code: def get_euclidean(x, y, **kwargs):
      m = x.shape[0]
      n = y.shape[0]
      distmat = (
          np.power(x, 2).sum(axis=1, keepdims=True).repeat(n, axis=1)
          + np.power(y, 2)
          .sum(axis=1, keepdims=True)
          .repeat(m, axis=1)
          .T
      )
      distmat -= np.dot(2 * x, y.T)
      return distmat
  
imports: from pptracking.python.mot.visualize import plot_tracking
  from python.visualize import visualize_attr
  import os
  import re
  import cv2
  import gc
  import numpy
  import pandas
  from tqdm import tqdm
  from functools import reduce
  import warnings
label_desc: Use image node_id 4 for calling a global function with example usage: get_euclidean(x, y) and returns: distmat