code: def _set_parallel_devices_and_init_accelerator(self) -> None:
      if isinstance(self._accelerator_flag, Accelerator):
          self.accelerator: Accelerator = self._accelerator_flag
      else:
          self.accelerator = AcceleratorRegistry.get(
              self._accelerator_flag
          )
      accelerator_cls = self.accelerator.__class__
  
      if not accelerator_cls.is_available():
          available_accelerator = [
              acc_str
              for acc_str in self._accelerator_types
              if AcceleratorRegistry[acc_str][
                  "accelerator"
              ].is_available()
          ]
          raise MisconfigurationException(
              f"`{accelerator_cls.__qualname__}` can not run on your system"
              " since the accelerator is not available. The following accelerator(s)"
              " is available and can be passed into `accelerator` argument of"
              f" `Trainer`: {available_accelerator}."
          )
  
      self._set_devices_flag_if_auto_passed()
      self._devices_flag = accelerator_cls.parse_devices(
          self._devices_flag
      )
      if not self._parallel_devices:
          self._parallel_devices = accelerator_cls.get_parallel_devices(
              self._devices_flag
          )
  
imports: import logging
  import os
  from collections import Counter
  from typing import Dict, List, Literal, Optional, Union
  import torch
  from lightning.fabric.connector import _PRECISION_INPUT, _PRECISION_INPUT_STR, _convert_precision_to_unified_args
  from lightning.fabric.plugins.environments import ClusterEnvironment, LightningEnvironment, LSFEnvironment, MPIEnvironment, SLURMEnvironment, TorchElasticEnvironment
  from lightning.fabric.utilities.device_parser import _determine_root_gpu_device
  from lightning.fabric.utilities.imports import _IS_INTERACTIVE
  from lightning.pytorch.accelerators import AcceleratorRegistry
  from lightning.pytorch.accelerators.accelerator import Accelerator
  from lightning.pytorch.accelerators.cuda import CUDAAccelerator
  from lightning.pytorch.accelerators.mps import MPSAccelerator
  from lightning.pytorch.accelerators.xla import XLAAccelerator
  from lightning.pytorch.plugins import _PLUGIN_INPUT, CheckpointIO, DeepSpeedPrecision, DoublePrecision, FSDPPrecision, HalfPrecision, MixedPrecision, Precision, TransformerEnginePrecision, XLAPrecision
  from lightning.pytorch.plugins.layer_sync import LayerSync, TorchSyncBatchNorm
  from lightning.pytorch.strategies import DDPStrategy, DeepSpeedStrategy, FSDPStrategy, ParallelStrategy, SingleDeviceStrategy, SingleDeviceXLAStrategy, Strategy, StrategyRegistry, XLAStrategy
  from lightning.pytorch.strategies.ddp import _DDP_FORK_ALIASES
  from lightning.pytorch.utilities.exceptions import MisconfigurationException
  from lightning.pytorch.utilities.imports import _LIGHTNING_BAGUA_AVAILABLE, _LIGHTNING_COLOSSALAI_AVAILABLE, _graphcore_available_and_importable, _habana_available_and_importable
  from lightning.pytorch.utilities.rank_zero import rank_zero_info, rank_zero_warn
label_desc: Use image node_id 6 for calling the _AcceleratorConnector obj's underlying member method code with example usage: obj._set_parallel_devices_and_init_accelerator() without return types