code: def three_var_model():
      with pm.Model() as model:
          pm.HalfNormal("one", size=(10, 2))
          pm.Normal("two", size=(10,))
          pm.Normal("three", size=(10, 1, 2))
      return model
  
imports: import functools
  import numpy
  import pytensor.tensor
  import pytest
  import pymc
  from pymc.variational import opvi
  from pymc.variational.approximations import Empirical, EmpiricalGroup, FullRank, FullRankGroup, MeanField, MeanFieldGroup
  from tests.helpers import not_raises
label_desc: Use image node_id 2 for calling a global function with example usage: three_var_model() and returns: model