code: def _batch_shape_as_list(self, distribution):
      if self.use_static_shape:
          return distribution.batch_shape.as_list()
      else:
          return list(self.evaluate(distribution.batch_shape_tensor()))
  
imports: from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.internal import samplers
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.sts import fitting
  from tensorflow_probability.python.sts.components import local_linear_trend
  from tensorflow_probability.python.sts.components import seasonal
  from tensorflow_probability.python.sts.components import sum
  from tensorflow_probability.python.sts.internal import missing_values_util
  from tensorflow_probability.python.vi import csiszar_divergence
  from tensorflow_probability.python.vi import optimization
label_desc: Use image node_id 5 for calling the _HMCTests obj's underlying member method code with example usage: obj._batch_shape_as_list(distribution) and returns: distribution, list