code: def _dummify_model(train, test, model):
      y_pred_train = y_pred_test = y_proba_train = y_proba_test = None
      if hasattr(model, "predict"):
          if train is not None:
              y_pred_train = model.predict(train.features_columns)
          if test is not None:
              y_pred_test = model.predict(test.features_columns)
      if hasattr(model, "predict_proba"):
          if train is not None:
              y_proba_train = model.predict_proba(
                  train.features_columns
              )
          if test is not None:
              y_proba_test = model.predict_proba(test.features_columns)
  
      return y_pred_train, y_pred_test, y_proba_train, y_proba_test
  
imports: from hamcrest import assert_that, calling, close_to, has_items, raises
  from deepchecks.core.check_result import CheckResult
  from deepchecks.core.condition import ConditionCategory
  from deepchecks.core.errors import DeepchecksValueError, ValidationError
  from deepchecks.tabular.base_checks import TrainTestCheck
  from deepchecks.tabular.checks import SingleDatasetPerformance
  from deepchecks.tabular.checks.model_evaluation.regression_error_distribution import RegressionErrorDistribution
  from deepchecks.tabular.checks.model_evaluation.roc_report import RocReport
  from deepchecks.tabular.checks.model_evaluation.simple_model_comparison import SimpleModelComparison
  from deepchecks.tabular.context import Context
  from deepchecks.tabular.dataset import Dataset
  from deepchecks.tabular.suites.default_suites import full_suite
  from deepchecks.tabular.utils.task_type import TaskType
  from tests.base.utils import equal_condition_result
  from tests.common import get_expected_results_length, validate_suite_result
  from tests.tabular.checks.model_evaluation.simple_model_comparison_test import assert_regression
label_desc: Use image node_id 1 for calling a global function with example usage: _dummify_model(train, test, model) and returns: y_pred_train,  y_pred_test,  y_proba_train,  y_proba_test