code: def testTrainerFn(self):
      trainer_fn_args = trainer_executor.TrainerFnArgs(
          train_files="/path/to/train.file",
          transform_output="/path/to/transform_output",
          serving_model_dir="/path/to/model_dir",
          eval_files="/path/to/eval.file",
          schema_file="/path/to/schema_file",
          train_steps=1000,
          eval_steps=100,
      )
      schema = schema_pb2.Schema()
      result = model._create_train_and_eval_spec(
          trainer_fn_args, schema
      )  # pylint: disable=protected-access
      self.assertIsInstance(result["estimator"], tf_estimator.Estimator)
      self.assertIsInstance(
          result["train_spec"], tf_estimator.TrainSpec
      )
      self.assertIsInstance(result["eval_spec"], tf_estimator.EvalSpec)
      self.assertTrue(callable(result["eval_input_receiver_fn"]))
  
imports: import tensorflow
  from tensorflow import estimator
  from tfx.components.trainer import executor
  from tfx.experimental.templates.taxi.models.estimator_model import model
  from tensorflow_metadata.proto.v0 import schema_pb2
label_desc: Use image node_id 1 for calling the ModelTest obj's underlying member method code with example usage: obj.testTrainerFn() without return types