code: def test_remove_value_transforms():
      with pm.Model() as base_m:
          p = pm.Uniform("p", transform=logodds)
          q = pm.Uniform("q", transform=logodds)
  
      new_m = remove_value_transforms(base_m)
      new_p = new_m["p"]
      new_q = new_m["q"]
      assert new_m.rvs_to_transforms == {new_p: None, new_q: None}
  
      new_m = remove_value_transforms(base_m, [p, q])
      new_p = new_m["p"]
      new_q = new_m["q"]
      assert new_m.rvs_to_transforms == {new_p: None, new_q: None}
  
      new_m = remove_value_transforms(base_m, [p])
      new_p = new_m["p"]
      new_q = new_m["q"]
      assert new_m.rvs_to_transforms == {new_p: None, new_q: logodds}
  
      new_m = remove_value_transforms(base_m, ["q"])
      new_p = new_m["p"]
      new_q = new_m["q"]
      assert new_m.rvs_to_transforms == {new_p: logodds, new_q: None}
  
imports: import arviz
  import numpy
  import pytest
  from pytensor import config
  import pymc
  from pymc.distributions.transforms import logodds
  from pymc.model.transform.conditioning import change_value_transforms, do, observe, remove_value_transforms
  from pymc.variational.minibatch_rv import create_minibatch_rv
label_desc: Use image node_id 14 for calling a global function with example usage: test_remove_value_transforms() without return types