code: def batch_fn(self, batch_ex):
      batch_src = []
      batch_dst = []
      join_graph = []
      cc = 0
      batch_node_id = []
      batch_labels = []
      for ex in batch_ex:
          batch_src.append(ex.src)
          batch_dst.append(ex.dst)
          batch_labels.append(ex.label)
  
      if self.phase == "train":
          for num in range(1):
              rand_src = np.random.randint(
                  low=0, high=self.num_nodes, size=len(batch_ex)
              )
              rand_dst = np.random.randint(
                  low=0, high=self.num_nodes, size=len(batch_ex)
              )
              batch_src = batch_src + rand_src.tolist()
              batch_dst = batch_dst + rand_dst.tolist()
              batch_labels = (
                  batch_labels
                  + np.zeros_like(rand_src, dtype="int64").tolist()
              )
  
      feed_dict = {}
  
      feed_dict["batch_src"] = np.array(batch_src, dtype="int64")
      feed_dict["batch_dst"] = np.array(batch_dst, dtype="int64")
      feed_dict["labels"] = np.array(batch_labels, dtype="int64")
      return feed_dict
  
file_path: PGL/ogb_examples/linkproppred/ogbl-ppa/dataloader/ogbl_ppa_dataloader.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from __future__ import unicode_literals
  from __future__ import absolute_import
  from dataloader.base_dataloader import BaseDataGenerator
  import ssl
  from ogb.linkproppred import LinkPropPredDataset
  from ogb.linkproppred import Evaluator
  import tqdm
  from collections import namedtuple
  import pgl
  import numpy
label_desc: Use image node_id 2 for calling the PPADataGenerator obj's underlying member method code with example usage: obj.batch_fn(batch_ex) and returns: feed_dict