code: def test_default_bijector(self, data):
      batch_shape = data.draw(tfp_hps.shapes())
      bcast_arg, dist_batch_shp = data.draw(
          tfp_hps.broadcasting_shapes(batch_shape, 2)
      )
      underlying = data.draw(
          tfd_hps.distributions(
              batch_shape=dist_batch_shp,
              eligibility_filter=(lambda name: name != "BatchReshape"),
          )
      )  # b/183977243
      if not self.is_static_shape:
          bcast_arg = tf.Variable(bcast_arg)
          self.evaluate(bcast_arg.initializer)
      dist = batch_broadcast.BatchBroadcast(underlying, bcast_arg)
      bijector = dist.experimental_default_event_space_bijector()
      hp.assume(bijector is not None)
      shp = bijector.inverse_event_shape_tensor(
          tf.concat(
              [dist.batch_shape_tensor(), dist.event_shape_tensor()],
              axis=0,
          )
      )
      obs = bijector.forward(
          tf.random.normal(shp, seed=test_util.test_seed())
      )
      with tf.control_dependencies(
          dist._sample_control_dependencies(obs)
      ):
          self.evaluate(tf.identity(obs))
  
imports: import hypothesis
  import hypothesis.strategies
  import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import batch_broadcast
  from tensorflow_probability.python.distributions import bernoulli
  from tensorflow_probability.python.distributions import beta
  from tensorflow_probability.python.distributions import categorical
  from tensorflow_probability.python.distributions import dirichlet
  from tensorflow_probability.python.distributions import hypothesis_testlib
  from tensorflow_probability.python.distributions import independent
  from tensorflow_probability.python.distributions import mixture_same_family
  from tensorflow_probability.python.distributions import mvn_diag
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.distributions import sample
  from tensorflow_probability.python.distributions import uniform
  from tensorflow_probability.python.distributions import von_mises_fisher
  from tensorflow_probability.python.distributions import wishart
  from tensorflow_probability.python.internal import hypothesis_testlib
  from tensorflow_probability.python.internal import tensorshape_util
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.random import random_ops
label_desc: Use image node_id 13 for calling the _BatchBroadcastTest obj's underlying member method code with example usage: obj.test_default_bijector(data) without return types