- mars.tensor.subtract(x1, x2, out=None, where=None, **kwargs)#
Subtract arguments, element-wise.
x1 (array_like) – The tensors to be subtracted from each other.
x2 (array_like) – The tensors to be subtracted from each other.
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.
y – The difference of x1 and x2, element-wise. Returns a scalar if both x1 and x2 are scalars.
- Return type
x1 - x2in terms of tensor broadcasting.
>>> import mars.tensor as mt
>>> mt.subtract(1.0, 4.0).execute() -3.0
>>> x1 = mt.arange(9.0).reshape((3, 3)) >>> x2 = mt.arange(3.0) >>> mt.subtract(x1, x2).execute() array([[ 0., 0., 0.], [ 3., 3., 3.], [ 6., 6., 6.]])