[to #42322933] Fix bug in release

Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/10173975

modelscope/trainers/hooks/checkpoint_hook.py

@@ -117,20 +117,20 @@ class CheckpointHook(Hook):
         for i, hook in enumerate(trainer.hooks):
             # hook: Hook
             key = f'{hook.__class__}-{i}'
-            if key in meta:
+            if key in meta and hasattr(hook, 'load_state_dict'):
                 hook.load_state_dict(meta[key])
             else:
-                trainer.logger(
+                trainer.logger.warn(
                     f'The state_dict of hook {hook.__class__} at index {i} is not found in the checkpoint file.'
                 )
 
         version = meta.get('modelscope')
         if version != __version__:
-            trainer.logger(
+            trainer.logger.warn(
                 f'The modelscope version of loaded checkpoint does not match the runtime version. '
                 f'The saved version: {version}, runtime version: {__version__}'
             )
-        trainer.logger(
+        trainer.logger.warn(
             f'Checkpoint {filename} saving time: {meta.get("time")}')
         return meta
 
@@ -149,7 +149,8 @@ class CheckpointHook(Hook):
             'rng_state': self.rng_state,
         }
         for i, hook in enumerate(trainer.hooks):
-            meta[f'{hook.__class__}-{i}'] = hook.state_dict()
+            if hasattr(hook, 'state_dict'):
+                meta[f'{hook.__class__}-{i}'] = hook.state_dict()
 
         save_checkpoint(
             trainer.model,
@@ -239,6 +240,7 @@ class BestCkptSaverHook(CheckpointHook):
         self.rule = rule
         self._best_metric = None
         self._best_ckpt_file = None
+        self.save_file_name = save_file_name
 
     def _should_save(self, trainer):
         return self._is_best_metric(trainer.metric_values)

modelscope/utils/checkpoint.py

@@ -87,9 +87,8 @@ def save_checkpoint(model: torch.nn.Module,
                 checkpoint['optimizer'][name] = optim.state_dict()
 
         # save lr_scheduler state dict in the checkpoint
-        assert isinstance(lr_scheduler, _LRScheduler), \
-            f'lr_scheduler to be saved should be a subclass of _LRScheduler, current is : {lr_scheduler.__class__}'
-        checkpoint['lr_scheduler'] = lr_scheduler.state_dict()
+        if lr_scheduler is not None and hasattr(lr_scheduler, 'state_dict'):
+            checkpoint['lr_scheduler'] = lr_scheduler.state_dict()
     else:
         checkpoint = weights_to_cpu(model.state_dict())
 

modelscope/utils/hub.py

@@ -142,8 +142,8 @@ def parse_label_mapping(model_dir):
             id2label = config[ConfigFields.preprocessor].id2label
             label2id = {label: id for id, label in id2label.items()}
 
-    if label2id is None:
-        config_path = os.path.join(model_dir, 'config.json')
+    config_path = os.path.join(model_dir, 'config.json')
+    if label2id is None and os.path.exists(config_path):
         config = Config.from_file(config_path)
         if hasattr(config, 'label2id'):
             label2id = config.label2id