code: def test_seasonal_component_assumptions_enforced(
      self, seasonal_component_factory, assertion_regex
  ):
      with self.assertRaisesRegex(NotImplementedError, assertion_regex):
          self._build_test_model(
              # Use a factory since distributions in JAX can not be initialized
              # before main runs.
              seasonal_components=[seasonal_component_factory()]
          )
  
imports: from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import identity
  from tensorflow_probability.python.bijectors import invert
  from tensorflow_probability.python.bijectors import square
  from tensorflow_probability.python.distributions import inverse_gamma
  from tensorflow_probability.python.distributions import lognormal
  from tensorflow_probability.python.distributions import mvn_diag
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.distributions import student_t
  from tensorflow_probability.python.distributions import transformed_distribution
  from tensorflow_probability.python.distributions.linear_gaussian_ssm import linear_gaussian_update
  from tensorflow_probability.python.experimental.distributions import mvn_precision_factor_linop
  from tensorflow_probability.python.experimental.sts_gibbs import gibbs_sampler
  from tensorflow_probability.python.internal import samplers
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.stats import sample_stats
  from tensorflow_probability.python.sts.components import local_level
  from tensorflow_probability.python.sts.components import local_linear_trend
  from tensorflow_probability.python.sts.components import regression
  from tensorflow_probability.python.sts.components import seasonal
  from tensorflow_probability.python.sts.components import semilocal_linear_trend
  from tensorflow_probability.python.sts.components import sum
  from tensorflow_probability.python.sts.forecast import forecast
  from tensorflow_probability.python.sts.internal import missing_values_util
  from tensorflow_probability.python.sts.internal import util
label_desc: Use image node_id 15 for calling the GibbsSamplerTests obj's underlying member method code with example usage: obj.test_seasonal_component_assumptions_enforced(seasonal_component_factory, assertion_regex) without return types