code: def run(ctx):
      ds, model, optimizer, loss, args = get_setting(ctx)
      trainer = train(ctx, ds, model, optimizer, loss, args)
      pred = predict(trainer, ds)
      if ctx.is_on_guest:
          # print("pred:", pred)
          # compute auc here
          from sklearn.metrics import roc_auc_score
  
          print("auc is")
          print(roc_auc_score(pred.label_ids, pred.predictions))
  
file_path: FATE/examples/launchers/sshe_nn_launcher.py
imports: import torch
  from fate.arch import Context
  from fate.ml.nn.hetero.hetero_nn import HeteroNNTrainerGuest, HeteroNNTrainerHost, TrainingArguments
  from fate.ml.nn.model_zoo.hetero_nn_model import HeteroNNModelGuest, HeteroNNModelHost
  from fate.ml.nn.model_zoo.hetero_nn_model import SSHEArgument
label_desc: Use image node_id 4 for calling a global function with example usage: run(ctx) without return types