Upload app.py

app.py

@@ -46,6 +46,7 @@ def fn(glycan, model):
     glycan = [glycan]
     label = [0]
     data = next(iter(dataset_to_dataloader(glycan, label, batch_size=1)))
+    
     if model == "Ensemble":
         pred = model_pred(data)
     else:
@@ -57,6 +58,7 @@ def fn(glycan, model):
         edge_index = edge_index.to(device)
         batch = batch.to(device)
         pred = model_pred(x,edge_index, batch).cpu().detach().numpy()[0]
+    
     pred = np.exp(pred)/sum(np.exp(pred)) # Softmax 
     pred = [float(x) for x in pred]
     pred = {class_list[i]:pred[i] for i in range(15)}
@@ -65,7 +67,7 @@ def fn(glycan, model):
 
 demo = gr.Interface(
     fn=fn,
-    inputs=[gr.Textbox(label="Glycan sequence"), gr.Radio(label="Model",choices=["No data augmentation", "Random node deletion"])],
+    inputs=[gr.Textbox(label="Glycan sequence"), gr.Radio(label="Model",choices=["No data augmentation", "Random node deletion", "Ensemble"])],
     outputs=[gr.Label(num_top_classes=15, label="Prediction")],
     allow_flagging=False,
     title="SweetNet demo",