code: def test_has_len_all_rank():
      trainer = Trainer(fast_dev_run=True)
  
      with pytest.warns(
          UserWarning,
          match="Total length of `DataLoader` across ranks is zero.",
      ):
          assert has_len_all_ranks(
              DataLoader(RandomDataset(0, 0)), trainer.strategy
          )
  
      assert has_len_all_ranks(
          DataLoader(RandomDataset(1, 1)), trainer.strategy
      )
  
imports: from dataclasses import dataclass
  from unittest.mock import Mock
  import numpy
  import pytest
  import torch
  from lightning.fabric.utilities.data import _replace_dunder_methods
  from lightning.pytorch import Trainer
  from lightning.pytorch.demos.boring_classes import RandomDataset, RandomIterableDataset
  from lightning.pytorch.overrides.distributed import _IndexBatchSamplerWrapper
  from lightning.pytorch.trainer.states import RunningStage
  from lightning.pytorch.utilities.data import _get_dataloader_init_args_and_kwargs, _update_dataloader, extract_batch_size, has_len_all_ranks, warning_cache
  from lightning.pytorch.utilities.exceptions import MisconfigurationException
  from lightning_utilities.test.warning import no_warning_call
  from torch import Tensor
  from torch.utils.data import BatchSampler, DataLoader, RandomSampler
label_desc: Use image node_id 2 for calling a global function with example usage: test_has_len_all_rank() without return types