code: def get_devices_spec(
      devices: Sequence[torch.device | str] | None = None,
  ) -> list[torch.device]:
      """
      Get a valid specification for one or more devices. If `devices` is None get devices for all CUDA devices available.
      If `devices` is and zero-length structure a single CPU compute device is returned. In any other cases `devices` is
      returned unchanged.
  
      Args:
          devices: list of devices to request, None for all GPU devices, [] for CPU.
  
      Raises:
          RuntimeError: When all GPUs are selected (``devices=None``) but no GPUs are available.
  
      Returns:
          list of torch.device: list of devices.
  
      """
      if devices is None:
          devices = [
              torch.device(f"cuda:{d:d}")
              for d in range(torch.cuda.device_count())
          ]
  
          if not devices:
              raise RuntimeError("No GPU devices available.")
  
      elif len(devices) == 0:
          devices = [torch.device("cpu")]
  
      else:
          devices = list(devices)
  
      devices = [
          torch.device(d) if isinstance(d, str) else d for d in devices
      ]
      return devices
  
imports: from __future__ import annotations
  from abc import ABC, abstractmethod
  from collections.abc import Callable, Sequence
  from typing import TYPE_CHECKING, Any, cast
  import torch
  from monai.config import IgniteInfo
  from monai.transforms import apply_transform
  from monai.utils import ensure_tuple, min_version, optional_import
  from monai.utils.enums import CommonKeys, GanKeys
label_desc: Use image node_id 1 for calling a global function with example usage: get_devices_spec(devices) and returns: devices