class_docstr: load the FB15K
docstr: train_triple_positive
  :return:
code: def training_data_batch(self):
      """
      train_triple_positive
      :return:
      """
      n = len(self._triple_train)
      rand_idx = np.random.permutation(n)
      n_triple = len(rand_idx)
      start = 0
      while start < n_triple:
          end = min(start + self._batch_size, n_triple)
          train_triple_positive = self._triple_train[
              rand_idx[start:end]
          ]
          start = end
          yield train_triple_positive
  
file_path: PGL/legacy/examples/pgl-ke/data_loader.py
imports: import os
  import numpy
  from collections import defaultdict
  from pgl.utils.logger import log
label_desc: Use image node_id 5 for calling the KGLoader obj's underlying member method code with example usage: obj.training_data_batch() without return types