code: def test_evaluate(
      self, num_aggregate, aggregation_method, aggregation_interval
  ):
      gin.parse_config(
          [
              f"evaluator.evaluate.num_aggregate = {num_aggregate}",
              f"evaluator.evaluate.aggregation_method = '{aggregation_method}'",
              f"evaluator.evaluate.aggregation_interval = {aggregation_interval}",
              "evaluator.evaluate.representation_list = [('identity', 'linf')]",
              "evaluator.evaluate.should_write_final_predictions = True",
          ]
      )
      with tfds.testing.mock_data(num_examples=10):
          evaluator.evaluate(
              self.ckpt_dir.full_path, self.summary_dir.full_path
          )
      self.assertTrue(
          tf.io.gfile.exists(
              os.path.join(
                  self.summary_dir, "results_identity_linf.tsv"
              )
          )
      )
  
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 2 for calling the EvaluatorTest obj's underlying member method code with example usage: obj.test_evaluate(num_aggregate, aggregation_method, aggregation_interval) without return types