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author | Georgios Pinitas <georgios.pinitas@arm.com> | 2019-06-21 18:43:12 +0100 |
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committer | Georgios Pinitas <georgios.pinitas@arm.com> | 2019-07-05 15:30:24 +0000 |
commit | 37d080f2f11cfd734104b76512e1fb191486216e (patch) | |
tree | d5df067c826aacc0676e7e9557a54b61a9a3b7eb /arm_compute/runtime/NEON/functions/NEGEMMAssemblyDispatch.h | |
parent | 11de30da8a9f79943255ddba7bb70a66b076673b (diff) | |
download | ComputeLibrary-37d080f2f11cfd734104b76512e1fb191486216e.tar.gz |
COMPMID-2378: Sanitize GEMM configuration for NEON
Change-Id: I7859b82b2059e14685f8792424648ac5eacd67f1
Signed-off-by: Georgios Pinitas <georgios.pinitas@arm.com>
Reviewed-on: https://review.mlplatform.org/c/1418
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Michele Di Giorgio <michele.digiorgio@arm.com>
Reviewed-by: Michalis Spyrou <michalis.spyrou@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Diffstat (limited to 'arm_compute/runtime/NEON/functions/NEGEMMAssemblyDispatch.h')
-rw-r--r-- | arm_compute/runtime/NEON/functions/NEGEMMAssemblyDispatch.h | 46 |
1 files changed, 23 insertions, 23 deletions
diff --git a/arm_compute/runtime/NEON/functions/NEGEMMAssemblyDispatch.h b/arm_compute/runtime/NEON/functions/NEGEMMAssemblyDispatch.h index 2fc2cf4a99..b5a2978ea1 100644 --- a/arm_compute/runtime/NEON/functions/NEGEMMAssemblyDispatch.h +++ b/arm_compute/runtime/NEON/functions/NEGEMMAssemblyDispatch.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2018 ARM Limited. + * Copyright (c) 2018-2019 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -64,17 +64,17 @@ private: /** If supported create the ACL function corresponding to the GemmMethod provided to process the other passed parameters * - * @param[in] method GemmMethod to use to perform the matrix multiplication. - * @param[in] a Input tensor (Matrix A). - * @param[in] b Input tensor (Matrix B). - * @param[out] d Output tensor to store the result of matrix multiplication. Data type supported: same as @p input0. - * @param[in] alpha Scalar multiplier to apply to AB matrix product. - * @param[in] beta Scalar multiplier to apply to input D matrix before adding product. - * @param[in] pretransposed_hint Can the B tensor can be pretransposed (ie shared across invocations)? + * @param[in] method GemmMethod to use to perform the matrix multiplication. + * @param[in] a Input tensor (Matrix A). + * @param[in] b Input tensor (Matrix B). + * @param[out] d Output tensor to store the result of matrix multiplication. Data type supported: same as @p input0. + * @param[in] alpha Scalar multiplier to apply to AB matrix product. + * @param[in] beta Scalar multiplier to apply to input D matrix before adding product. + * @param[in] gemm_info GEMM meta-data * * @return True if the method is supported and the function was successfully created, false otherwise. */ - bool create_function(arm_gemm::GemmMethod method, const ITensor *a, const ITensor *b, ITensor *d, float alpha, float beta, bool pretranspose_hint); + bool create_function(arm_gemm::GemmMethod method, const ITensor *a, const ITensor *b, ITensor *d, float alpha, float beta, const GEMMInfo &gemm_info); /** Interface for the arm_gemm fallback */ std::unique_ptr<IFallback> _arm_gemm; @@ -83,27 +83,27 @@ private: public: /** If supported create an ACL function else fallback to the arm_gemm function. * - * @param[in] a Input tensor (Matrix A) - * @param[in] b Input tensor (Matrix B) - * @param[out] d Output tensor to store the result of matrix multiplication. Data type supported: same as @p input0. - * @param[in] alpha Scalar multiplier to apply to AB matrix product. - * @param[in] beta Scalar multiplier to apply to input D matrix before adding product. - * @param[in] pretranspose_hint Can the B tensor can be pretransposed (ie shared across invocations)? + * @param[in] a Input tensor (Matrix A) + * @param[in] b Input tensor (Matrix B) + * @param[out] d Output tensor to store the result of matrix multiplication. Data type supported: same as @p input0. + * @param[in] alpha Scalar multiplier to apply to AB matrix product. + * @param[in] beta Scalar multiplier to apply to input D matrix before adding product. + * @param[in] gemm_info GEMM meta-data */ - void configure(const ITensor *a, const ITensor *b, ITensor *d, float alpha, float beta, bool pretranspose_hint); + void configure(const ITensor *a, const ITensor *b, ITensor *d, float alpha, float beta, const GEMMInfo &gemm_info); /** Indicates whether or not this function can be used to process the given parameters. * - * @param[in] a Input tensor (Matrix A) - * @param[in] b Input tensor (Matrix B) - * @param[in] d Output tensor to store the result of matrix multiplication. Data type supported: same as @p input0. - * @param[in] alpha Scalar multiplier to apply to AB matrix product. - * @param[in] beta Scalar multiplier to apply to input D matrix before adding product. - * @param[in] pretranspose_hint Can the B tensor can be pretransposed (ie shared across invocations)? + * @param[in] a Input tensor (Matrix A) + * @param[in] b Input tensor (Matrix B) + * @param[in] d Output tensor to store the result of matrix multiplication. Data type supported: same as @p input0. + * @param[in] alpha Scalar multiplier to apply to AB matrix product. + * @param[in] beta Scalar multiplier to apply to input D matrix before adding product. + * @param[in] gemm_info GEMM meta-data * * @return a status. */ - static Status validate(const ITensorInfo *a, const ITensorInfo *b, const ITensorInfo *d, float alpha, float beta, bool pretranspose_hint); + static Status validate(const ITensorInfo *a, const ITensorInfo *b, const ITensorInfo *d, float alpha, float beta, const GEMMInfo &gemm_info); /** Was the function successfully configured ? * * @return True if the function is configured and ready to run |