code: def test_lsml_supervised(self):
      seed = np.random.RandomState(1234)
      lsml = LSML_Supervised(n_constraints=200, random_state=seed)
      lsml.fit(self.X, self.y)
      L = lsml.components_
      assert_array_almost_equal(
          L.T.dot(L), lsml.get_mahalanobis_matrix()
      )
  
imports: import unittest
  import numpy
  import pytest
  from scipy.stats import ortho_group
  from sklearn.datasets import load_iris
  from numpy.testing import assert_array_almost_equal, assert_allclose
  from metric_learn.sklearn_shims import ignore_warnings
  from metric_learn import LMNN, NCA, LFDA, Covariance, MLKR, LSML_Supervised, ITML_Supervised, SDML_Supervised, RCA_Supervised
  from metric_learn._util import components_from_metric
  from metric_learn.exceptions import NonPSDError
label_desc: Use image node_id 3 for calling the TestTransformerMetricConversion obj's underlying member method code with example usage: obj.test_lsml_supervised() without return types