Internal Change

PiperOrigin-RevId: 315843901

official/nlp/bert/bert_models.py

@@ -175,7 +175,8 @@ def pretrain_model(bert_config,
                    seq_length,
                    max_predictions_per_seq,
                    initializer=None,
-                   use_next_sentence_label=True):
+                   use_next_sentence_label=True,
+                   return_core_pretrainer_model=False):
   """Returns model to be used for pre-training.
 
   Args:
@@ -185,10 +186,13 @@ def pretrain_model(bert_config,
         and use for pretraining.
       initializer: Initializer for weights in BertPretrainer.
       use_next_sentence_label: Whether to use the next sentence label.
+      return_core_pretrainer_model: Whether to also return the `BertPretrainer`
+        object.
 
   Returns:
-      Pretraining model as well as core BERT submodel from which to save
-      weights after pretraining.
+      A Tuple of (1) Pretraining model, (2) core BERT submodel from which to
+      save weights after pretraining, and (3) optional core `BertPretrainer`
+      object if argument `return_core_pretrainer_model` is True.
   """
   input_word_ids = tf.keras.layers.Input(
       shape=(seq_length,), name='input_word_ids', dtype=tf.int32)
@@ -245,7 +249,10 @@ def pretrain_model(bert_config,
     inputs['next_sentence_labels'] = next_sentence_labels
 
   keras_model = tf.keras.Model(inputs=inputs, outputs=output_loss)
-  return keras_model, transformer_encoder
+  if return_core_pretrainer_model:
+    return keras_model, transformer_encoder, pretrainer_model
+  else:
+    return keras_model, transformer_encoder
 
 
 def squad_model(bert_config,