code: def testComplexShapes(self):
      n = np.random.randint(1, 10, size=(5, 4)).astype(np.float64)
      c1 = np.random.rand(2, 1, 1)
      c0 = np.random.rand(3, 1, 5, 1)
      dist = beta_binomial.BetaBinomial(n, c1, c0, validate_args=True)
      self.assertAllEqual([], self.evaluate(dist.event_shape_tensor()))
      self.assertAllEqual(
          [3, 2, 5, 4], self.evaluate(dist.batch_shape_tensor())
      )
      self.assertEqual(tf.TensorShape([]), dist.event_shape)
      self.assertEqual(tf.TensorShape([3, 2, 5, 4]), dist.batch_shape)
  
imports: import numpy
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import bernoulli
  from tensorflow_probability.python.distributions import beta_binomial
  from tensorflow_probability.python.distributions import dirichlet_multinomial
  from tensorflow_probability.python.distributions.internal import statistical_testing
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 2 for calling the BetaBinomialTest obj's underlying member method code with example usage: obj.testComplexShapes() without return types