code: def test_condition_ratio_not_greater_than_passed(
      diabetes_split_dataset_and_model,
  ):
      # Arrange
      train_ds, val_ds, clf = diabetes_split_dataset_and_model
      check = (
          TrainTestSamplesMix().add_condition_duplicates_ratio_less_or_equal()
      )
  
      # Act
      result = check.conditions_decision(
          check.run(train_ds, val_ds, clf)
      )
  
      assert_that(
          result,
          has_items(
              equal_condition_result(
                  is_pass=True,
                  details="No samples mix found",
                  name="Percentage of test data samples that appear in train data is less or equal to 5%",
              )
          ),
      )
  
file_path: deepchecks/tests/tabular/checks/train_test_validation/train_test_samples_mix_test.py
imports: import numpy
  import pandas
  from hamcrest import assert_that, calling, equal_to, greater_than, has_entry, has_items, has_length, raises
  from sklearn.model_selection import train_test_split
  from deepchecks.core.errors import DeepchecksValueError
  from deepchecks.tabular.checks.train_test_validation import TrainTestSamplesMix
  from deepchecks.tabular.dataset import Dataset
  from tests.base.utils import equal_condition_result
label_desc: Use image node_id 8 for calling a global function with example usage: test_condition_ratio_not_greater_than_passed(diabetes_split_dataset_and_model) without return types