code: def chebyshev_grad(x, y):
      r"""Chebyshev or l-infinity distance with gradient.
  
      ..math::
          D(x, y) = \max_i |x_i - y_i|
      """
      result = 0.0
      max_i = 0
      for i in range(x.shape[0]):
          v = np.abs(x[i] - y[i])
          if v > result:
              result = v
              max_i = i
      grad = np.zeros(x.shape)
      grad[max_i] = np.sign(x[max_i] - y[max_i])
  
      return result, grad
  
imports: import numba
  import numpy
  import scipy.stats
  from sklearn.metrics import pairwise_distances
label_desc: Use image node_id 9 for calling a global function with example usage: chebyshev_grad(x, y) and returns: result,  grad