code: def testPdfCorrectBroadcastDynamicShape(self):
      prob = tf1.placeholder_with_default([0.2, 0.3, 0.4], shape=None)
      dist = continuous_bernoulli.ContinuousBernoulli(
          probs=prob, validate_args=True
      )
      event1 = [0.9, 0.1, 1.0]
      event2 = [[0.9, 0.1, 1.0]]
      self.assertAllClose(
          [pdf(0.9, 0.2), pdf(0.1, 0.3), pdf(1.0, 0.4)],
          self.evaluate(dist.prob(event1)),
      )
      self.assertAllClose(
          [[pdf(0.9, 0.2), pdf(0.1, 0.3), pdf(1.0, 0.4)]],
          self.evaluate(dist.prob(event2)),
      )
  
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 8 for calling the ContinuousBernoulliTest obj's underlying member method code with example usage: obj.testPdfCorrectBroadcastDynamicShape() without return types