code: def load_model_as_bytes(model):
      model_path = os.path.join(tempfile.mkdtemp(), "vfl_server_model")
      m = torch.jit.script(model)
      torch.jit.save(m, model_path)
      # torch.save(model, model_path)
      logging.info(
          f"Client packed model file, length: {os.path.getsize(model_path)}"
      )
      file_chunk_generator = file_chunk_generate(model_path)
      return file_chunk_generator
  
imports: import logging
  from numpy import ndarray
  import torch
  from torch import nn
  from bigdl.ppml.fl.nn.fl_client import FLClient
  from torch.utils.data import DataLoader
  from bigdl.dllib.utils.log4Error import invalidInputError, invalidOperationError
  from bigdl.ppml.fl.nn.nn_client import NNClient
  from bigdl.ppml.fl.nn.utils import file_chunk_generate, tensor_map_to_ndarray_map
  import os
  import tempfile
  from nn_service_pb2 import LoadModelRequest, SaveModelRequest
label_desc: Use image node_id 4 for calling the PytorchEstimator obj's underlying member method code with example usage: obj.load_model_as_bytes(model) and returns: file_chunk_generator