code: def test_overflow_length_dataloader():
      folder = os.getenv("TORCHMETA_DATA_FOLDER")
      download = bool(os.getenv("TORCHMETA_DOWNLOAD", False))
  
      # The number of tasks is C(4112, 20), which exceeds machine precision
      dataset = helpers.omniglot(
          folder,
          ways=20,
          shots=1,
          test_shots=5,
          meta_train=True,
          download=download,
      )
  
      meta_dataloader = BatchMetaDataLoader(dataset, batch_size=4)
  
      batch = next(iter(meta_dataloader))
      assert isinstance(batch, dict)
      assert "train" in batch
      assert "test" in batch
  
file_path: pytorch-meta/torchmeta/tests/utils/test_dataloaders.py
imports: import pytest
  import os
  import torch
  from torch.utils.data import DataLoader
  from torchmeta.datasets import helpers
  from torchmeta.toy import Sinusoid
  from torchmeta.transforms import ClassSplitter
  from torchmeta.utils.data import Task, MetaDataLoader, BatchMetaDataLoader
label_desc: Use image node_id 6 for calling a global function with example usage: test_overflow_length_dataloader() without return types