code: def collate_dgl(samples):
      graphs, labels = map(list, zip(*samples))
      batched_graph = dgl.batch(graphs)
      labels = torch.stack(labels)
  
      return batched_graph, labels
  
file_path: dgl/examples/pytorch/ogb_lsc/PCQM4M/main.py
imports: import argparse
  import os
  import random
  import dgl
  import numpy
  import torch
  import torch.optim
  from gnn import GNN
  from ogb.lsc import DglPCQM4MDataset, PCQM4MEvaluator
  from torch.optim.lr_scheduler import StepLR
  from torch.utils.data import DataLoader
  from torch.utils.tensorboard import SummaryWriter
  from tqdm import tqdm
label_desc: Use image node_id 1 for calling a global function with example usage: collate_dgl(samples) and returns: batched_graph,  labels