code: def jensenshannon(u, v):
      """Compute the Jensen-Shannon distance between two 1-D arrays.
  
      The Jensen-Shannon distance is defined as
  
      .. math::
          d(u, v) = \\sqrt{\\frac{KL(u \\| m) + KL(v \\| m)}{2}}
  
      where :math:`KL` is the Kullback-Leibler divergence and :math:`m` is the
      pointwise mean of `u` and `v`.
  
      Args:
          u (array_like): Input array of size (N,)
          v (array_like): Input array of size (N,)
  
      Returns:
          jensenshannon (double): The Jensen-Shannon distance between
          vectors `u` and `v`.
      """
      if not pylibraft_available:
          raise RuntimeError("pylibraft is not installed")
      u = cupy.asarray(u)
      v = cupy.asarray(v)
      output_arr = cupy.zeros((1,), dtype=u.dtype)
      pairwise_distance(u, v, output_arr, "jensenshannon")
  
      return output_arr[0]
  
imports: import cupy
label_desc: Use image node_id 11 for calling a global function with example usage: jensenshannon(u, v) and returns: output_arr