code: def test_near_duplicate_sets(self, embeddings):
      data = {"metadata": ["" for _ in range(len(embeddings))]}
      lab = Datalab(data)
      issue_manager = NearDuplicateIssueManager(
          datalab=lab,
          metric="euclidean",
          k=2,
      )
      embeddings = np.array(embeddings)
      issue_manager.find_issues(features=embeddings)
      near_duplicate_sets = issue_manager.info["near_duplicate_sets"]
      issues = issue_manager.issues["is_near_duplicate_issue"]
  
      # Test: Near duplicates are symmetric
      all_symmetric = all(
          i in near_duplicate_sets[j]
          for i, near_duplicates in enumerate(near_duplicate_sets)
          for j in near_duplicates
      )
      assert all_symmetric, "Some near duplicate sets are not symmetric"
  
      # Test: Near duplicate sets for issues
      assert all(
          len(near_duplicate_set) == 0
          for i, near_duplicate_set in enumerate(near_duplicate_sets)
          if not issues[i]
      ), "Non-issue examples should not have near duplicate sets"
      assert all(
          len(near_duplicate_set) > 0
          for i, near_duplicate_set in enumerate(near_duplicate_sets)
          if issues[i]
      ), "Issue examples should have near duplicate sets"
  
imports: import numpy
  import pytest
  from hypothesis import HealthCheck, assume, given, settings, strategies
  from hypothesis.strategies import composite
  from hypothesis.extra.numpy import arrays
  from cleanlab import Datalab
  from cleanlab.datalab.internal.issue_manager.duplicate import NearDuplicateIssueManager
  from .conftest import knn_graph_strategy
label_desc: Use image node_id 7 for calling the TestNearDuplicateIssueManager obj's underlying member method code with example usage: obj.test_near_duplicate_sets(embeddings) without return types