maxframe.tensor.multiply#
- maxframe.tensor.multiply(x1, x2, out=None, where=None, **kwargs)[source]#
Multiply arguments element-wise.
- Parameters:
x1 (array_like) – Input arrays to be multiplied.
x2 (array_like) – Input arrays to be multiplied.
out (Tensor, None, or tuple of Tensor and None, optional) – 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 tensor is returned. A tuple (possible only as a keyword argument) must have length equal to the number of outputs.
where (array_like, optional) – Values of True indicate to calculate the ufunc at that position, values of False indicate to leave the value in the output alone.
**kwargs
- Returns:
y – The product of x1 and x2, element-wise. Returns a scalar if both x1 and x2 are scalars.
- Return type:
Tensor
Notes
Equivalent to x1 * x2 in terms of array broadcasting.
Examples
>>> import maxframe.tensor as mt
>>> mt.multiply(2.0, 4.0).execute() 8.0
>>> x1 = mt.arange(9.0).reshape((3, 3)) >>> x2 = mt.arange(3.0) >>> mt.multiply(x1, x2).execute() array([[ 0., 1., 4.], [ 0., 4., 10.], [ 0., 7., 16.]])