code: def _initialize_deepspeed_inference(self, model: Module) -> None:
      import deepspeed
  
      assert isinstance(self.config, dict)
  
      # todo: this is required for DeepSpeed throughput timers
      inference_config = {"train_micro_batch_size_per_gpu": 1}
      if "fp16" in self.config:
          inference_config.update({"fp16": self.config["fp16"]})
      if "bf16" in self.config:
          inference_config.update({"bf16": self.config["bf16"]})
      if self.zero_stage_3:
          inference_config.update(
              {
                  "zero_allow_untested_optimizer": self.config[
                      "zero_allow_untested_optimizer"
                  ],
                  "zero_optimization": self.config["zero_optimization"],
              }
          )
      # Remove all module hooks before initializing new model
      remove_module_hooks(model)
      model, _, _, _ = deepspeed.initialize(
          args=argparse.Namespace(device_rank=self.root_device.index),
          config=inference_config,
          model=model,
          optimizer=None,
          lr_scheduler=None,
          model_parameters=[],
          dist_init_required=False,
      )
      self.model = model
  
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 17 for calling the DeepSpeedStrategy obj's underlying member method code with example usage: obj._initialize_deepspeed_inference(model) without return types