code: def test_without_conflicting_labels(dataset_name, request):
      # Arrange
      dataset = request.getfixturevalue(dataset_name)
      check = (
          ConflictingLabels().add_condition_ratio_of_conflicting_labels_less_or_equal()
      )
  
      # Act
      result = check.run(dataset=dataset)
      conditions_decisions = check.conditions_decision(result)
  
      # Assert
      assert_that(
          result.value,
          has_entries(
              {
                  "percent_of_conflicting_samples": equal_to(0),
                  "conflicting_samples": instance_of(pd.DataFrame),
              }
          ),
      )
  
      assert_that(
          conditions_decisions[0],
          equal_condition_result(
              is_pass=True,
              details=f"Ratio of samples with conflicting labels: 0%",
              name="Ambiguous sample ratio is less or equal to 0%",
          ),
      )  # type: ignore
  
      assert_that(len(result.value["conflicting_samples"]), equal_to(0))
      assert_result_dataframe(result.value["conflicting_samples"])
  
imports: import typing
  import pandas
  import pytest
  from hamcrest import *
  from deepchecks.nlp.checks import ConflictingLabels
  from deepchecks.nlp.text_data import TextData
  from deepchecks.utils.strings import format_percent
  from tests.base.utils import equal_condition_result
label_desc: Use image node_id 5 for calling a global function with example usage: test_without_conflicting_labels(dataset_name, request) without return types