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>
diff --git a/arm_compute/runtime/NEON/functions/NEGEMMAssemblyDispatch.h b/arm_compute/runtime/NEON/functions/NEGEMMAssemblyDispatch.h
index 2fc2cf4..b5a2978 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 @@
/** 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 @@
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
diff --git a/arm_compute/runtime/NEON/functions/assembly/NEGEMMInterleavedWrapper.h b/arm_compute/runtime/NEON/functions/assembly/NEGEMMInterleavedWrapper.h
index 9495647..ad89e1f 100644
--- a/arm_compute/runtime/NEON/functions/assembly/NEGEMMInterleavedWrapper.h
+++ b/arm_compute/runtime/NEON/functions/assembly/NEGEMMInterleavedWrapper.h
@@ -104,14 +104,14 @@
*
* @note The input and output tensor must have the same dimensions
*
- * @param[in] a Input tensor (Matrix A)
- * @param[in] b Input tensor (Matrix B)
- * @param[out] c 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 C matrix before adding product.
- * @param[in] pretranspose_b If true, pretranspose B once during the prepare() stage instead of on the fly every time.
+ * @param[in] a Input tensor (Matrix A)
+ * @param[in] b Input tensor (Matrix B)
+ * @param[out] c 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 C matrix before adding product.
+ * @param[in] gemm_info GEMM meta-data
*/
- void configure(const ITensor *a, const ITensor *b, ITensor *c, float alpha, float beta, bool pretranspose_b);
+ void configure(const ITensor *a, const ITensor *b, ITensor *c, float alpha, float beta, const GEMMInfo &gemm_info);
// Inherited methods overridden:
void run() override;