code: def setxor1d(ar1, ar2, assume_unique=False):
      """Find the set exclusive-or of two arrays.
  
      Parameters
      ----------
      ar1, ar2 : cupy.ndarray
          Input arrays. They are flattend if they are not already 1-D.
      assume_unique : bool
          By default, False, i.e. input arrays are not unique.
          If True, input arrays are assumed to be unique. This can
          speed up the calculation.
  
      Returns
      -------
      setxor1d : cupy.ndarray
          Return the sorted, unique values that are in only one
          (not both) of the input arrays.
  
      See Also
      --------
      numpy.setxor1d
  
      """
      if not assume_unique:
          ar1 = cupy.unique(ar1)
          ar2 = cupy.unique(ar2)
  
      aux = cupy.concatenate((ar1, ar2), axis=None)
      if aux.size == 0:
          return aux
  
      aux.sort()
  
      return aux[
          _setxorkernel(
              aux, aux.size, cupy.zeros(aux.size, dtype=cupy.bool_)
          )
      ]
  
file_path: cupy/cupy/_logic/truth.py
imports: import warnings
  import cupy
  from cupy._core import _routines_logic
  from cupy._core import _fusion_thread_local
  from cupy._sorting import search
  from cupy import _util
label_desc: Use image node_id 7 for calling a global function with example usage: setxor1d(ar1, ar2, assume_unique) and returns: aux, aux