code: def simple_normal(bounded_prior=False):
      """Simple normal for testing MLE / MAP; probes issue #2482."""
      x0 = 10.0
      sigma = 1.0
      a, b = (
          9,
          12,
      )  # bounds for uniform RV, need non-symmetric to reproduce issue
  
      with pm.Model() as model:
          if bounded_prior:
              mu_i = pm.Uniform("mu_i", a, b)
          else:
              mu_i = pm.Flat("mu_i")
          pm.Normal("X_obs", mu=mu_i, sigma=sigma, observed=x0)
  
      return model.initial_point(), model, None
  
imports: from itertools import product
  import numpy
  import pytensor
  import pytensor.tensor
  from pytensor.compile.ops import as_op
  import pymc
  from pymc import Categorical, Metropolis, Model, Normal
  from pymc.pytensorf import floatX_array
label_desc: Use image node_id 16 for calling a global function with example usage: simple_normal(bounded_prior) and returns: model,  model,  None