app fixes_v4

app.py

@@ -83,16 +83,16 @@ class DebertPaperClassifierV5(torch.nn.Module):
         else:
             self.loss_fct = torch.nn.BCEWithLogitsLoss()
 
-    def forward(self, input_ids, attention_mask, labels=None):
-        outputs = self.deberta(
-            input_ids=input_ids,
-            attention_mask=attention_mask
-        )
-        logits = self.classifier(outputs.last_hidden_state[:, 0, :])
-        loss = None
-        if labels is not None:
-            loss = self.loss_fct(logits, labels)
-        return (loss, logits) if loss is not None else logits
+        def forward(self, input_ids, attention_mask, labels=None):
+            outputs = self.deberta(
+                input_ids=input_ids,
+                attention_mask=attention_mask
+            )
+            logits = self.classifier(outputs.last_hidden_state[:, 0, :])
+            loss = None
+            if labels is not None:
+                loss = self.loss_fct(logits, labels)
+            return (loss, logits) if loss is not None else logits
 
     def _init_weights(self):
         for module in self.classifier.modules():