code: def testLogPDF(self):
      a = [1.0, 2]
      b = [1.0, 2]
      x = [0.0, 0.0]
      dist = sigmoid_beta.SigmoidBeta(a, b, validate_args=True)
      logpdf = dist.log_prob(x)
  
      oracle = transformed_distribution.TransformedDistribution(
          distribution=beta.Beta(a, b),
          bijector=invert.Invert(sigmoid.Sigmoid()),
      )
      expected_logpdf = oracle.log_prob(x)
  
      self.assertAllClose(expected_logpdf, logpdf)
      self.assertEqual((2,), logpdf.shape)
  
      x = [1.0, 1.0]
      logpdf = dist.log_prob(x)
      expected_logpdf = oracle.log_prob(x)
  
      self.assertAllClose(expected_logpdf, logpdf)
      self.assertEqual((2,), logpdf.shape)
  
      a = [1.0, 2.0]
      b = [2.0, 1.0]
      x = [1.0, 1.0]
      dist = sigmoid_beta.SigmoidBeta(a, b, validate_args=True)
      oracle = transformed_distribution.TransformedDistribution(
          distribution=beta.Beta(a, b),
          bijector=invert.Invert(sigmoid.Sigmoid()),
      )
  
      logpdf = dist.log_prob(x)
      expected_logpdf = oracle.log_prob(x)
      self.assertAllClose(expected_logpdf, logpdf)
      self.assertEqual((2,), logpdf.shape)
  
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 8 for calling the SigmoidBetaTest obj's underlying member method code with example usage: obj.testLogPDF() without return types