`scipy.linalg._fblas:sgemm`

Signature

def sgemm(alpha, a, b, beta = 0.0, c = None, trans_a = 0, trans_b = 0, overwrite_c = 0)

Compute the matrix-matrix product c = alpha*op(a)@op(b) + beta*c (BLAS sgemm).

alpha : float: Scalar multiplier for the product.
a : ndarray: First input matrix.
b : ndarray: Second input matrix.
beta : float, optional: Scalar multiplier for c. Default is 0.
c : ndarray, optional: Input/output matrix; if omitted a new zero matrix is allocated. Default is None.
trans_a : int, optional: Operation on a: 0 none, 1 transpose, 2 conjugate transpose. Default is 0.
trans_b : int, optional: Operation on b: 0 none, 1 transpose, 2 conjugate transpose. Default is 0.
overwrite_c : int, optional: If nonzero, c may be overwritten in place. Default is 0.

c : ndarray: The matrix alpha*op(a)@op(b) + beta*c, where op(x) is x, x.T, or x.conj().T according to trans_a / trans_b.