[Fix] Fix bugs of multiple rounds of inference when using mm_eval (#201)

opencompass/tasks/mm_infer.py

@@ -6,6 +6,7 @@ import random
 import time
 from typing import List, Sequence
 
+import mmengine
 import torch
 import torch.distributed as dist
 from mmengine.config import Config, ConfigDict
@@ -75,8 +76,8 @@ class MultimodalInferTask:
         dataset_name = self.dataloader['dataset']['type']
         evaluator_name = self.evaluator[0]['type']
 
-        return osp.join(model_name,
-                        f'{dataset_name}-{evaluator_name}.{file_extension}')
+        return osp.join(self.cfg.work_dir, model_name, dataset_name,
+                        f'{evaluator_name}.{file_extension}')
 
     def get_output_paths(self, file_extension: str = 'json') -> List[str]:
         """Get the path to the output file.
@@ -90,7 +91,7 @@ class MultimodalInferTask:
         evaluator_name = self.evaluator[0]['type']
 
         return [
-            osp.join(model_name, dataset_name,
+            osp.join(self.cfg.work_dir, model_name, dataset_name,
                      f'{evaluator_name}.{file_extension}')
         ]
 
@@ -134,7 +135,8 @@ class MultimodalInferTask:
             evaluator.process(data_samples)
 
         metrics = evaluator.evaluate(len(dataloader.dataset))
-        metrics_file = osp.join(cfg.work_dir, 'res.log')
+        metrics_file = self.get_output_paths()[0]
+        mmengine.mkdir_or_exist(osp.split(metrics_file)[0])
         with open(metrics_file, 'w') as f:
             json.dump(metrics, f)