code: def get_state_dict(model):
      """
      Get the state dict from the model.
  
      When using Pytorch FSDP, we can offload to CPU.
      """
  
      if FSDP_AVAILABLE:
          from torch.distributed.fsdp.fully_sharded_data_parallel import (
              FullStateDictConfig,
              StateDictType,
          )
  
          save_policy = FullStateDictConfig(
              offload_to_cpu=True, rank0_only=True
          )
          with FSDP.state_dict_type(
              model, StateDictType.FULL_STATE_DICT, save_policy
          ):
              state = model.state_dict()
      else:
          state = model.state_dict()
  
      return state
  
imports: import contextlib
  import functools
  import torch
  import torch.distributed
  from torch.distributed.algorithms.join import Join, Joinable, JoinHook
  import torch.nn
  from parlai.scripts.eval_model import Evaluator
  from parlai.scripts.train_model import TrainLoop
  from parlai.utils.distributed import is_distributed, get_dist_group
label_desc: Use image node_id 7 for calling a global function with example usage: get_state_dict(model) and returns: state