code: def load_state_dict(self):
      if self.is_consistent:
          state_dict = flow.load(self.load_path, consistent_src_rank=0)
      elif self.rank == 0:
          state_dict = flow.load(self.load_path)
      else:
          return
      logging.info("Model resume successfully!")
      self.model.load_state_dict(state_dict)
  
imports: import oneflow
  from oneflow.nn.parallel import DistributedDataParallel
  from utils.ofrecord_data_utils import OFRecordDataLoader, SyntheticDataLoader
  from utils.utils_logging import AverageMeter
  from utils.utils_callbacks import CallBackVerification, CallBackLogging, CallBackModelCheckpoint
  from backbones import get_model
  from graph import TrainGraph, EvalGraph
  from utils.losses import CrossEntropyLoss_sbp
  import logging
label_desc: Use image node_id 3 for calling the Trainer obj's underlying member method code with example usage: obj.load_state_dict() without return types