code: def test_initialize_pytorch_with_distributed_bad_local_rank(
      mock_torch, mock_warnings
  ):
      """In this scenario, the local_size 5 is out of the bounds of the GPU indices."""
      mock_torch.cuda.is_available.return_value = True
      mock_torch.cuda.device_count.return_value = 4
  
      with clean_params():
          initialize_pytorch(local_rank=1, local_size=5)
  
      assert os.environ["CUDA_VISIBLE_DEVICES"] == ""
      mock_warnings.warn.assert_called()
  
file_path: ludwig/tests/ludwig/utils/test_torch_utils.py
imports: import contextlib
  import os
  from typing import List
  from unittest.mock import patch
  import pytest
  import torch
  from ludwig.utils.torch_utils import _get_torch_init_params, _set_torch_init_params, initialize_pytorch, sequence_length_2D, sequence_length_3D
label_desc: Use image node_id 10 for calling a global function with example usage: test_initialize_pytorch_with_distributed_bad_local_rank(mock_torch, mock_warnings) without return types