# mars.tensor.bitwise_xor¶

mars.tensor.bitwise_xor(x1, x2, out=None, where=None, **kwargs)

Compute the bit-wise XOR of two arrays element-wise.

Computes the bit-wise XOR of the underlying binary representation of the integers in the input arrays. This ufunc implements the C/Python operator ^.

x1, x2 : array_like
Only integer and boolean types are handled.
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

out : array_like
Result.

logical_xor bitwise_and bitwise_or binary_repr :

Return the binary representation of the input number as a string.

The number 13 is represented by 00001101. Likewise, 17 is represented by 00010001. The bit-wise XOR of 13 and 17 is therefore 00011100, or 28:

>>> import mars.tensor as mt

>>> mt.bitwise_xor(13, 17).execute()
28

>>> mt.bitwise_xor(31, 5).execute()
26
>>> mt.bitwise_xor([31,3], 5).execute()
array([26,  6])

>>> mt.bitwise_xor([31,3], [5,6]).execute()
array([26,  5])
>>> mt.bitwise_xor([True, True], [False, True]).execute()
array([ True, False])