fuck charcut fuck accuracy

bangalore_score.py

@@ -96,7 +96,7 @@ class Bangalore_Score(evaluate.Metric):
         evaluate.load('bleu')
         evaluate.load('rouge')
         evaluate.load('ncoop57/levenshtein_distance')
-        evaluate.load('BramVanroy/CharCut')
+        # evaluate.load('BramVanroy/CharCut')
         evaluate.load('exact_match')
         # evaluate.load('accuracy')
         pass
@@ -180,9 +180,9 @@ class Bangalore_Score(evaluate.Metric):
         )['exact_match']
 
         # charcut (data)
-        charcut = evaluate.load('BramVanroy/CharCut').compute(
-            predictions=proc_ds['predictions']['rows_text'], references=proc_ds['references']['rows_text']
-        )['charcut_mt']
+        # charcut = evaluate.load('BramVanroy/CharCut').compute(
+        #     predictions=proc_ds['predictions']['rows_text'], references=proc_ds['references']['rows_text']
+        # )['charcut_mt']
 
         # bleu (data)
         bleu = evaluate.load('bleu').compute(
@@ -208,7 +208,7 @@ class Bangalore_Score(evaluate.Metric):
 
         return {
             'exact_match_headers': exact_match_headers,
-            'charcut': charcut,
+            # 'charcut': charcut,
             'bleu': bleu,
             'rougeL': rougeL,
             'levenstein_distance': levenstein_distance,