code: def display_model(opt) -> Tuple[str, str, str]:
      """
      Run display_model.py.
  
      :return: (stdout_train, stdout_valid, stdout_test)
      """
      import parlai.scripts.display_model as dm
  
      parser = dm.setup_args()
      parser.set_params(**opt)
      popt = parser.parse_args([])
      with capture_output() as train_output:
          # evalmode so that we don't hit train_step
          popt["datatype"] = "train:evalmode:stream"
          dm.display_model(popt)
      with capture_output() as valid_output:
          popt["datatype"] = "valid:stream"
          dm.display_model(popt)
      with capture_output() as test_output:
          popt["datatype"] = "test:stream"
          dm.display_model(popt)
      return (
          train_output.getvalue(),
          valid_output.getvalue(),
          test_output.getvalue(),
      )
  
imports: import os
  import unittest
  import contextlib
  import tempfile
  import shutil
  import io
  import signal
  from typing import Tuple, Dict, Any
  from parlai.core.opt import Opt
  import parlai.utils.logging
  from parlai.utils.io import PathManager
  from pytest_regressions.data_regression import DataRegressionFixture
label_desc: Use image node_id 24 for calling a global function with example usage: display_model(opt) and returns: train_output,  valid_output,  test_output