code: def testShapes(self):
      for batch_shape in ([], [1], [2, 3, 4]):
          dist = make_bernoulli(batch_shape)
          self.assertAllEqual(
              batch_shape, tensorshape_util.as_list(dist.batch_shape)
          )
          self.assertAllEqual(
              batch_shape, self.evaluate(dist.batch_shape_tensor())
          )
          self.assertAllEqual(
              [], tensorshape_util.as_list(dist.event_shape)
          )
          self.assertAllEqual(
              [], self.evaluate(dist.event_shape_tensor())
          )
  
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 4 for calling the ProbitBernoulliTest obj's underlying member method code with example usage: obj.testShapes() without return types