Add an option to disable the progress bars

code/train.py

@@ -30,6 +30,7 @@ if __name__ == "__main__":
     DEFAULT_TEST_SIZE = 0.2
     DEFAULT_RANDOM_SEED_NUMBER = 1
     DEFAULT_TRAIN_ON_SUBSET = 'train'
+    DEFAULT_DISABLE_PROGRESS = False
 
     begin_random_seed_range = 1
     end_random_seed_range = 2000
@@ -46,6 +47,7 @@ if __name__ == "__main__":
     parser.add_argument('--random_seed_number', nargs='?', type=int, default=DEFAULT_RANDOM_SEED_NUMBER, help='Number of random seeds used.')
     parser.add_argument('--seeds', nargs='+', type=int, default=None, help='Specific a list of seeds instead of generate them randomly')
     parser.add_argument('--train_on_subset', nargs='?', type=str, default=DEFAULT_TRAIN_ON_SUBSET, help='Specify on witch subset the model will be trained (either train or dev).')
+    parser.add_argument('--disable_progress', action='store_true', default=DEFAULT_DISABLE_PROGRESS, help='Disable the progress bars.')
     args = parser.parse_args()
 
     pathlib.Path(args.models_dir).mkdir(parents=True, exist_ok=True)
@@ -68,7 +70,7 @@ if __name__ == "__main__":
 
     logger.info('Experiment id: {}'.format(experiment_id_str))
 
-    with tqdm(seeds) as seed_bar:
+    with tqdm(seeds, disable=args.disable_progress) as seed_bar:
         for seed in seed_bar:
             seed_bar.set_description('seed={}'.format(seed))
             seed_str = str(seed)
@@ -90,7 +92,7 @@ if __name__ == "__main__":
 
             trainer = Trainer(dataset)
 
-            with tqdm(args.extracted_forest_size) as extracted_forest_size_bar:
+            with tqdm(args.extracted_forest_size, disable=args.disable_progress) as extracted_forest_size_bar:
                 for extracted_forest_size in extracted_forest_size_bar:
                     extracted_forest_size_bar.set_description('extracted_forest_size={}'.format(extracted_forest_size))
                     sub_models_dir = models_dir + os.sep + 'extracted_forest_size' + os.sep + str(extracted_forest_size)