code: def test_nested_sharded_maintains_correct_axis_ordering(self):
      if not JAX_MODE:
          self.skipTest("Multiple axes only supported in JAX backend.")
  
      other_axis_name = self.axis_name + "_other"
  
      dist = sharded.Sharded(
          sharded.Sharded(normal.Normal(0.0, 1.0), self.axis_name),
          other_axis_name,
      )
  
      self.assertListEqual(
          dist.experimental_shard_axis_names,
          [self.axis_name, other_axis_name],
      )
  
imports: import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import invert
  from tensorflow_probability.python.distributions import exponential
  from tensorflow_probability.python.distributions import independent
  from tensorflow_probability.python.distributions import joint_distribution_coroutine
  from tensorflow_probability.python.distributions import log_prob_ratio
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.distributions import sample
  from tensorflow_probability.python.distributions import transformed_distribution
  from tensorflow_probability.python.experimental.distribute import joint_distribution
  from tensorflow_probability.python.experimental.distribute import sharded
  from tensorflow_probability.python.experimental.distributions import increment_log_prob
  from tensorflow_probability.python.internal import distribute_test_lib
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 3 for calling the ShardTest obj's underlying member method code with example usage: obj.test_nested_sharded_maintains_correct_axis_ordering() without return types