code: def test_model_with_linop_precision_works(self):
      observed_time_series = tf.ones([2])
      design_matrix = tf.eye(2)
      sampler = gibbs_sampler.build_model_for_gibbs_fitting(
          observed_time_series,
          design_matrix=design_matrix,
          weights_prior=mvnpflo.MultivariateNormalPrecisionFactorLinearOperator(
              precision_factor=tf.linalg.LinearOperatorDiag(tf.ones(2))
          ),
          level_variance_prior=inverse_gamma.InverseGamma(0.01, 0.01),
          observation_noise_variance_prior=inverse_gamma.InverseGamma(
              0.01, 0.01
          ),
      )
      self.assertIsNotNone(sampler)
  
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 6 for calling the GibbsSamplerTests obj's underlying member method code with example usage: obj.test_model_with_linop_precision_works() without return types