code: def _full_batch_wapper(ds):
      feed_dict = {}
      feed_dict["batch_nodes"] = np.array(ds.nodes_idx, dtype="int64")
      feed_dict["labels"] = np.array(ds.labels, dtype="int64")
  
      def r():
          yield feed_dict
  
      return r
  
file_path: PGL/ogb_examples/nodeproppred/ogbn-arxiv/GaAN/monitor/train_monitor.py
imports: import tqdm
  import json
  import numpy
  import sys
  import os
  import paddle.fluid
  from tensorboardX import SummaryWriter
  from ogb.nodeproppred import Evaluator
  from ogb.nodeproppred import NodePropPredDataset
label_desc: Use image node_id 4 for calling a global function with example usage: _full_batch_wapper(ds) and returns: r