code: def load_state_dict(
      model: torch.nn.Module, state_dict: Dict, strict: bool = True
  ) -> torch.nn.Module:
      """Load the given `state_dict` into the model.
  
      Args:
          model: A torch model (it can be also a wrapped model, e.g., with DDP).
          state_dict: A state dict dictionary to load model parameters from.
          strict: whether to strictly enforce that the keys in `state_dict` match the keys returned by this module's
              `state_dict` function. Default: ``True``.
  
      Returns:
          model loaded with parameters from the given state_dict
      """
      if hasattr(model, "module"):
          model.module.load_state_dict(state_dict, strict=strict)
      else:
          model.load_state_dict(state_dict, strict=strict)
      return model
  
imports: import argparse
  import glob
  import math
  import os
  from typing import Dict, List, Optional, Tuple, Union
  import torch
  from cvnets import EMA
  from optim import BaseOptim
  from utils import logger
  from utils.common_utils import unwrap_model_fn
  from utils.ddp_utils import is_master
  from utils.download_utils import get_local_path
label_desc: Use image node_id 2 for calling a global function with example usage: load_state_dict(model, state_dict, strict) and returns: model