code: def test_set_threshold():
      # test that set_threshold indeed sets the threshold
      identity_pairs_classifier = IdentityPairsClassifier()
      pairs = np.array(
          [
              [[0.0], [1.0]],
              [[1.0], [3.0]],
              [[2.0], [5.0]],
              [[3.0], [7.0]],
          ]
      )
      y = np.array([1, 1, -1, -1])
      identity_pairs_classifier.fit(pairs, y)
      identity_pairs_classifier.set_threshold(0.5)
      assert identity_pairs_classifier.threshold_ == 0.5
  
imports: from functools import partial
  import pytest
  from numpy.testing import assert_array_equal
  from scipy.spatial.distance import euclidean
  from metric_learn.base_metric import _PairsClassifierMixin, MahalanobisMixin
  from sklearn.exceptions import NotFittedError
  from sklearn.metrics import f1_score, accuracy_score, fbeta_score, precision_score
  from sklearn.model_selection import train_test_split
  from test.test_utils import pairs_learners, ids_pairs_learners
  from metric_learn.sklearn_shims import set_random_state
  from sklearn import clone
  import numpy
  from itertools import product
label_desc: Use image node_id 7 for calling a global function with example usage: test_set_threshold() without return types