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adding save checkpoint and loading in examples

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thomwolf
2018-12-09 17:04:23 -05:00
parent 85fff78c2d
commit b3caec5a56
2 changed files with 6 additions and 2 deletions
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6
examples/run_classifier.py
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@@ -329,7 +329,7 @@ def main():
default=None, default=None,
type=str, type=str,
required=True, 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 ## Other parameters
parser.add_argument("--max_seq_length", parser.add_argument("--max_seq_length",
@@ -593,6 +593,10 @@ def main():
'global_step': global_step, 'global_step': global_step,
'loss': tr_loss/nb_tr_steps} '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") output_eval_file = os.path.join(args.output_dir, "eval_results.txt")
with open(output_eval_file, "w") as writer: with open(output_eval_file, "w") as writer:
logger.info("***** Eval results *****") logger.info("***** Eval results *****")

2
examples/run_squad.py
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@@ -690,7 +690,7 @@ def main():
help="Bert pre-trained model selected in the list: bert-base-uncased, " help="Bert pre-trained model selected in the list: bert-base-uncased, "
"bert-large-uncased, bert-base-cased, bert-base-multilingual, bert-base-chinese.") "bert-large-uncased, bert-base-cased, bert-base-multilingual, bert-base-chinese.")
parser.add_argument("--output_dir", default=None, type=str, required=True, 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 ## Other parameters
parser.add_argument("--train_file", default=None, type=str, help="SQuAD json for training. E.g., train-v1.1.json") parser.add_argument("--train_file", default=None, type=str, help="SQuAD json for training. E.g., train-v1.1.json")