code: def set_batch_size(self, model: nn.Module, batch_size: int):
      # Adapted from:
      # https://github.com/microsoft/DeepSpeed/blob/7ce371b139521b1ebbf052f0496b1a16397c1d19/deepspeed/runtime/engine.py#L422  # noqa: E501
      model._config.micro_batch_size_per_gpu = batch_size
      model._config.train_batch_size = (
          batch_size
          * self.size()
          * model._config.gradient_accumulation_steps
      )
  
imports: import logging
  import os
  import warnings
  from typing import Any, Dict, List, Mapping, Optional, Tuple, TYPE_CHECKING, Union
  import deepspeed
  import deepspeed.comm
  import torch
  from deepspeed.utils.zero_to_fp32 import get_fp32_state_dict_from_zero_checkpoint
  from packaging import version
  from torch import nn
  from torch.optim.optimizer import Optimizer
  from ludwig.constants import MIN_POSSIBLE_BATCH_SIZE
  from ludwig.distributed.ddp import DDPStrategy
  from ludwig.modules.optimization_modules import get_optimizer_class_and_kwargs
  from ludwig.utils.checkpoint_utils import Checkpoint
  from ludwig.utils.model_utils import extract_tensors, replace_tensors
label_desc: Use image node_id 9 for calling the DeepSpeedStrategy obj's underlying member method code with example usage: obj.set_batch_size(model, batch_size) without return types