code: def test_sampler_respects_pseudo_observations(self):
      design_matrix = self.evaluate(
          samplers.uniform([2, 20, 5], seed=test_util.test_seed())
      )
      first_obs = 2.0
      second_obs = 10.0
      first_sampler = spike_and_slab.SpikeSlabSampler(
          design_matrix, default_pseudo_observations=first_obs
      )
      second_sampler = spike_and_slab.SpikeSlabSampler(
          design_matrix, default_pseudo_observations=second_obs
      )
  
      self.assertNotAllClose(
          first_sampler.weights_prior_precision,
          second_sampler.weights_prior_precision,
      )
      self.assertAllClose(
          first_sampler.weights_prior_precision / first_obs,
          second_sampler.weights_prior_precision / second_obs,
      )
  
imports: from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import inverse_gamma
  from tensorflow_probability.python.distributions import normal_conjugate_posteriors
  from tensorflow_probability.python.experimental.sts_gibbs import spike_and_slab
  from tensorflow_probability.python.internal import samplers
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.mcmc.internal import util
label_desc: Use image node_id 4 for calling the SpikeAndSlabTest obj's underlying member method code with example usage: obj.test_sampler_respects_pseudo_observations() without return types