code: def test_do_deterministic():
      rng = np.random.default_rng(seed=435)
      with pm.Model() as m:
          x = pm.Normal("x", 0, 1e-3)
          y = pm.Deterministic("y", x + 105)
          z = pm.Normal("z", y, 1e-3)
  
      do_m = do(m, {"z": x - 105})
      assert pm.draw(do_m["z"], random_seed=rng) < 100
  
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 8 for calling a global function with example usage: test_do_deterministic() without return types