code: def test_over_255_categories_in_column():
      np.random.seed(42)
  
      letters = string.ascii_letters
      categories = [
          "".join(random.choice(letters) for _ in range(5))
          for _ in range(300)
      ]
  
      train_data = np.concatenate(
          [
              np.random.randn(1000, 1),
              np.random.choice(a=categories, size=(1000, 1)),
          ],
          axis=1,
      )
      test_data = np.concatenate(
          [
              np.random.randn(1000, 1),
              np.random.choice(a=categories, size=(1000, 1)),
          ],
          axis=1,
      )
  
      df_train = pd.DataFrame(
          train_data,
          columns=[
              "numeric_without_drift",
              "categorical_with_many_categories",
          ],
      )
      df_test = pd.DataFrame(test_data, columns=df_train.columns)
  
      df_test["categorical_with_many_categories"] = np.random.choice(
          a=categories[20:280], size=(1000, 1)
      )
  
      df_train = df_train.astype({"numeric_without_drift": "float"})
      df_test = df_test.astype({"numeric_without_drift": "float"})
  
      label = np.random.randint(0, 2, size=(df_train.shape[0],))
      df_train["target"] = label
      train_ds = Dataset(
          df_train,
          cat_features=["categorical_with_many_categories"],
          label="target",
      )
  
      label = np.random.randint(0, 2, size=(df_test.shape[0],))
      df_test["target"] = label
      test_ds = Dataset(
          df_test,
          cat_features=["categorical_with_many_categories"],
          label="target",
      )
  
      check = MultivariateDrift()
  
      # Act
      result = check.run(train_ds, test_ds)
  
      # Assert
      # we only care that it runs
      assert_that(result.value["domain_classifier_auc"])
  
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 6 for calling a global function with example usage: test_over_255_categories_in_column() without return types