code: def init_deepspeed(self) -> None:
      assert self.lightning_module is not None
      # deepspeed handles gradient clipping internally
      if is_overridden(
          "configure_gradient_clipping",
          self.lightning_module,
          pl.LightningModule,
      ):
          rank_zero_warn(
              "Since DeepSpeed handles gradient clipping internally, the default"
              " `LightningModule.configure_gradient_clipping` implementation will not actually clip gradients."
              " The hook will still be called. Consider setting"
              " `Trainer(gradient_clip_val=..., gradient_clip_algorithm='norm')`"
              " which will use the internal mechanism."
          )
  
      if (
          self.lightning_module.trainer.gradient_clip_algorithm
          == GradClipAlgorithmType.VALUE
      ):
          raise MisconfigurationException(
              "DeepSpeed does not support clipping gradients by value."
          )
  
      assert isinstance(self.model, pl.LightningModule)
      if (
          self.lightning_module.trainer
          and self.lightning_module.trainer.training
      ):
          self._initialize_deepspeed_train(self.model)
      else:
          self._initialize_deepspeed_inference(self.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 10 for calling the DeepSpeedStrategy obj's underlying member method code with example usage: obj.init_deepspeed() without return types