Save configuration files and logs only during training

tools/program.py

@@ -332,7 +332,7 @@ def eval(model, valid_dataloader, post_process_class, eval_class):
     return metirc
 
 
-def preprocess():
+def preprocess(is_train=False):
     FLAGS = ArgsParser().parse_args()
     config = load_config(FLAGS.config)
     merge_config(FLAGS.opt)
@@ -350,15 +350,17 @@ def preprocess():
     device = paddle.set_device(device)
 
     config['Global']['distributed'] = dist.get_world_size() != 1
-
+    if is_train:
         # save_config
         save_model_dir = config['Global']['save_model_dir']
         os.makedirs(save_model_dir, exist_ok=True)
         with open(os.path.join(save_model_dir, 'config.yml'), 'w') as f:
-        yaml.dump(dict(config), f, default_flow_style=False, sort_keys=False)
-
-    logger = get_logger(
-        name='root', log_file='{}/train.log'.format(save_model_dir))
+            yaml.dump(
+                dict(config), f, default_flow_style=False, sort_keys=False)
+        log_file = '{}/train.log'.format(save_model_dir)
+    else:
+        log_file = None
+    logger = get_logger(name='root', log_file=log_file)
     if config['Global']['use_visualdl']:
         from visualdl import LogWriter
         vdl_writer_path = '{}/vdl/'.format(save_model_dir)

tools/train.py

@@ -110,6 +110,6 @@ def test_reader(config, device, logger):
 
 
 if __name__ == '__main__':
-    config, device, logger, vdl_writer = program.preprocess()
+    config, device, logger, vdl_writer = program.preprocess(is_train=True)
     main(config, device, logger, vdl_writer)
     # test_reader(config, device, logger)