code: def test_make_the_inputs_outputs(
      tmp_root_dir: Path,
      x,
      fitted_tree: DecisionTreeClassifier,
      template: str,
      language: str,
  ):
      if not can(fitted_tree, language, template, "predict"):
          pytest.skip(
              "Skip unsupported estimator/language/template combination"
          )
  
      # Directory:
      tmp_dir = fs_mkdir(
          tmp_root_dir,
          [
              ("test", "make_the_inputs_outputs"),
              ("estimator", "DecisionTreeClassifier"),
              ("language", language),
              ("template", template),
          ],
      )
  
      # Estimator:
      est = Estimator(fitted_tree)
      out = est.make(
          x,
          language=language,
          template=template,
          directory=tmp_dir,
          n_jobs=False,
          delete_created_files=False,
      )
  
      assert isinstance(out, tuple)
      assert len(out) == 2
      y_pred, y_proba = out
      if isinstance(x[0], (int, float)):
          assert isinstance(y_pred, np.int64)
          assert y_pred == 0
          assert isinstance(y_proba, np.ndarray)
          assert list(y_proba) == [1, 0, 0]
      if isinstance(x[0], (list, np.ndarray)):
          assert isinstance(y_pred, np.ndarray)
          assert y_pred[0] == 0
          assert isinstance(y_proba, np.ndarray)
          assert list(y_proba[0]) == [1, 0, 0]
  
imports: import os
  import random
  import shutil
  import warnings
  from os import environ
  from pathlib import Path
  from sys import version_info
  from typing import Callable, Tuple
  import numpy
  import pytest
  from joblib import dump
  from sklearn import preprocessing
  from sklearn.base import BaseEstimator
  from sklearn.datasets import load_iris
  from sklearn.ensemble.forest import ExtraTreesClassifier, RandomForestClassifier
  from sklearn.ensemble.weight_boosting import AdaBoostClassifier
  from sklearn.linear_model import SGDClassifier
  from sklearn.naive_bayes import BernoulliNB, GaussianNB
  from sklearn.neighbors.classification import KNeighborsClassifier
  from sklearn.svm import SVC, LinearSVC, NuSVC
  from sklearn.tree.tree import DecisionTreeClassifier
  from sklearn_porter import exceptions
  from sklearn_porter.cli.__main__ import parse_args
  from sklearn_porter.Estimator import Estimator, can, show
  from sklearn_porter.cli.command.port import main
  from sklearn_porter.cli.command.save import main
  from sklearn_porter.cli.command.show import main
  from tests.commons import SKLEARN_VERSION, CANDIDATES, CLASSIFIERS, DATASETS, Candidate, Dataset, ROOT_DIR, RESOURCES_DIR
  from tests.utils import dataset_generate_x, dataset_uniform_x, fs_mkdir
label_desc: Use image node_id 24 for calling a global function with example usage: test_make_the_inputs_outputs(tmp_root_dir, x, fitted_tree, template, language) without return types