Merge branch 'master' of github.com:victoresque/pytorch-template into update

Author: SunQpark

base/base_trainer.py

@@ -61,6 +61,7 @@ def train(self):
         """
         Full training logic
         """
+        not_improved_count = 0
         for epoch in range(self.start_epoch, self.epochs + 1):
             result = self._train_epoch(epoch)
 
@@ -90,7 +91,6 @@ def train(self):
                                         "Model performance monitoring is disabled.".format(self.mnt_metric))
                     self.mnt_mode = 'off'
                     improved = False
-                    not_improved_count = 0
 
                 if improved:
                     self.mnt_best = log[self.mnt_metric]

parse_config.py

@@ -17,17 +17,20 @@ def __init__(self, args, options='', timestamp=True):
 
         if args.device:
             os.environ["CUDA_VISIBLE_DEVICES"] = args.device
-        if args.resume:
-            self.resume = Path(args.resume)
-            self.cfg_fname = self.resume.parent / 'config.json'
-        else:
+        if args.resume is None:
             msg_no_cfg = "Configuration file need to be specified. Add '-c config.json', for example."
             assert args.config is not None, msg_no_cfg
-            self.resume = None
             self.cfg_fname = Path(args.config)
+            config = read_json(self.cfg_fname)
+            self.resume = None
+        else:        
+            self.resume = Path(args.resume)
+            resume_cfg_fname = self.resume.parent / 'config.json'
+            config = read_json(resume_cfg_fname)
+            if args.config is not None:
+                config.update(read_json(Path(args.config)))
 
         # load config file and apply custom cli options
-        config = read_json(self.cfg_fname)
         self._config = _update_config(config, options, args)
 
         # set save_dir where trained model and log will be saved.