SIGNED/QSYMM8_PER_CHANNEL/BFLOAT16/F16/F32. * @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. - * Data type supported: Same as @p weights, S32 if @p weights is QASYMM8/QASYMM8_SIGNED, FP32 if @p weights is BLOAT16 + * Data type supported: Same as @p weights, S32 if @p weights is QASYMM8/QASYMM8_SIGNED, FP32 if @p weights is BFLOAT16 * @param[in] output Destination tensor. - * Data types supported: Same as @p weights FP32 if @p weights is BLOAT16 + * Data types supported: Same as @p weights FP32 if @p weights is BFLOAT16 * * @return an error status */ @@ -140,7 +140,7 @@ private: /** Basic function to compute the convolution layer. This function calls the following NEON kernels/functions: * * -# @ref NEIm2ColKernel - * -# @ref NEGEMM (if the data type is BLOAT16/FP16/FP32) + * -# @ref NEGEMM (if the data type is BFLOAT16/FP16/FP32) * -# @ref NEGEMMLowpMatrixMultiplyCore (if the data type is QASYMM8/QASYMM8_SIGNED) * -# @ref NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint (if the data type is QASYMM8/QASYMM8_SIGNED) * -# @ref NEArithmeticAdditionKernel (if biases != nullptr and we have a 1x1 convolution with the NHWC data layout) |