code: def _generate_random_data_sample(
      sample_size, feature_dim, num_classes
  ):
      Y = np.random.randint(
          size=(sample_size, 1), low=0, high=num_classes
      )
      X = (np.random.randn(sample_size, feature_dim) + 3) * (Y + 1)
      X = X.astype(np.float32)
      class_ind = [
          Y == class_number for class_number in range(num_classes)
      ]
      Y = np.asarray(np.hstack(class_ind), dtype=np.float32)
      return X, Y
  
file_path: CNTK/bindings/python/cntk/contrib/netopt/test/factorization_test.py
imports: import numpy
  import pytest
  import cntk
  import cntk.contrib.netopt.factorization
label_desc: Use image node_id 5 for calling a global function with example usage: _generate_random_data_sample(sample_size, feature_dim, num_classes) and returns: X,  Y