code: def _convert_model_from_object_to_bytearray(model_object):
      """Converts a tflite model from a parsable object into a bytearray."""
      # Initial size of the buffer, which will grow automatically if needed
      builder = flatbuffers.Builder(1024)
      model_offset = model_object.Pack(builder)
      builder.Finish(
          model_offset, file_identifier=_TFLITE_FILE_IDENTIFIER
      )
      return bytes(builder.Output())
  
imports: import copy
  import datetime
  import sys
  from absl import logging
  import flatbuffers
  from tensorflow.core.protobuf import config_pb2
  from tensorflow.core.protobuf import meta_graph_pb2
  from tensorflow.lite.python import conversion_metadata_schema_py_generated
  from tensorflow.lite.python import schema_py_generated
  from tensorflow.lite.python import schema_util
  from tensorflow.lite.python import tflite_keras_util
  from tensorflow.lite.python.op_hint import convert_op_hints_to_stubs
  from tensorflow.lite.python.op_hint import find_all_hinted_output_nodes
  from tensorflow.lite.tools import flatbuffer_utils
  from tensorflow.python.eager import function
  from tensorflow.python.framework import convert_to_constants
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import error_interpolation
  from tensorflow.python.grappler import tf_optimizer
  from tensorflow.python.training.saver import export_meta_graph
label_desc: Use image node_id 16 for calling a global function with example usage: _convert_model_from_object_to_bytearray(model_object) and returns: bytes