class_docstr: Test class for testing homogeneity, completeness and v-measure metrics.
docstr: Test class implementation of metric.
docstr_tok: ["Test","class","implementation","of","metric","."]
code: def test_homogeneity_completeness_vmeasure(
      self,
      modular_metric,
      functional_metric,
      reference_metric,
      preds,
      target,
      ddp,
  ):
      """Test class implementation of metric."""
      self.run_class_metric_test(
          ddp=ddp,
          preds=preds,
          target=target,
          metric_class=modular_metric,
          reference_metric=partial(_sk_reference, fn=reference_metric),
      )
  
file_path: torchmetrics/tests/unittests/clustering/test_homogeneity_completeness_v_measure.py
imports: from functools import partial
  import pytest
  from sklearn.metrics import completeness_score
  from sklearn.metrics import homogeneity_score
  from sklearn.metrics import v_measure_score
  from torchmetrics.clustering.homogeneity_completeness_v_measure import CompletenessScore, HomogeneityScore, VMeasureScore
  from torchmetrics.functional.clustering.homogeneity_completeness_v_measure import completeness_score, homogeneity_score, v_measure_score
  from unittests.clustering.inputs import _float_inputs_extrinsic, _single_target_extrinsic1, _single_target_extrinsic2
  from unittests.helpers import seed_all
  from unittests.helpers.testers import MetricTester
label_desc: Use image node_id 1 for calling the TestHomogeneityCompletenessVmeasur obj's underlying member method code with example usage: obj.test_homogeneity_completeness_vmeasure(modular_metric, functional_metric, reference_metric, preds, target, ddp) without return types