code: def test_shared_trainable_variables_are_equal(self):
      (
          true_encoder,
          sample_inputs,
      ) = get_small_bert_encoder_and_sample_inputs()
      unwrapped_encoder = bert_encoder_utils.get_unwrapped_bert_encoder(
          true_encoder
      )
      # Initializes the trainable variable shapes.
      true_encoder(sample_inputs)
      unwrapped_encoder(sample_inputs)
      # The official BERT encoder may initialize trainable variables that are
      # not used in a model forward pass. Hence, they are invisible when we
      # try to unwrapping layers using our utility function.
      true_vars, computed_vars = get_shared_trainable_variables(
          true_encoder, unwrapped_encoder
      )
      self.assertAllClose(true_vars, computed_vars)
  
file_path: privacy/tensorflow_privacy/privacy/fast_gradient_clipping/bert_encoder_utils_test.py
imports: from absl.testing import parameterized
  import numpy
  import tensorflow
  import tensorflow_models
  from tensorflow_privacy.privacy.fast_gradient_clipping import bert_encoder_utils
label_desc: Use image node_id 2 for calling the BertEncoderUtilsTest obj's underlying member method code with example usage: obj.test_shared_trainable_variables_are_equal() without return types