code: def _load_optim_state_dict(
      model: nn.Module,
      optimizers: Tuple[torch.optim.Optimizer, ...],
      state_dict: OptimizerStateType,
      info: _StateDictInfo,
  ) -> None:
      if not info.handle_optim:
          return
  
      for optim in optimizers:
          optim_state_dict = _split_optim_state_dict(
              model, optim, state_dict, info
          )
          if info.fsdp_modules:
              with info.fsdp_context():
                  optim_state_dict = FSDP.optim_state_dict_to_load(
                      model, optim, optim_state_dict
                  )
  
          # Note that we do not have to convert the FQN back to param id here if
          # order in optim.param_groups[idx][PARAMS] is the same as the one in
          # optim_state_dict[PG][idx][PARAMS].
          _init_optim_state(optim)
          _state_dict_fn(optim, "load_state_dict")(
              state_dict=optim_state_dict
          )
  
imports: import contextlib
  import functools
  import gc
  from dataclasses import asdict, dataclass, field
  from itertools import chain
  from typing import Any, Callable, cast, Dict, Iterable, List, no_type_check, Optional, Set, Tuple, Union
  import torch
  import torch.distributed
  import torch.nn
  from torch.distributed._shard.sharded_tensor import ShardedTensor
  from torch.distributed._state_dict_utils import _gather_state_dict, _offload_state_dict_to_cpu
  from torch.distributed._tensor import DTensor
  from torch.distributed.fsdp import FullOptimStateDictConfig, FullStateDictConfig, FullyShardedDataParallel, OptimStateDictConfig, ShardedOptimStateDictConfig, ShardedStateDictConfig, StateDictConfig, StateDictType
  from torch.distributed.fsdp._common_utils import _get_module_fsdp_state_if_fully_sharded_module, FSDP_WRAPPED_MODULE
  from torch.nn.modules.module import _IncompatibleKeys
  from torch.nn.parallel import DistributedDataParallel
label_desc: Use image node_id 11 for calling a global function with example usage: _load_optim_state_dict(model, optimizers, state_dict, info) without return types