Update app.py

app.py

@@ -265,13 +265,15 @@ def run_diagnosis(
     logits = model(x)
     probs = torch.sigmoid(logits)[0].cpu().numpy()
 
+    print("predicted logits\n")
+    for i, logit_ in enumerate(logits):
+        print(f"{Idx2labels[i]}: {logit_}")
+        
     output_probs = {
-        Idx2labels[i]: float(p) for i, p in enumerate(probs)
-    }
+        Idx2labels[i]: float(p) for i, p in enumerate(probs)}
 
     predicted_classes = [
-        Idx2labels[i] for i, p in enumerate(probs) if p >= threshold
-    ]
+        Idx2labels[i] for i, p in enumerate(probs) if p >= threshold]
 
     return "\n".join(predicted_classes), output_probs