m

inference.py

@@ -48,10 +48,15 @@ def predict_absa(text):
     inputs = tokenizer(text, return_tensors="pt", truncation=True, padding=True)
     with torch.no_grad():
         output = model(input_ids=inputs["input_ids"], attention_mask=inputs["attention_mask"])
+        print("output: ",output)
         pred_ids = output['logits'][0].tolist()
+        print("pred_ids: ",pred_ids)
 
     tokens = tokenizer.convert_ids_to_tokens(inputs["input_ids"][0])
     labels = [id2label.get(i, 'O') for i in pred_ids]
+    print("tokens: ",tokens)
+    print("labels: ",labels)
+
 
     result = bio_to_spans(tokens, labels)
     return [{"aspect": asp, "sentiment": pol} for asp, pol in result]