code: def make_model(cls):
      with pm.Model() as model:
          sd_mu = np.array([1, 2, 3, 4, 5])
          sd_dist = pm.LogNormal.dist(
              mu=sd_mu, sigma=sd_mu / 10.0, size=5
          )
          chol_packed = pm.LKJCholeskyCov(
              "chol_packed",
              eta=3,
              n=5,
              sd_dist=sd_dist,
              compute_corr=False,
          )
          chol = pm.expand_packed_triangular(5, chol_packed, lower=True)
          cov = pt.dot(chol, chol.T)
          stds = pt.sqrt(pt.diag(cov))
          pm.Deterministic("log_stds", pt.log(stds))
          corr = cov / stds[None, :] / stds[:, None]
          corr_entries_unit = (corr[np.tril_indices(5, -1)] + 1) / 2
          pm.Deterministic("corr_entries_unit", corr_entries_unit)
      return model
  
imports: import arviz
  import numpy
  import numpy.testing
  import pytensor.tensor
  from scipy import stats
  import pymc
  from pymc.backends.arviz import to_inference_data
  from pymc.util import get_var_name
label_desc: Use image node_id 1 for calling the LKJCholeskyCovFixture obj's underlying member method code with example usage: obj.make_model(cls) and returns: model