Add flag for do_lower_case in export_tfhub.py

PiperOrigin-RevId: 306669872

official/nlp/bert/export_tfhub.py

@@ -20,6 +20,7 @@ from __future__ import print_function
 
 from absl import app
 from absl import flags
+from absl import logging
 import tensorflow as tf
 from typing import Text
 from official.nlp.bert import bert_models
@@ -34,6 +35,9 @@ flags.DEFINE_string("model_checkpoint_path", None,
 flags.DEFINE_string("export_path", None, "TF-Hub SavedModel destination path.")
 flags.DEFINE_string("vocab_file", None,
                     "The vocabulary file that the BERT model was trained on.")
+flags.DEFINE_bool("do_lower_case", None, "Whether to lowercase. If None, "
+                  "do_lower_case will be enabled if 'uncased' appears in the "
+                  "name of --vocab_file")
 
 
 def create_bert_model(bert_config: configs.BertConfig) -> tf.keras.Model:
@@ -65,21 +69,26 @@ def create_bert_model(bert_config: configs.BertConfig) -> tf.keras.Model:
 
 def export_bert_tfhub(bert_config: configs.BertConfig,
                       model_checkpoint_path: Text, hub_destination: Text,
-                      vocab_file: Text):
+                      vocab_file: Text, do_lower_case: bool = None):
   """Restores a tf.keras.Model and saves for TF-Hub."""
+  # If do_lower_case is not explicit, default to checking whether "uncased" is
+  # in the vocab file name
+  if do_lower_case is None:
+    do_lower_case = "uncased" in vocab_file
+    logging.info("Using do_lower_case=%s based on name of vocab_file=%s",
+                 do_lower_case, vocab_file)
   core_model, encoder = create_bert_model(bert_config)
   checkpoint = tf.train.Checkpoint(model=encoder)
   checkpoint.restore(model_checkpoint_path).assert_consumed()
   core_model.vocab_file = tf.saved_model.Asset(vocab_file)
-  core_model.do_lower_case = tf.Variable(
-      "uncased" in vocab_file, trainable=False)
+  core_model.do_lower_case = tf.Variable(do_lower_case, trainable=False)
   core_model.save(hub_destination, include_optimizer=False, save_format="tf")
 
 
 def main(_):
   bert_config = configs.BertConfig.from_json_file(FLAGS.bert_config_file)
   export_bert_tfhub(bert_config, FLAGS.model_checkpoint_path, FLAGS.export_path,
-                    FLAGS.vocab_file)
+                    FLAGS.vocab_file, FLAGS.do_lower_case)
 
 
 if __name__ == "__main__":