import transformers
from transformers import GraphormerForGraphClassification
import gradio as gr

import os 
try:
    import toml
except ImportError:
    os.system('pip install toml')
    import toml
print('todo en orden')
model = GraphormerForGraphClassification.from_pretrained("PedroLancharesSanchez/graph-regression")

def predict(instancia):
  instancia_preprocesada=preprocess_item(instancia)
  inputs={}
  inputs['input_nodes'] = torch.tensor([instancia_preprocesada['input_nodes']])
  inputs['input_edges'] = torch.tensor([instancia_preprocesada['input_edges']])
  inputs['attn_bias'] = torch.tensor([instancia_preprocesada['attn_bias']])
  inputs['in_degree'] = torch.tensor([instancia_preprocesada['in_degree']])
  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']])
  with torch.no_grad():
    logits = model(**inputs).logits
  predicted_class_id = logits.argmax().item()
  return logits
    
graph_input = gr.inputs.Graph(graph_type="networkx", label="Grafo de entrada")
regression_output = gr.outputs.Textbox(label="Valor de regresión")

gr.Interface(fn=predict, inputs=graph_input, outputs=regression_output,examples=['grafo1.json','grafo2.json']).launch(share=False)