code: def test_log_prior_matches(self):
      # Pearce has a set `noise_scale` of 0.005 ** 0.5 that we must account for.
      linear_bnn, constant_params, _, _ = self.get_bnn_and_params()
      diff = lognormal_lib.LogNormal(
          linear_bnn.noise_min, linear_bnn.log_noise_scale
      ).log_prob(0.005**0.5)
      self.assertAlmostEqual(
          linear_bnn.log_prior(constant_params) - diff,
          31.59,  # Hardcoded from reference implementation.
          places=2,
      )
  
imports: from absl.testing import parameterized
  import jax
  import jax.numpy
  import numpy
  from tensorflow_probability.python.experimental.autobnn import kernels
  from tensorflow_probability.python.experimental.autobnn import util
  from tensorflow_probability.substrates.jax.distributions import lognormal
  from absl.testing import absltest
label_desc: Use image node_id 2 for calling the ReproduceExperimentTest obj's underlying member method code with example usage: obj.test_log_prior_matches() without return types