code: def setUp(self):
      super(ComplexityRegularizedEnsemblerTest, self).setUp()
  
      self._optimizer = tf_compat.v1.train.GradientDescentOptimizer(
          learning_rate=0.1
      )
      self.easy_ensembler = ensemble.ComplexityRegularizedEnsembler(
          optimizer=self._optimizer
      )
  
      mock.patch.object(
          tf.train, "load_variable", autospec=False
      ).start()
      mock.patch.object(
          tf.compat.v1.train, "load_variable", autospec=False
      ).start()
      mock.patch.object(
          tf.compat.v2.train, "load_variable", autospec=False
      ).start()
      mock.patch.object(
          ensemble.ComplexityRegularizedEnsembler,
          "_load_variable",
          autospec=False,
      ).start()
  
      def _load_variable(var, previous_iteration_checkpoint):
          del var  # unused
          assert previous_iteration_checkpoint is not None
          return 1.0
  
      complexity_regularized_ensembler = (
          ensemble.ComplexityRegularizedEnsembler
      )
      complexity_regularized_ensembler._load_variable.side_effect = (
          _load_variable
      )
  
      self.summary = _FakeSummary()
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import collections
  import contextlib
  from absl.testing import parameterized
  from adanet import ensemble
  from adanet import subnetwork
  from adanet import tf_compat
  from adanet.core.summary import Summary
  import mock
  import tensorflow.compat.v2
  from tensorflow.python.eager import context
  from tensorflow.python.framework import test_util
label_desc: Use image node_id 1 for calling the ComplexityRegularizedEnsemblerTest obj's underlying member method code with example usage: obj.setUp() and returns: int