code: def canberra_grad(x, y):
      result = 0.0
      grad = np.zeros(x.shape)
      for i in range(x.shape[0]):
          denominator = np.abs(x[i]) + np.abs(y[i])
          if denominator > 0:
              result += np.abs(x[i] - y[i]) / denominator
              grad[i] = (
                  np.sign(x[i] - y[i]) / denominator
                  - np.abs(x[i] - y[i])
                  * np.sign(x[i])
                  / denominator**2
              )
  
      return result, grad
  
imports: import numba
  import numpy
  import scipy.stats
  from sklearn.metrics import pairwise_distances
label_desc: Use image node_id 20 for calling a global function with example usage: canberra_grad(x, y) and returns: result,  grad