code: def pairwise_distances_no_broadcast(X, Y):
      """Utility function to calculate row-wise euclidean distance of two matrix.
      Different from pair-wise calculation, this function would not broadcast.
  
      For instance, X and Y are both (4,3) matrices, the function would return
      a distance vector with shape (4,), instead of (4,4).
  
      Parameters
      ----------
      X : array of shape (n_samples, n_features)
          First input samples
  
      Y : array of shape (n_samples, n_features)
          Second input samples
  
      Returns
      -------
      distance : array of shape (n_samples,)
          Row-wise euclidean distance of X and Y
      """
      X = check_array(X)
      Y = check_array(Y)
  
      if X.shape[0] != Y.shape[0] or X.shape[1] != Y.shape[1]:
          raise ValueError(
              "pairwise_distances_no_broadcast function receive"
              "matrix with different shapes {0} and {1}".format(
                  X.shape, Y.shape
              )
          )
      return _pairwise_distances_no_broadcast_helper(X, Y)
  
file_path: pyod/pyod/utils/stat_models.py
imports: from __future__ import division
  from __future__ import print_function
  import numpy
  from numba import njit
  from scipy.stats import pearsonr
  from sklearn.utils.validation import check_array
  from sklearn.utils.validation import check_consistent_length
label_desc: Use image node_id 1 for calling a global function with example usage: pairwise_distances_no_broadcast(X, Y) and returns: _pairwise_distances_no_broadcast_helper