code: def test_generate_knntriplets_under_edge(
      k_genuine, k_impostor, T_test
  ):
      """Checks under the edge cases of knn triplet construction with enough
      neighbors"""
  
      X = np.array(
          [[0, 0], [2, 2], [4, 4], [8, 8], [16, 16], [32, 32], [33, 33]]
      )
      y = np.array([1, 1, 1, 2, 2, 2, -1])
  
      T = Constraints(y).generate_knntriplets(X, k_genuine, k_impostor)
  
      assert np.array_equal(sorted(T.tolist()), T_test)
  
file_path: metric-learn/test/test_constraints.py
imports: import pytest
  import numpy
  from sklearn.utils import shuffle
  from metric_learn.constraints import Constraints
  from sklearn.datasets import make_blobs
label_desc: Use image node_id 5 for calling a global function with example usage: test_generate_knntriplets_under_edge(k_genuine, k_impostor, T_test) without return types