add id field to wandb and remove dublicate code from train

config/wandb_config.py

@@ -11,6 +11,7 @@ class WandbConfig(BaseModel):
     group: str | None = None        # WandB group name
     entity: str | None = None       # WandB entity (user or team)
     name: str | None = None         # Name of the run
+    id: str | None = None           # Id of the run
     tags: list[str] | None = None   # List of tags for the run
     notes: str | None = None        # Notes or description for the run
     save_code: bool = True          # Whether to save the code to WandB

core/segmentator.py

@@ -382,12 +382,7 @@ class CellSegmentator:
             self._model.load_state_dict(self._best_weights)
 
         if self._test_dataloader is not None:
-            test_metrics = self.__run_epoch("test", save_results=save_results, only_masks=only_masks)
-            self.__print_with_logging(test_metrics, 0)
-            
-            save_path = self._dataset_setup.common.predictions_dir
-            os.makedirs(save_path, exist_ok=True)
-            self.__save_metrics_to_csv(test_metrics, os.path.join(save_path, 'metrics.csv'))
+            self.evaluate(save_results=save_results, only_masks=only_masks)
 
   
     def evaluate(self, save_results: bool = True, only_masks: bool = False) -> None:
@@ -693,6 +688,8 @@ class CellSegmentator:
                 logger.info(f"├─ Entity:  {self._wandb_config.entity}")
             if self._wandb_config.name:
                 logger.info(f"├─ Run name: {self._wandb_config.name}")
+            if self._wandb_config.id:
+                logger.info(f"├─ Run id: {self._wandb_config.id}")
             if self._wandb_config.tags:
                 logger.info(f"├─ Tags:     {', '.join(self._wandb_config.tags)}")
             if self._wandb_config.notes: