code: def test_force_nvml_based_cuda_check():
      """Test that we force PyTorch to use the NVML-based CUDA checks."""
      importlib.reload(
          lightning.fabric
      )  # reevaluate top-level code, without becoming a different object
  
      assert os.environ["PYTORCH_NVML_BASED_CUDA_CHECK"] == "1"
  
file_path: pytorch-lightning/tests/tests_fabric/accelerators/test_cuda.py
imports: import importlib
  import logging
  import os
  from re import escape
  from unittest import mock
  from unittest.mock import Mock
  import lightning.fabric
  import pytest
  import torch
  from lightning.fabric.accelerators.cuda import CUDAAccelerator, _check_cuda_matmul_precision, find_usable_cuda_devices, is_cuda_available, num_cuda_devices
  from tests_fabric.helpers.runif import RunIf
label_desc: Use image node_id 7 for calling a global function with example usage: test_force_nvml_based_cuda_check() without return types