FEAT: load model and continue to train

recbole/quick_start/__init__.py

@@ -1 +1 @@
-from recbole.quick_start.quick_start import run_recbole, objective_function, load_data_and_model
+from recbole.quick_start.quick_start import run_recbole, objective_function, load_data_and_model, continue_train

recbole/quick_start/quick_start.py

@@ -18,6 +18,36 @@
 from recbole.data import create_dataset, data_preparation, save_split_dataloaders, load_split_dataloaders
 from recbole.utils import init_logger, get_model, get_trainer, init_seed, set_color
 
+def continue_train(file_path):
+    logger = getLogger()
+    config, model, dataset, train_data, valid_data, test_data = load_data_and_model(
+        model_file=file_path,
+    )
+    # ------changed config--------#
+
+    # config['base_learning_rate']=1e-6
+    ##############################
+    # trainer loading and initialization
+    trainer = get_trainer(config['MODEL_TYPE'], config['model'], config['task'], config['robust'])(config, model)
+
+    # model training
+    best_valid_score, best_valid_result = trainer.fit(
+        train_data, valid_data, saved=True, show_progress=config['show_progress']
+    )
+
+    # model evaluation
+    test_result = trainer.evaluate(test_data, load_best_model=True, show_progress=config['show_progress'])
+
+    logger.info(set_color('best valid ', 'yellow') + f': {best_valid_result}')
+    logger.info(set_color('test result', 'yellow') + f': {test_result}')
+    return {
+        'best_valid_score': best_valid_score,
+        'valid_score_bigger': config['valid_metric_bigger'],
+        'best_valid_result': best_valid_result,
+        'test_result': test_result
+    }
+
+
 def run_recbole(model=None, dataset=None, config_file_list=None, config_dict=None, saved=True):
     r""" A fast running api, which includes the complete process of
     training and testing a model on a specified dataset
@@ -49,7 +79,6 @@ def run_recbole(model=None, dataset=None, config_file_list=None, config_dict=Non
     init_seed(config['seed'], config['reproducibility'])
     model = get_model(config['model'])(config, train_data.dataset).to(config['device'])
     logger.info(model)
-
     # trainer loading and initialization
     trainer = get_trainer(config['MODEL_TYPE'], config['model'],config['task'],config['robust'])(config, model)
 

run_continue.py

@@ -0,0 +1,23 @@
+# @Time   : 2020/7/20
+# @Author : Shanlei Mu
+# @Email  : [email protected]
+
+# UPDATE
+# @Time   : 2020/10/3, 2020/10/1
+# @Author : Yupeng Hou, Zihan Lin
+# @Email  : [email protected], [email protected]
+
+
+import argparse
+
+from recbole.quick_start import run_recbole, continue_train
+
+if __name__ == '__main__':
+    parser = argparse.ArgumentParser()
+
+    parser.add_argument('--file_path', '-f', type=str, default=None, help='config files')
+
+    args, _ = parser.parse_known_args()
+
+    # config_file_list = args.config_files.strip().split(' ') if args.config_files else None
+    continue_train(args.file_path)