code: def load_model_as_bytes(model):
      model_path = os.path.join(tempfile.mkdtemp(), "vfl_server_model")
      model.save(model_path, save_format="h5")
      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
  import os
  import shutil
  import tempfile
  from numpy import ndarray
  from bigdl.dllib.utils.log4Error import invalidInputError
  from bigdl.ppml.fl.nn.fl_client import FLClient
  from bigdl.ppml.fl.nn.nn_client import NNClient
  from bigdl.ppml.fl.nn.utils import file_chunk_generate, print_file_size_in_dir, tensor_map_to_ndarray_map
  import tensorflow
  from tensorflow.keras.layers import Dense, Flatten, Conv2D
  from tensorflow.keras import Model
  from bigdl.ppml.fl.nn.generated.nn_service_pb2 import ByteChunk
  from nn_service_pb2 import LoadModelRequest, SaveModelRequest
label_desc: Use image node_id 4 for calling the TensorflowEstimator obj's underlying member method code with example usage: obj.load_model_as_bytes(model) and returns: file_chunk_generator