adding save checkpoint and loading in examples

examples/run_classifier.py

@@ -329,7 +329,7 @@ def main():
                         default=None,
                         type=str,
                         required=True,
-                        help="The output directory where the model checkpoints will be written.")
+                        help="The output directory where the model predictions and checkpoints will be written.")
 
     ## Other parameters
     parser.add_argument("--max_seq_length",
@@ -593,6 +593,10 @@ def main():
                   'global_step': global_step,
                   'loss': tr_loss/nb_tr_steps}
 
+        model_to_save = model.module if hasattr(model, 'module') else model
+        raise NotImplementedError # TODO add save of the configuration file and vocabulary file also ?
+        output_model_file = os.path.join(args.output_dir, "pytorch_model.bin")
+        torch.save(model_to_save, output_model_file)
         output_eval_file = os.path.join(args.output_dir, "eval_results.txt")
         with open(output_eval_file, "w") as writer:
             logger.info("***** Eval results *****")

examples/run_squad.py

@@ -690,7 +690,7 @@ def main():
                         help="Bert pre-trained model selected in the list: bert-base-uncased, "
                              "bert-large-uncased, bert-base-cased, bert-base-multilingual, bert-base-chinese.")
     parser.add_argument("--output_dir", default=None, type=str, required=True,
-                        help="The output directory where the model checkpoints will be written.")
+                        help="The output directory where the model checkpoints and predictions will be written.")
 
     ## Other parameters
     parser.add_argument("--train_file", default=None, type=str, help="SQuAD json for training. E.g., train-v1.1.json")