code: def test_new_data(diabetes_split_dataset_and_model):
      class NewDataCheck(TrainTestCheck):
          def run_logic(self, context: Context) -> CheckResult:
              model = context.model
              row = context.train.features_columns.head(1)
              row["s1"] = [0]
              return_value = model.predict(row)
              return CheckResult(return_value)
  
      # Arrange
      train, test, clf = diabetes_split_dataset_and_model
      (
          y_pred_train,
          y_pred_test,
          y_proba_train,
          y_proba_test,
      ) = _dummify_model(train, test, clf)
  
      # Act
      assert_that(
          calling(NewDataCheck().run).with_args(
              train_dataset=train,
              test_dataset=test,
              y_pred_train=y_pred_train,
              y_pred_test=y_pred_test,
              y_proba_train=y_proba_train,
              y_proba_test=y_proba_test,
          ),
          raises(
              DeepchecksValueError,
              r"Data that has not been seen before passed for inference with static predictions. Pass a real model to "
              r"resolve this",
          ),
      )
  
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 8 for calling a global function with example usage: test_new_data(diabetes_split_dataset_and_model) and returns: CheckResult