code: def test_event_shape(
      self,
      is_static,
      get_distributions,
      static_event_shape,
      dynamic_event_shape,
  ):
      _, concat_dist = get_distributions(is_static=is_static)
      if tf.executing_eagerly() or is_static:
          self.assertAllEqual(
              concat_dist.event_shape, static_event_shape
          )
      else:
          self.assertAllEqual(
              concat_dist.event_shape.as_list(), dynamic_event_shape
          )
  
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 4 for calling the BatchConcatTest obj's underlying member method code with example usage: obj.test_event_shape(is_static, get_distributions, static_event_shape, dynamic_event_shape) without return types