code: def mahalanobis(x, y, vinv=_mock_identity):
      result = 0.0
  
      diff = np.empty(x.shape[0], dtype=np.float32)
  
      for i in range(x.shape[0]):
          diff[i] = x[i] - y[i]
  
      for i in range(x.shape[0]):
          tmp = 0.0
          for j in range(x.shape[0]):
              tmp += vinv[i, j] * diff[j]
          result += tmp * diff[i]
  
      return np.sqrt(result)
  
imports: import numba
  import numpy
  import scipy.stats
  from sklearn.metrics import pairwise_distances
label_desc: Use image node_id 16 for calling a global function with example usage: mahalanobis(x, y, vinv) and returns: np