mxnet.np.multiply¶
-
multiply
(x1, x2, out=None, **kwargs)¶ Multiply arguments element-wise.
- Parameters
x2 (x1,) – The arrays to be multiplied. If x1.shape != x2.shape, they must be broadcastable to a common shape (which may be the shape of one or the other).
out (ndarray) – A location into which the result is stored. If provided, it must have a shape that the inputs broadcast to. If not provided or None, a freshly-allocated array is returned.
- Returns
out (ndarray or scalar) – The difference of x1 and x2, element-wise. This is a scalar if both x1 and x2 are scalars.
.. note:: – This operator now supports automatic type promotion. The resulting type will be determined according to the following rules:
If both inputs are of floating number types, the output is the more precise type.
If only one of the inputs is floating number type, the result is that type.
If both inputs are of integer types (including boolean), not supported yet.
Examples
>>> np.multiply(2.0, 4.0) 8.0 >>> x1 = np.arange(9.0).reshape((3, 3)) >>> x2 = np.arange(3.0) >>> np.multiply(x1, x2) array([[ 0., 1., 4.], [ 0., 4., 10.], [ 0., 7., 16.]])