code: def testVaryingBatchShapeErrorStatic(self):
      with self.assertRaisesRegexp(
          ValueError, "Distributions must have the same `batch_shape`"
      ):
          blockwise.Blockwise(
              [
                  normal.Normal(tf.zeros(2), tf.ones(2)),
                  normal.Normal(0.0, 1.0),
              ],
              validate_args=True,
          )
  
imports: from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import blockwise
  from tensorflow_probability.python.distributions import exponential
  from tensorflow_probability.python.distributions import gamma
  from tensorflow_probability.python.distributions import independent
  from tensorflow_probability.python.distributions import joint_distribution_coroutine
  from tensorflow_probability.python.distributions import joint_distribution_named
  from tensorflow_probability.python.distributions import joint_distribution_sequential
  from tensorflow_probability.python.distributions import kullback_leibler
  from tensorflow_probability.python.distributions import mvn_linear_operator
  from tensorflow_probability.python.distributions import mvn_tril
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 4 for calling the BlockwiseTest obj's underlying member method code with example usage: obj.testVaryingBatchShapeErrorStatic() without return types