code: def test_get_trained_cav(self):
      # 1D inputs.
      x = [[1], [1], [1], [2], [1], [1], [-1], [-1], [-2], [-1], [-1]]
      y = [1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0]
      cav, accuracy = self.tcav.get_trained_cav(
          x, y, 0.33, random_state=0
      )
      np.testing.assert_almost_equal(np.array([[19.08396947]]), cav)
      self.assertAlmostEqual(1.0, accuracy)
  
      # 2D inputs.
      x = [[-8, 1], [5, 3], [3, 6], [-2, 5], [-8, 10], [10, -5]]
      y = [1, 0, 0, 1, 1, 0]
      cav, accuracy = self.tcav.get_trained_cav(
          x, y, 0.33, random_state=0
      )
      np.testing.assert_almost_equal(
          np.array([[-77.89678676, 9.73709834]]), cav
      )
      self.assertAlmostEqual(1.0, accuracy)
  
imports: from absl.testing import absltest
  from absl.testing import parameterized
  from lit_nlp.api import dataset
  from lit_nlp.api import model
  from lit_nlp.api import types
  from lit_nlp.components import tcav
  import numpy
label_desc: Use image node_id 5 for calling the TCAVTest obj's underlying member method code with example usage: obj.test_get_trained_cav() without return types