code: def get_nlp_position_embedding_layer_registries():
      dbl_registry = layer_registry.LayerRegistry()
      dbl_registry.insert(
          tf.keras.layers.Dense, dense.dense_layer_computation
      )
      dbl_registry.insert(
          tfm.nlp.layers.PositionEmbedding,
          nlp_position_embedding.nlp_position_embedding_layer_computation,
      )
      return {
          "embed_and_dense": dbl_registry,
      }
  
file_path: privacy/tensorflow_privacy/privacy/fast_gradient_clipping/registry_functions/nlp_position_embedding_test.py
imports: from absl.testing import parameterized
  import tensorflow
  import tensorflow_models
  from tensorflow_privacy.privacy.fast_gradient_clipping import common_test_utils
  from tensorflow_privacy.privacy.fast_gradient_clipping import layer_registry
  from tensorflow_privacy.privacy.fast_gradient_clipping.registry_functions import dense
  from tensorflow_privacy.privacy.fast_gradient_clipping.registry_functions import nlp_position_embedding
label_desc: Use image node_id 3 for calling a global function with example usage: get_nlp_position_embedding_layer_registries() and returns: dict