code: def _testPmf(self, **kwargs):
      dist = probit_bernoulli.ProbitBernoulli(**kwargs)
      # pylint: disable=bad-continuation
      xs = [
          0,
          [1],
          [1, 0],
          [[1, 0]],
          [[1, 0], [1, 1]],
      ]
      expected_pmfs = [
          [[0.8, 0.6], [0.7, 0.4]],
          [[0.2, 0.4], [0.3, 0.6]],
          [[0.2, 0.6], [0.3, 0.4]],
          [[0.2, 0.6], [0.3, 0.4]],
          [[0.2, 0.6], [0.3, 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 kullback_leibler
  from tensorflow_probability.python.distributions import probit_bernoulli
  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 ProbitBernoulliTest obj's underlying member method code with example usage: obj._testPmf() without return types