code: def _format_batch_size_and_grad_accum_config(self) -> None:
      # TODO: Using Fabric, we do not support these variables within the config
      assert isinstance(self.config, dict)
      if self.lightning_module is None:
          return
  
      if "gradient_accumulation_steps" in self.config:
          raise MisconfigurationException(
              "Do not set `gradient_accumulation_steps` in the DeepSpeed config"
              " as this will be set with the `accumulate_grad_batches` argument passed via the Lightning Trainer."
          )
      self.config[
          "gradient_accumulation_steps"
      ] = self.lightning_module.trainer.accumulate_grad_batches
      if "train_micro_batch_size_per_gpu" not in self.config:
          batch_size = self._auto_select_batch_size()
          self.config["train_micro_batch_size_per_gpu"] = batch_size
      if "gradient_clipping" not in self.config:
          self.config["gradient_clipping"] = (
              self.lightning_module.trainer.gradient_clip_val or 0.0
          )
  
imports: import argparse
  import json
  import logging
  import os
  import platform
  from collections import OrderedDict
  from contextlib import contextmanager
  from pathlib import Path
  from typing import TYPE_CHECKING, Any, Dict, Generator, List, Mapping, Optional, Tuple, Union
  import torch
  from torch.nn import Module
  from torch.optim import Optimizer
  from typing_extensions import override
  import lightning.pytorch
  from lightning.fabric.plugins import ClusterEnvironment
  from lightning.fabric.strategies import _StrategyRegistry
  from lightning.fabric.strategies.deepspeed import _DEEPSPEED_AVAILABLE, _format_precision_config, _validate_checkpoint_directory, _validate_device_index_selection
  from lightning.fabric.utilities.optimizer import _optimizers_to_device
  from lightning.fabric.utilities.seed import reset_seed
  from lightning.fabric.utilities.types import _PATH, LRScheduler, ReduceLROnPlateau
  from lightning.pytorch.accelerators.cuda import CUDAAccelerator
  from lightning.pytorch.core.optimizer import _init_optimizers_and_lr_schedulers
  from lightning.pytorch.plugins.precision import Precision
  from lightning.pytorch.strategies.ddp import DDPStrategy
  from lightning.pytorch.trainer.states import TrainerFn
  from lightning.pytorch.utilities import GradClipAlgorithmType
  from lightning.pytorch.utilities.exceptions import MisconfigurationException
  from lightning.pytorch.utilities.model_helpers import is_overridden
  from lightning.pytorch.utilities.rank_zero import WarningCache, rank_zero_info, rank_zero_warn
  from lightning.pytorch.utilities.types import LRSchedulerConfig
label_desc: Use image node_id 34 for calling the DeepSpeedStrategy obj's underlying member method code with example usage: obj._format_batch_size_and_grad_accum_config() without return types