code: def corr(index_s, index_t):
      features_s = X[index_s]
      features_t = X[index_t]
      corr = np.einsum("ij,ij->i", features_s, features_t) / n_samples
      return corr
  
file_path: deepgraph/doc/source/tutorials/pairwise_correlations.py
imports: import os
  from multiprocessing import Pool
  import numpy
  import pandas
  import deepgraph
  from numpy.random import RandomState
label_desc: Use image node_id 1 for calling a global function with example usage: corr(index_s, index_t) and returns: corr