code: def testQuantile(self):
      batch_shape = [6, 1]
      a = 2.0 * np.ones(batch_shape, dtype=np.float32)
      b = 3.0 * np.ones(batch_shape, dtype=np.float32)
      p = np.logspace(-4.0, -0.01, 20).astype(np.float32)
      dist = sigmoid_beta.SigmoidBeta(a, b, validate_args=True)
      quantile = dist.quantile(p)
      self.assertEqual(quantile.shape, (6, 20))
  
      expected_quantile = (
          transformed_distribution.TransformedDistribution(
              distribution=beta.Beta(a, b),
              bijector=invert.Invert(sigmoid.Sigmoid()),
          ).quantile(p)
      )
      self.assertAllClose(quantile, expected_quantile)
  
imports: import numpy
  from scipy import stats
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import invert
  from tensorflow_probability.python.bijectors import sigmoid
  from tensorflow_probability.python.distributions import beta
  from tensorflow_probability.python.distributions import sigmoid_beta
  from tensorflow_probability.python.distributions import transformed_distribution
  from tensorflow_probability.python.distributions.internal import statistical_testing
  from tensorflow_probability.python.internal import assert_util
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 13 for calling the SigmoidBetaTest obj's underlying member method code with example usage: obj.testQuantile() without return types