Update app.py

app.py

@@ -34,17 +34,17 @@ def predict(instancia):
     inputs['out_degree'] = torch.tensor([instancia_preprocesada['out_degree']])
     inputs['spatial_pos'] = torch.tensor([instancia_preprocesada['spatial_pos']])
     inputs['attn_edge_type'] = torch.tensor([instancia_preprocesada['attn_edge_type']])
+    print(inputs)
     with torch.no_grad():
         logits = model(**inputs).logits
-    predicted_class_id = logits.argmax().item()
     return str(logits.item())
 
-ejemplos = ['''{"node_feat": [[0],[0],[0],[0],[0],[0],[0],[0],[1],[0],[0],[0],[0],[1],[2],[0],[0],[0],[0],[0],[0],[3],[0],[0]],
+ejemplos = '''{"node_feat": [[0],[0],[0],[0],[0],[0],[0],[0],[1],[0],[0],[0],[0],[1],[2],[0],[0],[0],[0],[0],[0],[3],[0],[0]],
      "edge_index": [[0,1,1,1,1,2,3,4,4,4,5,5,6,6,7,7,7,8,8,9,9,10,10,10,11,11,12,12,12,13,14,14,15,15,15,16,16,17,17,18,18,19,19,20,20,20,21,22,22,22,23,23]],
      "edge_attr": [[1],[1],[1],[1],[1],[1],[1],[1],[2],[1],[2],[1],[1],[2],[2],[1],[1],[1],[1],[1],[2],[2],[1],[1],[1],[1],[1],[2],[1],[2],[1],[1],[1],[2],[1],[2],[1],[1],[2],[2],[1],[1],[2],[1],[2],[1],[1],[1],[1],[2],[1],[2]],
      "y": [3.1381945610046387],
      "num_nodes": 24}'''
-]
+
 
 # Crear la interfaz Gradio
 interfaz = gr.Interface(fn=predict, inputs="text", outputs='text', examples=ejemplos)