code: def test_dataloader_tensor_frame():
      tf = get_random_tensor_frame(num_rows=10)
      loader = DataLoader([tf, tf, tf, tf], batch_size=2, shuffle=False)
      assert len(loader) == 2
  
      for batch in loader:
          assert batch.num_rows == 20
  
      data = Data(tf=tf, edge_index=get_random_edge_index(10, 10, 20))
      loader = DataLoader(
          [data, data, data, data], batch_size=2, shuffle=False
      )
      assert len(loader) == 2
  
      for batch in loader:
          assert batch.num_graphs == len(batch) == 2
          assert batch.num_nodes == 20
          assert batch.tf.num_rows == 20
          assert batch.edge_index.max() >= 10
  
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 8 for calling a global function with example usage: test_dataloader_tensor_frame() without return types