class_docstr: load the FB15K
docstr: faster, no filter for exists triples
code: def training_data_no_filter(self, train_triple_positive):
      """faster, no filter for exists triples"""
      size = len(train_triple_positive) * self._neg_times
      train_triple_negative = train_triple_positive.repeat(
          self._neg_times, axis=0
      )
      replace_head_probability = 0.5 * np.ones(size)
      replace_entity_id = np.random.randint(
          self.entity_total, size=size
      )
      random_num = np.random.random(size=size)
      index_t = (random_num < replace_head_probability) * 1
      train_triple_negative[:, 0] = (
          train_triple_negative[:, 0]
          + (replace_entity_id - train_triple_negative[:, 0]) * index_t
      )
      train_triple_negative[:, 2] = (
          replace_entity_id
          + (train_triple_negative[:, 2] - replace_entity_id) * index_t
      )
      train_triple_positive = np.expand_dims(
          train_triple_positive, axis=2
      )
      train_triple_negative = np.expand_dims(
          train_triple_negative, axis=2
      )
      return train_triple_positive, train_triple_negative
  
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 3 for calling the KGLoader obj's underlying member method code with example usage: obj.training_data_no_filter(train_triple_positive) and returns: train_triple_positive,  train_triple_negative