Function mult

python/singa/tensor.py:1302–1332

Do matrix-matrix or matrix-vector multiplication. This function returns C = alpha * A * B + beta * C Currently below cases are supported case 1 - matrix * vector: A (Tensor): 2d Tensor B (Tensor): 1d Tensor, GEMV would be invoked case 2 - matrix * matr

(A, B, C=None, alpha=1.0, beta=0.0)

def mult(A, B, C=None, alpha=1.0, beta=0.0):
    '''Do matrix-matrix or matrix-vector multiplication.
    This function returns C = alpha * A * B + beta * C
    Currently below cases are supported
        case 1 - matrix * vector:
            A (Tensor): 2d Tensor
            B (Tensor): 1d Tensor, GEMV would be invoked
        case 2 - matrix * matrix:
            A (Tensor): 2d Tensor
            B (Tensor): 2d Tensor, GEMM would be invoked
        case 3 - batched matrix * batched matrix:
            A (Tensor): 3/4d Tensor
            B (Tensor): 3/4d Tensor, batched GEMM would be invoked
            Where first/first and second dimension(s) of A, B should be exactly the same
            e.g. C{2,3,4,6} = A{2,3,4,5} * B{2,3,5,6}

    Args:
        A: n-d tensor
        B: n-d tensor
        C (Tensor, optional): for storing the result; If None, a new Tensor would be created.
        alpha (float): scaling factor
        beta (float): scaling factor

    Returns:
        the result Tensor
    '''
    if C is None:
        return _call_singa_func(singa.Mult, A.data, B.data)
    else:
        singa.MultWithScale(alpha, A.data, B.data, beta, C.data)
        return C


def einsum(ops, *args):