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author | Gian Marco Iodice <gianmarco.iodice@arm.com> | 2017-06-30 12:21:00 +0100 |
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committer | Anthony Barbier <anthony.barbier@arm.com> | 2018-09-17 14:15:39 +0100 |
commit | bdb6b0bb156588dc39fd5084d4c91d05b5148610 (patch) | |
tree | bb3c3645dd9abbf20462dace7828bb7ec459dc4d /arm_compute/core/NEON/kernels/NEGEMMMatrixMultiplyKernel.h | |
parent | ac69aa137e360340fe9f148f019d93af6c3d8336 (diff) | |
download | ComputeLibrary-bdb6b0bb156588dc39fd5084d4c91d05b5148610.tar.gz |
COMPMID-433 - Port NEGEMM to support 16 bit fixed point
Change-Id: I82de74d7027bbc8a00a4d6671e968785280d5f6c
Reviewed-on: http://mpd-gerrit.cambridge.arm.com/79498
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
Tested-by: Kaizen <jeremy.johnson+kaizengerrit@arm.com>
Reviewed-by: Moritz Pflanzer <moritz.pflanzer@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
Diffstat (limited to 'arm_compute/core/NEON/kernels/NEGEMMMatrixMultiplyKernel.h')
-rw-r--r-- | arm_compute/core/NEON/kernels/NEGEMMMatrixMultiplyKernel.h | 2 |
1 files changed, 1 insertions, 1 deletions
diff --git a/arm_compute/core/NEON/kernels/NEGEMMMatrixMultiplyKernel.h b/arm_compute/core/NEON/kernels/NEGEMMMatrixMultiplyKernel.h index a684945828..e82fc6f5d7 100644 --- a/arm_compute/core/NEON/kernels/NEGEMMMatrixMultiplyKernel.h +++ b/arm_compute/core/NEON/kernels/NEGEMMMatrixMultiplyKernel.h @@ -54,7 +54,7 @@ public: * @note If the output tensor is a matrix, the input matrices @p input0 and @p input1 should be the output of the kernels: @ref NEGEMMInterleave4x4Kernel and @ref NEGEMMTranspose1xWKernel * These two kernels change the layout of the original matrices to be more cache-friendly. * - * @param[in] input0 Input tensor containing the interleaved Matrix A or the vector A. Data types supported: F16/F32 + * @param[in] input0 Input tensor containing the interleaved Matrix A or the vector A. Data types supported: QS8/QS16/F16/F32 * @param[in] input1 Input tensor containing the transposed Matrix B if the first input tensor A is not a vector. * If the output tensor is a vector, input1 must contain the matrix B not reshaped. Data type supported: same as @p input0 * @param[out] output Output tensor to store the result of matrix multiplication. Data type supported: same as @p input0. |