code: def build_model_flags(
      change_concat_input_ranges=False,
      allow_nonexistent_arrays=False,
      saved_model_dir=None,
      saved_model_version=0,
      saved_model_tags=None,
      saved_model_exported_names=None,
      **_,
  ):
      """Builds the model flags object from params.
  
      Args:
        change_concat_input_ranges: Boolean to change behavior of min/max ranges for
          inputs and outputs of the concat operator for quantized models. Changes
          the ranges of concat operator overlap when true. (default False)
        allow_nonexistent_arrays: Allow specifying array names that don't exist or
          are unused in the final graph. (default False)
        saved_model_dir: Filepath of the saved model to be converted. This value
          will be non-empty only when the saved model import path will be used.
          Otherwises, the graph def-based conversion will be processed.
        saved_model_version: SavedModel file format version of The saved model file
          to be converted. This value will be set only when the SavedModel import
          path will be used.
        saved_model_tags: Set of string saved model tags, formatted in the
          comma-separated value. This value will be set only when the SavedModel
          import path will be used.
        saved_model_exported_names: Names to be exported (default: export all) when
          the saved model import path is on. This value will be set only when the
          SavedModel import path will be used.
  
      Returns:
        model_flags: protocol buffer describing the model.
      """
      model_flags = _model_flags_pb2.ModelFlags()
      model_flags.change_concat_input_ranges = (
          change_concat_input_ranges
      )
      model_flags.allow_nonexistent_arrays = allow_nonexistent_arrays
      if saved_model_dir:
          model_flags.saved_model_dir = saved_model_dir
      model_flags.saved_model_version = saved_model_version
      if saved_model_tags:
          model_flags.saved_model_tags.extend(saved_model_tags)
      if saved_model_exported_names:
          model_flags.saved_model_exported_names.extend(
              saved_model_exported_names
          )
      return model_flags
  
imports: import distutils.spawn
  import enum
  import hashlib
  import os
  import platform
  import subprocess
  import tempfile
  from typing import Optional
  import warnings
  from tensorflow.compiler.mlir.quantization.stablehlo import quantization_options_pb2
  from tensorflow.lite.python import lite_constants
  from tensorflow.lite.python import util
  from tensorflow.lite.python import wrap_toco
  from tensorflow.lite.python.convert_phase import Component
  from tensorflow.lite.python.convert_phase import convert_phase
  from tensorflow.lite.python.convert_phase import ConverterError
  from tensorflow.lite.python.convert_phase import SubComponent
  from tensorflow.lite.python.metrics import converter_error_data_pb2
  from tensorflow.lite.python.metrics.wrapper import metrics_wrapper
  from tensorflow.lite.toco import model_flags_pb2
  from tensorflow.lite.toco import toco_flags_pb2
  from tensorflow.lite.toco import types_pb2
  from tensorflow.lite.tools import flatbuffer_utils
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import tensor_shape
  from tensorflow.python.platform import resource_loader
  from tensorflow.python.util import deprecation
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 10 for calling a global function with example usage: build_model_flags(change_concat_input_ranges, allow_nonexistent_arrays, saved_model_dir, saved_model_version, saved_model_tags, saved_model_exported_names) and returns: model_flags