code: def _kstest(self, a, b, samples):
      # Uses the Kolmogorov-Smirnov test for goodness of fit.
      oracle_dist = sigmoid_beta.SigmoidBeta(
          concentration0=a, concentration1=b
      )
      ks, _ = sp_stats.kstest(
          samples, lambda x: self.evaluate(oracle_dist.cdf(x))
      )
      # Return True when the test passes.
      return ks < 0.02
  
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 20 for calling the SigmoidBetaTest obj's underlying member method code with example usage: obj._kstest(a, b, samples) and returns: unknown