merge

rageval/metrics/answer_informativeness/_text_length.py

@@ -61,7 +61,7 @@ def __init__(self, tokenize_model: str = "Qwen/Qwen2-0.5B-Instruct"):
 
     def __repr__(self) -> str:
         """:return: Formatted string representation of the metric."""
-        return f"{self.ALIAS[0]}" # pragma: no cover
+        return f"{self.ALIAS[0]}"  # pragma: no cover
 
     def _info(self):
         return datasets.MetricInfo(

rageval/metrics/base.py

@@ -113,15 +113,15 @@ def _compute_batch(
     ) -> List[float]:
         """Compute the metric for a batch of predictions and references."""
         scores = []
-        if (pred_answers and ref_answers): # if both columns exist
+        if (pred_answers and ref_answers):  # if both columns exist
             for pred_answer, ref_answer in tqdm(zip(pred_answers, ref_answers),
-                                desc=f"Computing {self.name}",
-                                total=len(pred_answers)):
+                                                    desc=f"Computing {self.name}",
+                                                    total=len(pred_answers)):
                 scores.append(self._compute_one(pred_answer, ref_answer))
         else:
             for pred_answer in tqdm(pred_answers,
-                                desc=f"Computing {self.name}",
-                                total=len(pred_answers)):
+                                    desc=f"Computing {self.name}",
+                                    total=len(pred_answers)):
                 scores.append(self._compute_one(pred_answer))
         return scores