code: def testBetaMode(self):
      a = np.array([1.1, 2, 3])
      b = np.array([2.0, 4, 1.2])
      expected_mode = (a - 1) / (a + b - 2)
      dist = beta.Beta(a, b, validate_args=True)
      self.assertEqual(dist.mode().shape, (3,))
      self.assertAllClose(expected_mode, self.evaluate(dist.mode()))
  
imports: from absl.testing import parameterized
  import numpy
  from scipy import special
  from scipy import stats
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import beta
  from tensorflow_probability.python.distributions import kullback_leibler
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 17 for calling the BetaTest obj's underlying member method code with example usage: obj.testBetaMode() without return types