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

Return (x1 == x2) element-wise.

  • x1 (array_like) – Input tensors of the same shape.

  • x2 (array_like) – Input tensors of the same shape.

  • 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 array 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 – For other keyword-only arguments, see the ufunc docs.


out – Output tensor of bools, or a single bool if x1 and x2 are scalars.

Return type

Tensor or bool


>>> import mars.tensor as mt
>>> mt.equal([0, 1, 3], mt.arange(3)).execute()
array([ True,  True, False])

What is compared are values, not types. So an int (1) and a tensor of length one can evaluate as True:

>>> mt.equal(1, mt.ones(1))
array([ True])