fix formatting

lm_eval/tasks/coqa/utils.py

@@ -2,6 +2,7 @@ from itertools import zip_longest
 
 import transformers.data.metrics.squad_metrics as squad_metrics
 
+
 def doc_to_text(doc):
     # Given a passage p, the conversation history {q1, a1, . . . qi−1, ai−1}
     # and a question qi, the task is to predict the answer ai
@@ -41,14 +42,13 @@ def em(gold_list, pred):
         for i in range(len(gold_list)):
             gold_answers = gold_list[0:i] + gold_list[i + 1 :]
             # predictions compared against (n) golds and take maximum
-            em_sum += max(
-                squad_metrics.compute_exact(a, pred) for a in gold_answers
-            )
+            em_sum += max(squad_metrics.compute_exact(a, pred) for a in gold_answers)
     else:
         em_sum += max(squad_metrics.compute_exact(a, pred) for a in gold_list)
 
     return em_sum / max(1, len(gold_list))
 
+
 def compute_scores(gold_list, pred):
     # tests for exact match and on the normalised answer (compute_exact)
     # test for overlap (compute_f1)
@@ -58,9 +58,7 @@ def compute_scores(gold_list, pred):
         for i in range(len(gold_list)):
             gold_answers = gold_list[0:i] + gold_list[i + 1 :]
             # predictions compared against (n) golds and take maximum
-            em_sum += max(
-                squad_metrics.compute_exact(a, pred) for a in gold_answers
-            )
+            em_sum += max(squad_metrics.compute_exact(a, pred) for a in gold_answers)
             f1_sum += max(squad_metrics.compute_f1(a, pred) for a in gold_answers)
     else:
         em_sum += max(squad_metrics.compute_exact(a, pred) for a in gold_list)
@@ -71,6 +69,7 @@ def compute_scores(gold_list, pred):
         "f1": f1_sum / max(1, len(gold_list)),
     }
 
+
 def process_results(doc, results):
 
     gold_list = doc_to_target(doc)