class_docstr: Implementation of knowledge graph interface in pglke.
  
  Args:
      triplets (dict):
          Triplet data of knowledge graphs with keys 'train', 'valid' and 'test'.
      num_ents (int, optional):
          Number of entities in a knowledge graph.
          If not provided, it will be inferred from triplets.
      num_rels (int, optional):
          Number of relations in a knowledge graph.
          If not provided, it will be inferred from triplets.
      ent_feat (np.ndarray, optional):
          Entity features, which have consistent order with entity ids.
      rel_feat (np.ndarray, optional):
          Relation features, which have consistent order with relation ids.
docstr: Count the number of relations.
          
docstr_tok: ["Count","the","number","of","relations","."]
code: def maybe_num_rels(self):
      """Count the number of relations."""
      rels = []
  
      def extract_rels(data):
          """Extract relations from data."""
          if isinstance(data, dict):
              rels.append(np.unique(data["r"]))
          elif isinstance(data, np.ndarray):
              rels.append(np.unique(data[:, 1]))
  
      extract_rels(self._train)
      extract_rels(self._valid)
      extract_rels(self._test)
      num_rels = np.unique(np.concatenate(rels)).shape[0]
      return num_rels
  
imports: import os
  import json
  from collections import defaultdict
  import numpy
label_desc: Use image node_id 4 for calling the TriGraph obj's underlying member method code with example usage: obj.maybe_num_rels() and returns: num_rels