class_docstr: Tests regularizer methods.
docstr: Tests virtual_adv_regularizer with default config.
docstr_tok: ["Tests","virtual_adv_regularizer","with","default","config","."]
code: def testVirtualAdvRegularizerDefaultConfig(self):
      """Tests virtual_adv_regularizer with default config."""
      input_layer = tf.constant([[1.0, -1.0]])
      embedding_fn = lambda x: x
      vadv_config = configs.VirtualAdvConfig()
      vadv_loss = regularizer.virtual_adv_regularizer(
          input_layer, embedding_fn, vadv_config
      )
      actual_loss = self.evaluate(vadv_loss)
      self.assertAllGreaterEqual(actual_loss, 0.0)
  
file_path: neural-structured-learning/neural_structured_learning/lib/regularizer_test.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import neural_structured_learning.configs
  from neural_structured_learning.lib import regularizer
  import numpy
  import tensorflow
label_desc: Use image node_id 5 for calling the RegularizerTest obj's underlying member method code with example usage: obj.testVirtualAdvRegularizerDefaultConfig() without return types