code: def _testPdf(self, **kwargs):
      dist = continuous_bernoulli.ContinuousBernoulli(
          validate_args=True, **kwargs
      )
      # pylint: disable=bad-continuation
      xs = [
          0.1,
          [0.9],
          [0.9, 0.1],
          [[0.9, 0.1]],
          [[0.9, 0.1], [0.9, 0.9]],
      ]
      expected_pmfs = [
          [
              [pdf(0.1, 0.2), pdf(0.1, 0.4)],
              [pdf(0.1, 0.3), pdf(0.1, 0.6)],
          ],
          [
              [pdf(0.9, 0.2), pdf(0.9, 0.4)],
              [pdf(0.9, 0.3), pdf(0.9, 0.6)],
          ],
          [
              [pdf(0.9, 0.2), pdf(0.1, 0.4)],
              [pdf(0.9, 0.3), pdf(0.1, 0.6)],
          ],
          [
              [pdf(0.9, 0.2), pdf(0.1, 0.4)],
              [pdf(0.9, 0.3), pdf(0.1, 0.6)],
          ],
          [
              [pdf(0.9, 0.2), pdf(0.1, 0.4)],
              [pdf(0.9, 0.3), pdf(0.9, 0.6)],
          ],
      ]
      # pylint: enable=bad-continuation
  
      for x, expected_pmf in zip(xs, expected_pmfs):
          self.assertAllClose(self.evaluate(dist.prob(x)), expected_pmf)
          self.assertAllClose(
              self.evaluate(dist.log_prob(x)), np.log(expected_pmf)
          )
  
imports: import numpy
  from scipy import special
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import continuous_bernoulli
  from tensorflow_probability.python.distributions import kullback_leibler
  from tensorflow_probability.python.internal import tensorshape_util
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 7 for calling the ContinuousBernoulliTest obj's underlying member method code with example usage: obj._testPdf() without return types