mars.tensor.subtract(x1, x2, out=None, where=None, **kwargs)[source]#

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.

  • **kwargs


y – The difference of x1 and x2, element-wise. Returns a scalar if both x1 and x2 are scalars.

Return type



Equivalent to x1 - x2 in terms of tensor broadcasting.


>>> import mars.tensor as mt
>>> mt.subtract(1.0, 4.0).execute()
>>> 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.]])