code: def test_condition_fail_on_overlap_date_in_index():
      # Arrange
      train_ds = Dataset(
          pd.DataFrame(
              np.ones((14, 1)),
              columns=["col1"],
              index=[
                  datetime(2021, 10, 1, 0, 0),
                  datetime(2021, 10, 1, 1, 0),
                  datetime(2021, 10, 1, 2, 0),
                  datetime(2021, 10, 2, 0, 0),
                  datetime(2021, 10, 2, 1, 0),
                  datetime(2021, 10, 2, 2, 0),
                  datetime(2021, 10, 3, 0, 0),
                  datetime(2021, 10, 3, 1, 0),
                  datetime(2021, 10, 3, 2, 0),
                  datetime(2021, 10, 4, 0, 0),
                  datetime(2021, 10, 4, 1, 0),
                  datetime(2021, 10, 4, 2, 0),
                  datetime(2021, 10, 5, 0, 0),
                  datetime(2021, 10, 5, 1, 0),
              ],
          ),
          set_datetime_from_dataframe_index=True,
      )
  
      val_ds = Dataset(
          pd.DataFrame(
              np.ones((11, 1)),
              columns=["col1"],
              index=[
                  datetime(2021, 9, 4, 0, 0),
                  datetime(2021, 10, 4, 0, 0),
                  datetime(2021, 10, 5, 0, 0),
                  datetime(2021, 10, 6, 0, 0),
                  datetime(2021, 10, 6, 1, 0),
                  datetime(2021, 10, 7, 0, 0),
                  datetime(2021, 10, 7, 1, 0),
                  datetime(2021, 10, 8, 0, 0),
                  datetime(2021, 10, 8, 1, 0),
                  datetime(2021, 10, 9, 0, 0),
                  datetime(2021, 10, 9, 1, 0),
              ],
          ),
          set_datetime_from_dataframe_index=True,
      )
  
      check = DateTrainTestLeakageOverlap().add_condition_leakage_ratio_less_or_equal(
          0.17
      )
  
      # Act
      result = check.conditions_decision(check.run(train_ds, val_ds))
  
      assert_that(
          result,
          has_items(
              equal_condition_result(
                  is_pass=False,
                  name="Date leakage ratio is less or equal to 17%",
                  details="Found 27.27% leaked dates",
              )
          ),
      )
  
imports: from datetime import datetime
  import numpy
  import pandas
  from hamcrest import assert_that, calling, close_to, equal_to, greater_than, has_items, has_length, raises
  from deepchecks.core.errors import DatasetValidationError, DeepchecksValueError
  from deepchecks.tabular.checks.train_test_validation import DateTrainTestLeakageDuplicates, DateTrainTestLeakageOverlap
  from deepchecks.tabular.dataset import Dataset
  from tests.base.utils import equal_condition_result
label_desc: Use image node_id 13 for calling a global function with example usage: test_condition_fail_on_overlap_date_in_index() without return types