class_docstr: Test class for `DaviesBouldinScore` metric.
class_docstr_tok: ["Test","class","for","`","DaviesBouldinScore","`","metric","."]
docstr: Test class implementation of metric.
docstr_tok: ["Test","class","implementation","of","metric","."]
code: def test_davies_bouldin_score(self, data, labels, ddp):
      """Test class implementation of metric."""
      self.run_class_metric_test(
          ddp=ddp,
          preds=data,
          target=labels,
          metric_class=DaviesBouldinScore,
          reference_metric=sklearn_davies_bouldin_score,
      )
  
file_path: torchmetrics/tests/unittests/clustering/test_davies_bouldin_score.py
imports: import pytest
  from sklearn.metrics import davies_bouldin_score
  from torchmetrics.clustering.davies_bouldin_score import DaviesBouldinScore
  from torchmetrics.functional.clustering.davies_bouldin_score import davies_bouldin_score
  from unittests.clustering.inputs import _single_target_intrinsic1, _single_target_intrinsic2
  from unittests.helpers import seed_all
  from unittests.helpers.testers import MetricTester
label_desc: Use image node_id 1 for calling the TestDaviesBouldinScore obj's underlying member method code with example usage: obj.test_davies_bouldin_score(data, labels, ddp) without return types