docstr: Checks edge cases when the strategy selection was a string input, and we need to fall back to a different
  choice depending on other parameters or the environment.
code: def _check_strategy_and_fallback(self) -> None:
      """Checks edge cases when the strategy selection was a string input, and we need to fall back to a different
      choice depending on other parameters or the environment."""
      # current fallback and check logic only apply to user pass in str config and object config
      # TODO this logic should apply to both str and object config
      strategy_flag = (
          ""
          if isinstance(self._strategy_flag, Strategy)
          else self._strategy_flag
      )
  
      if (
          strategy_flag in FSDPStrategy.get_registered_strategies()
          or isinstance(self._strategy_flag, FSDPStrategy)
      ) and self._accelerator_flag not in ("cuda", "gpu"):
          raise MisconfigurationException(
              f"You selected strategy to be `{FSDPStrategy.strategy_name}`, but GPU accelerator is not used."
          )
      if (
          strategy_flag in _DDP_FORK_ALIASES
          and "fork"
          not in torch.multiprocessing.get_all_start_methods()
      ):
          raise ValueError(
              f"You selected `Trainer(strategy='{strategy_flag}')` but process forking is not supported on this"
              f" platform. We recommed `Trainer(strategy='ddp_spawn')` instead."
          )
      if strategy_flag:
          self._strategy_flag = strategy_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 10 for calling the _AcceleratorConnector obj's underlying member method code with example usage: obj._check_strategy_and_fallback() without return types