code: def get_torch_bytes(model_dict):
      with tempfile.TemporaryFile() as f:
          t.save(model_dict, f)
          f.seek(0)
          model_saved_bytes = f.read()
  
          return model_saved_bytes
  
imports: import torch.nn
  from fate.arch.dataframe import DataFrame
  from fate.ml.abc.module import HomoModule
  from fate.ml.utils.model_io import ModelIO
  from fate.arch import Context
  import logging
  import torch
  from fate.ml.nn.homo.fedavg import FedAVGClient, TrainingArguments, FedAVGArguments
  from transformers import default_data_collator
  import functools
  import tempfile
  from fate.ml.utils.predict_tools import array_to_predict_df
  from fate.ml.utils.predict_tools import MULTI, BINARY
  from fate.ml.nn.dataset.table import TableDataset
  from fate.ml.utils._optimizer import optimizer_factory, lr_scheduler_factory
label_desc: Use image node_id 4 for calling a global function with example usage: get_torch_bytes(model_dict) and returns: model_saved_bytes