code: def testAssertValidSample(self):
      loc1 = tf1.placeholder_with_default(tf.zeros([2]), shape=None)
      loc2 = tf1.placeholder_with_default(tf.zeros([2]), shape=None)
      dist = blockwise.Blockwise(
          [
              normal.Normal(loc1, tf.ones_like(loc1)),
              normal.Normal(loc2, tf.ones_like(loc2)),
          ],
          validate_args=True,
      )
  
      with self.assertRaisesRegexp(
          ValueError, "must have at least one dimension"
      ):
          self.evaluate(dist.prob(3.0))
  
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 7 for calling the BlockwiseTest obj's underlying member method code with example usage: obj.testAssertValidSample() without return types