code: def is_cuda_available() -> bool:
      """Returns a bool indicating if CUDA is currently available.
  
      Unlike :func:`torch.cuda.is_available`, this function does its best not to create a CUDA context for fork support,
      if the platform allows it.
  
      """
      # We set `PYTORCH_NVML_BASED_CUDA_CHECK=1` in lightning.fabric.__init__.py
      return (
          torch.cuda.is_available()
          if _TORCH_GREATER_EQUAL_2_0
          else num_cuda_devices() > 0
      )
  
imports: import os
  import warnings
  from contextlib import contextmanager
  from functools import lru_cache
  from typing import Generator, List, Optional, Union, cast
  import torch
  from typing_extensions import override
  from lightning.fabric.accelerators.accelerator import Accelerator
  from lightning.fabric.accelerators.registry import _AcceleratorRegistry
  from lightning.fabric.utilities.imports import _TORCH_GREATER_EQUAL_2_0
  from lightning.fabric.utilities.rank_zero import rank_zero_info
label_desc: Use image node_id 5 for calling a global function with example usage: is_cuda_available() and returns: unknown