code: def _get_label_info(G, label_name):
      """Get and return information of labels from the input graph
  
      Parameters
      ----------
      G : Network X graph
      label_name : string
          Name of the target label
  
      Returns
      -------
      labels : numpy array, shape = [n_labeled_samples, 2]
          Array of pairs of labeled node ID and label ID
      label_dict : numpy array, shape = [n_classes]
          Array of labels
          i-th element contains the label corresponding label ID `i`
      """
      import numpy as np
  
      labels = []
      label_to_id = {}
      lid = 0
      for i, n in enumerate(G.nodes(data=True)):
          if label_name in n[1]:
              label = n[1][label_name]
              if label not in label_to_id:
                  label_to_id[label] = lid
                  lid += 1
              labels.append([i, label_to_id[label]])
      labels = np.array(labels)
      label_dict = np.array(
          [
              label
              for label, _ in sorted(
                  label_to_id.items(), key=lambda x: x[1]
              )
          ]
      )
      return (labels, label_dict)
  
imports: import networkx
label_desc: Use image node_id 3 for calling a global function with example usage: _get_label_info(G, label_name) and returns: labels,  label_dict