code: def test_train(self):
      gin.parse_config(
          [
              "data.preprocess_image.height = 28",
              "data.preprocess_image.width = 28",
              "data.preprocess_image.num_channels = 1",
              "data.get_test_dataset.batch_size = 1",
              "data.get_test_dataset.dataset = 'mnist'",
              "data.get_training_dataset.batch_size = 1",
              "data.get_training_dataset.dataset = 'mnist'",
              "data.get_training_dataset.shuffle_buffer_size = 1",
              "data.get_validation_dataset.batch_size = 1",
              "data.get_validation_dataset.dataset = 'mnist'",
              "data.get_validation_dataset.split = '2'",
              "resnet.build_resnet_v1.input_shape = (28, 28, 1)",
              "resnet.build_resnet_v1.depth = 8",
              "selectors.construct_representation_selector.selection_strategy = 'multiweight'",
              "selectors.construct_representation_selector.sample_freq = 1",
              "selectors.construct_representation_selector.update_freq = 1",
              "trainer.train.epochs = 2",
              "trainer.train.steps_per_epoch = 1",
              "trainer.train.representation_list = [('identity', 'l2'), ('dct', 'l2')]",
          ]
      )
      with tfds.testing.mock_data(num_examples=10):
          trainer.train(
              self.ckpt_dir.full_path, self.summary_dir.full_path
          )
  
      ckpt_path = os.path.join(self.ckpt_dir, "ckpt-2")
      self.assertTrue(tf.io.gfile.exists(ckpt_path + ".index"))
      variables = [
          name for name, shape in tf.train.list_variables(ckpt_path)
      ]
      self.assertTrue(
          any(name.startswith("model") for name in variables)
      )
      self.assertTrue(
          any(name.startswith("selector") for name in variables)
      )
  
file_path: neural-structured-learning/research/multi_representation_adversary/multi_representation_adversary/trainer_test.py
imports: import os
  import gin
  from multi_representation_adversary import trainer
  import tensorflow.compat.v2
  import tensorflow_datasets
label_desc: Use image node_id 2 for calling the TrainerTest obj's underlying member method code with example usage: obj.test_train() without return types