code: def test_drift_without_display(drifted_data):
      # Arrange
      train_ds, test_ds = drifted_data
      check = MultivariateDrift()
  
      # Act
      result = check.run(train_ds, test_ds, with_display=False)
  
      # Assert
      assert_that(
          result.value,
          has_entries(
              {
                  "domain_classifier_auc": close_to(0.93, 0.001),
                  "domain_classifier_drift_score": close_to(0.86, 0.01),
                  "domain_classifier_feature_importance": has_entries(
                      {
                          "categorical_without_drift": close_to(
                              0, 0.02
                          ),
                          "numeric_without_drift": close_to(0, 0.02),
                          "categorical_with_drift": close_to(0, 0.02),
                          "numeric_with_drift": close_to(1, 0.02),
                      }
                  ),
              }
          ),
      )
      assert_that(result.display, has_length(0))
  
file_path: deepchecks/tests/tabular/checks/train_test_validation/multivariate_drift_test.py
imports: import random
  import string
  import numpy
  import pandas
  from hamcrest import assert_that, close_to, greater_than, has_entries, has_length
  from deepchecks.tabular.checks import MultivariateDrift
  from deepchecks.tabular.dataset import Dataset
  from tests.base.utils import equal_condition_result
label_desc: Use image node_id 3 for calling a global function with example usage: test_drift_without_display(drifted_data) without return types