class_docstr: Accelerator for NVIDIA CUDA devices.
class_docstr_tok: ["Accelerator","for","NVIDIA","CUDA","devices","."]
docstr: Gets parallel devices for the Accelerator.
docstr_tok: ["Gets","parallel","devices","for","the","Accelerator","."]
code: def get_parallel_devices(devices: List[int]) -> List[torch.device]:
      """Gets parallel devices for the Accelerator."""
      return [torch.device("cuda", i) for i in devices]
  
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 7 for calling the CUDAAccelerator obj's underlying member method code with example usage: obj.get_parallel_devices(devices) and returns: unknown