code: def test_can_return_distribution_from_vectorized_map(self):
      def fn(x):
          dist = AutoNormal(loc=x, scale=[3.0, 5.0])
          return dist._broadcast_parameters_with_batch_shape(
              tf.ones_like(dist.batch_shape_tensor())
          )
  
      batch_dist = tf.vectorized_map(
          fn, tf.convert_to_tensor([1.0, 2.0, 3.0])
      )
      self.assertAllEqual(batch_dist.batch_shape, [3, 2])
  
imports: import functools
  import os
  from absl import flags
  from absl.testing import parameterized
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import bijector
  from tensorflow_probability.python.bijectors import reshape
  from tensorflow_probability.python.bijectors import scale
  from tensorflow_probability.python.bijectors import shift
  from tensorflow_probability.python.bijectors import transform_diagonal
  from tensorflow_probability.python.distributions import independent
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.distributions import transformed_distribution
  from tensorflow_probability.python.experimental.distributions import mvn_precision_factor_linop
  from tensorflow_probability.python.internal import auto_composite_tensor
  from tensorflow_probability.python.internal import tensor_util
  from tensorflow_probability.python.internal import test_util
  from absl.testing import absltest
label_desc: Use image node_id 22 for calling the AutoCompositeTensorTest obj's underlying member method code with example usage: obj.test_can_return_distribution_from_vectorized_map() and returns: dist