code: def collate_fn(batch_data):
      graphs = []
      labels = []
      for g, l in batch_data:
          graphs.append(g)
          labels.append(l)
  
      labels = np.array(labels, dtype="int64").reshape(-1, 1)
  
      return graphs, labels
  
imports: import os
  import sys
  import numpy
  from sklearn.model_selection import StratifiedKFold
  import paddle
  from pgl.utils.data import Dataset
  from pgl.utils.data import Dataloader
  import pgl
  from pgl.utils.logger import log
label_desc: Use image node_id 3 for calling a global function with example usage: collate_fn(batch_data) and returns: graphs,  labels