code: def test_set_wrong_type_threshold(value):
      """
      Test that `set_threshold` indeed sets the threshold
      and cannot accept nothing but float or integers, but
      being permissive with boolean True=1.0 and False=0.0
      """
      model = IdentityPairsClassifier()
      model.fit(np.array([[[0.0], [1.0]]]), np.array([1]))
      msg = (
          "Parameter threshold must be a real number. "
          "Got {} instead.".format(type(value))
      )
  
      with pytest.raises(ValueError) as e:  # String
          model.set_threshold(value)
      assert str(e.value).startswith(msg)
  
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 8 for calling a global function with example usage: test_set_wrong_type_threshold(value) without return types