Function: hgemm
C Prototype |
aclError aclblasHgemm(aclTransType transA, aclTransType transB, aclTransType transC, int m, int n, int k, const aclFloat16 *alpha, const aclFloat16 *matrixA, int lda, const aclFloat16 *matrixB, int ldb, const aclFloat16 *beta, aclFloat16 *matrixC, int ldc, aclComputeType type, aclrtStream stream) |
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Python Function |
ret = acl.blas.hgemm(trans_a, trans_b, trans_c, m, n, k, alpha, matrix_a, lda, matrix_b, ldb, beta, matrix_c, ldc, type, stream) |
Function Usage |
Computes matrix-matrix multiplication. The input and output data type is aclFloat16. It is an asynchronous interface. C = αAB + βC |
Input Description |
trans_a: int, whether matrix A is transposed. trans_b: int, whether matrix B is transposed. trans_c: int, transpose flag of matrix C. Currently, only aclTrans_N is supported. m: int, number of rows in matrix A and C. n: int, number of columns in matrix B and C. k: int, number of columns in matrix A and number of rows in matrix B. alpha: int, address of data pointer of Scalar alpha used for executing the multiplication operation. matrix_a: int, address of data pointer of matrix A. lda: int, leading dimension of matrix A. For row-major transpose, lda is the number of columns of matrix A. matrix_b: int, address of data pointer of matrix B. ldb: int, leading dimension of matrix B. For row-major transpose, leading dimension is the number of columns of matrix B. beta: int, address of data pointer of Scalar β used for executing the multiplication operation. matrix_c: int, address of data pointer of matrix C. ldc: int, leading dimension of matrix C (reserved). type: int, calculation precision. stream: int, stream where the operator is executed. |
Return Value |
ret: int, error code.
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Restrictions |
None |
Precautions |
None |