code: def bitxor(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 ``^``.
  
      Parameters
      ----------
      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
  
      Returns
      -------
      out : array_like
          Result.
  
      See Also
      --------
      logical_xor
      bitwise_and
      bitwise_or
      binary_repr :
          Return the binary representation of the input number as a string.
  
      Examples
      --------
      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])
      """
      op = TensorBitxor(**kwargs)
      return op(x1, x2, out=out, where=where)
  
file_path: mars/mars/tensor/arithmetic/bitxor.py
imports: import numpy
  from ...None import opcodes
  from ..utils import infer_dtype
  from .core import TensorBinOp
  from .utils import arithmetic_operand
label_desc: Use image node_id 1 for calling a global function with example usage: bitxor(x1, x2, out, where) and returns: op