code: def get_shared_trainable_variables(model1, model2):
      """Returns the shared trainable variables (by name) between models."""
      common_names = {v.name for v in model1.trainable_variables} & {
          v.name for v in model2.trainable_variables
      }
      tvars1 = [
          v
          for v in model1.trainable_variables
          if v.name in common_names
      ]
      tvars2 = [
          v
          for v in model2.trainable_variables
          if v.name in common_names
      ]
      return tvars1, tvars2
  
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 3 for calling a global function with example usage: get_shared_trainable_variables(model1, model2) and returns: tvars1,  tvars2