code: def setUp(self):
      super().setUp()
      self.ckpt_dir = self.create_tempdir()
      self.summary_dir = self.create_tempdir()
      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'",
              "evaluator.evaluate.epochs = 5",
              "resnet.build_resnet_v1.input_shape = (28, 28, 1)",
              "resnet.build_resnet_v1.depth = 8",
          ]
      )
      for epoch in range(6):
          model = resnet.build_resnet_v1()  # Randomly initialized
          ckpt = tf.train.Checkpoint(model)
          ckpt.save_counter.assign(
              epoch - 1
          )  # Next save() uses number <epoch>.
          ckpt.save(os.path.join(self.ckpt_dir, "ckpt"))
  
file_path: neural-structured-learning/research/multi_representation_adversary/multi_representation_adversary/evaluator_test.py
imports: import os
  from absl.testing import parameterized
  import gin
  from multi_representation_adversary import evaluator
  from multi_representation_adversary import resnet
  import numpy
  import tensorflow.compat.v2
  import tensorflow_datasets
label_desc: Use image node_id 1 for calling the EvaluatorTest obj's underlying member method code with example usage: obj.setUp() without return types