code: def test_incompatible_event_shape(self, is_static):
      norm = normal.Normal(
          loc=self.maybe_static(tf.zeros([2, 3]), is_static),
          scale=self.maybe_static(tf.ones([2, 3]), is_static),
      )
      mvn = mvn_diag.MultivariateNormalDiag(
          loc=self.maybe_static(tf.zeros([2, 3, 2]), is_static),
          scale_diag=self.maybe_static(tf.ones([2, 3, 2]), is_static),
      )
  
      if tf.executing_eagerly() or is_static:
          with self.assertRaises(Exception):
              _ = batch_concat.BatchConcat([norm, mvn])
      else:
          concat_dist = batch_concat.BatchConcat([norm, mvn], axis=0)
          with self.assertRaises(Exception):
              self.evaluate(concat_dist.mean())
  
imports: from absl.testing import parameterized
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import batch_concat
  from tensorflow_probability.python.distributions import dirichlet
  from tensorflow_probability.python.distributions import exponential
  from tensorflow_probability.python.distributions import independent
  from tensorflow_probability.python.distributions import logistic
  from tensorflow_probability.python.distributions import mvn_diag
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.distributions import onehot_categorical
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 14 for calling the BatchConcatTest obj's underlying member method code with example usage: obj.test_incompatible_event_shape(is_static) without return types