code: def testComplexShapes(self):
      p = np.random.beta(1, 1, size=(3, 2)).astype(np.float32)
      n = [[3.0, 2], [4, 5], [6, 7]]
      binom = binomial_lib.Binomial(
          total_count=n, probs=p, validate_args=True
      )
      self.assertAllEqual([], self.evaluate(binom.event_shape_tensor()))
      self.assertAllEqual(
          [3, 2], self.evaluate(binom.batch_shape_tensor())
      )
      self.assertEqual(tf.TensorShape([]), binom.event_shape)
      self.assertEqual(tf.TensorShape([3, 2]), binom.batch_shape)
  
imports: import numpy
  from scipy import stats
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import binomial
  from tensorflow_probability.python.internal import implementation_selection
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 5 for calling the BinomialTest obj's underlying member method code with example usage: obj.testComplexShapes() without return types