code: def get_tune_args(
      exec_properties: Dict[str, Any]
  ) -> Optional[tuner_pb2.TuneArgs]:
      """Returns TuneArgs protos from execution properties, if present."""
      tune_args = exec_properties.get(
          standard_component_specs.TUNE_ARGS_KEY
      )
      if not tune_args:
          return None
  
      result = tuner_pb2.TuneArgs()
      proto_utils.json_to_proto(tune_args, result)
  
      return result
  
imports: import json
  import os
  from typing import Any, Callable, Dict, List, Optional
  from absl import logging
  from keras_tuner.engine import base_tuner
  from keras_tuner.engine import trial
  from tfx import types
  from tfx.components.trainer import fn_args_utils
  from tfx.components.util import udf_utils
  from tfx.dsl.components.base import base_executor
  from tfx.proto import tuner_pb2
  from tfx.types import artifact_utils
  from tfx.types import standard_component_specs
  from tfx.utils import io_utils
  from tfx.utils import proto_utils
label_desc: Use image node_id 2 for calling a global function with example usage: get_tune_args(exec_properties) and returns: result, None