best_checkpoint_path = Engine.get_best_chechpoint(
os.path.join(args.output, best_training_args_name))
logging.info(
'The best checkpoint %s. Picking up the model from there',
best_checkpoint_path,
)
model = model_cls.create_from_checkpoint(best_checkpoint_path, args.gpu)
engine.model = model
for corpus, dl in dataset.get_test_and_valid_data_loaders_map().items():
engine.valid(dl, corpus, use_progress_bar=False)
if __name__ == '__main__':
parser = argparse.ArgumentParser(description='ChatBot training script')
Dataset.add_cmd_arguments(parser)
parser.add_argument(
'-o',
'--output',
type=str,
help='Prefix for path to the checkpointing dir.',
)
parser.add_argument(
'--gpu',
type=int,
default=None,
help='GPU ID (default - CPU)',
)
parser.add_argument(
'--glove',
