code: def test_multiprocessing():
      queue = torch.multiprocessing.Manager().Queue()
      data = Data(x=torch.randn(5, 16))
      data_list = [data, data, data, data]
      loader = DataLoader(data_list, batch_size=2)
      for batch in loader:
          queue.put(batch)
  
      batch = queue.get()
      assert batch.num_graphs == len(batch) == 2
  
      batch = queue.get()
      assert batch.num_graphs == len(batch) == 2
  
file_path: pytorch_geometric/test/loader/test_dataloader.py
imports: import multiprocessing
  import sys
  from collections import namedtuple
  import pytest
  import torch
  from torch_geometric import EdgeIndex
  from torch_geometric.data import Data, HeteroData, OnDiskDataset
  from torch_geometric.loader import DataLoader
  from torch_geometric.testing import get_random_edge_index, get_random_tensor_frame, withCUDA, withPackage
label_desc: Use image node_id 4 for calling a global function with example usage: test_multiprocessing() without return types