code: def create_loader(datasets):
      loader_train = DataLoader(
          datasets[0],
          collate_fn=Batch.collate(),
          batch_size=cfg.train.batch_size,
          shuffle=True,
          num_workers=cfg.num_workers,
          pin_memory=False,
      )
  
      loaders = [loader_train]
      for i in range(1, len(datasets)):
          loaders.append(
              DataLoader(
                  datasets[i],
                  collate_fn=Batch.collate(),
                  batch_size=cfg.train.batch_size,
                  shuffle=False,
                  num_workers=cfg.num_workers,
                  pin_memory=False,
              )
          )
  
      return loaders
  
imports: import logging
  import pickle
  import time
  import networkx
  import torch
  import torch_geometric.transforms
  from deepsnap.batch import Batch
  from deepsnap.dataset import GraphDataset
  from ogb.graphproppred import PygGraphPropPredDataset
  from torch.utils.data import DataLoader
  from torch_geometric.datasets import PPI, Amazon, Coauthor, KarateClub, MNISTSuperpixels, Planetoid, QM7b, TUDataset
  import graphgym.models.feature_augment
  import graphgym.register
  from graphgym.config import cfg
  from graphgym.models.transform import edge_nets, ego_nets, path_len, remove_node_feature
label_desc: Use image node_id 9 for calling a global function with example usage: create_loader(datasets) and returns: loaders