Update handler.py

handler.py

@@ -43,14 +43,14 @@ class EndpointHandler:
             hate_speech_logits = outputs.get('hate_speech')
 
         # Decode predictions from logits using argmax and the label encoders
-        emotion_preds = torch.argmax(emotion_logits, dim=1).cpu().numpy()
-        polarity_preds = torch.argmax(polarity_logits, dim=1).cpu().numpy()
-        hate_speech_preds = torch.argmax(hate_speech_logits, dim=1).cpu().numpy()
+        emotion_preds = torch.argmax(emotion_logits, dim=1).cpu().numpy().tolist()  
+        polarity_preds = torch.argmax(polarity_logits, dim=1).cpu().numpy().tolist()  
+        hate_speech_preds = torch.argmax(hate_speech_logits, dim=1).cpu().numpy().tolist()  
 
         # Inverse transform the predictions to get human-readable labels
-        decoded_emotions = self.emotion_encoder.inverse_transform(emotion_preds)
-        decoded_polarities = self.polarity_encoder.inverse_transform(polarity_preds)
-        decoded_hate_speech = self.hate_speech_encoder.inverse_transform(hate_speech_preds)
+        decoded_emotions = self.emotion_encoder.inverse_transform(emotion_preds).tolist()
+        decoded_polarities = self.polarity_encoder.inverse_transform(polarity_preds).tolist()
+        decoded_hate_speech = self.hate_speech_encoder.inverse_transform(hate_speech_preds).tolist()
 
         # Return the decoded results as a dictionary
         return {