code: def testSample(self):
      a = tf.constant(1.0)
      b = tf.constant(2.0)
      n = 500000
      d = sigmoid_beta.SigmoidBeta(
          concentration0=a, concentration1=b, validate_args=True
      )
      samples = d.sample(n, seed=test_util.test_seed())
      sample_values = self.evaluate(samples)
      self.assertEqual(samples.shape, (n,))
      self.assertEqual(sample_values.shape, (n,))
      self.assertTrue(self._kstest(a, b, sample_values))
  
      check_cdf_agrees = st.assert_true_cdf_equal_by_dkwm(
          samples, d.cdf, false_fail_rate=1e-6
      )
      self.evaluate(check_cdf_agrees)
      check_enough_power = assert_util.assert_less(
          st.min_discrepancy_of_true_cdfs_detectable_by_dkwm(
              n, false_fail_rate=1e-6, false_pass_rate=1e-6
          ),
          0.01,
      )
      self.evaluate(check_enough_power)
  
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 21 for calling the SigmoidBetaTest obj's underlying member method code with example usage: obj.testSample() without return types