code: def test_unit_batch_dims_are_not_vectorized(self):
      if not tf.executing_eagerly():
          self.skipTest("Test relies on eager execution.")
  
      # Define `fn` to expect a vector input.
      def must_run_eagerly(x):
          if not tf.executing_eagerly():
              raise ValueError(
                  "Code is running inside tf.function. This may "
                  "indicate that auto-vectorization is being "
                  "triggered unnecessarily."
              )
          return x
  
      polymorphic_fn = vectorization_util.make_rank_polymorphic(
          must_run_eagerly, core_ndims=[0]
      )
      for batch_shape in ([], [1], [1, 1]):
          polymorphic_fn(tf.zeros(batch_shape))
  
imports: import warnings
  from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import lognormal
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.distributions import poisson
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.internal import vectorization_util
label_desc: Use image node_id 10 for calling the VectorizationTest obj's underlying member method code with example usage: obj.test_unit_batch_dims_are_not_vectorized() and returns: x