mars.tensor.add#

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

Add arguments element-wise.

Parameters

  • x1 (array_like) – The tensors to be added. If x1.shape != x2.shape, they must be broadcastable to a common shape (which may be the shape of one or the other).

  • x2 (array_like) – The tensors to be added. If x1.shape != x2.shape, they must be broadcastable to a common shape (which may be the shape of one or the 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 –

Returns

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

Return type

Tensor or scalar

Notes

Equivalent to x1 + x2 in terms of tensor broadcasting.

Examples

>>> import mars.tensor as mt

>>> mt.add(1.0, 4.0).execute()
5.0
>>> x1 = mt.arange(9.0).reshape((3, 3))
>>> x2 = mt.arange(3.0)
>>> mt.add(x1, x2).execute()
array([[  0.,   2.,   4.],
       [  3.,   5.,   7.],
       [  6.,   8.,  10.]])