class_docstr: Accelerator for NVIDIA CUDA devices.
class_docstr_tok: ["Accelerator","for","NVIDIA","CUDA","devices","."]
docstr: Accelerator device parsing logic.
docstr_tok: ["Accelerator","device","parsing","logic","."]
code: def parse_devices(
      devices: Union[int, str, List[int]]
  ) -> Optional[List[int]]:
      """Accelerator device parsing logic."""
      return _parse_gpu_ids(devices, include_cuda=True)
  
imports: import logging
  import os
  import shutil
  import subprocess
  from typing import Any, Dict, List, Optional, Union
  import torch
  from typing_extensions import override
  import lightning.pytorch
  from lightning.fabric.accelerators import _AcceleratorRegistry
  from lightning.fabric.accelerators.cuda import _check_cuda_matmul_precision, _clear_cuda_memory, num_cuda_devices
  from lightning.fabric.utilities.device_parser import _parse_gpu_ids
  from lightning.fabric.utilities.types import _DEVICE
  from lightning.pytorch.accelerators.accelerator import Accelerator
  from lightning.pytorch.utilities.exceptions import MisconfigurationException
label_desc: Use image node_id 6 for calling the CUDAAccelerator obj's underlying member method code with example usage: obj.parse_devices(devices) and returns: _parse_gpu_ids