Update app.py

app.py

@@ -46,7 +46,7 @@ def _compute_softmax(scores):
         probs.append(score / total_sum)
     return probs
 
-def get_qa_nbest(start_logits, end_logits, seq_len, n_best_size=20, max_answer_length=30):
+def get_qa_nbest(input_ids, start_logits, end_logits, seq_len, n_best_size=20, max_answer_length=30):
     score_null = 1000000  # large and positive
     prelim_predictions = []
     null_start_logit = 0  # the start logit at the slice with min null score
@@ -92,7 +92,7 @@ def get_qa_nbest(start_logits, end_logits, seq_len, n_best_size=20, max_answer_l
             break
         
         if pred.start_index > 0:  # this is a non-null prediction\
-            predict_answer_tokens = inputs.input_ids[0, pred.start_index: (pred.end_index + 1)]
+            predict_answer_tokens = input_ids[0, pred.start_index: (pred.end_index + 1)]
             final_text = tokenizer.decode(predict_answer_tokens)
             if final_text in seen_predictions:
                 continue
@@ -170,7 +170,7 @@ def inference(question, context):
     cls_divide = cls_logits[1] - cls_logits[0]
 
 
-    nbest, score_diff = get_qa_nbest(qa_outputs.start_logits[0], qa_outputs.end_logits[0], seq_len=seq_len)
+    nbest, score_diff = get_qa_nbest(inputs.input_ids, qa_outputs.start_logits[0], qa_outputs.end_logits[0], seq_len=seq_len)
 
     thresh = -1.246073067188263