code: def test_do_dims():
      coords = {"test_dim": range(10)}
      with pm.Model(coords=coords) as m:
          x = pm.Normal("x", dims="test_dim")
          y = pm.Deterministic("y", x + 5, dims="test_dim")
  
      do_m = do(
          m,
          {"x": np.zeros(10, dtype=config.floatX)},
      )
      assert do_m.named_vars_to_dims["x"] == ["test_dim"]
  
      do_m = do(
          m,
          {"y": np.zeros(10, dtype=config.floatX)},
      )
      assert do_m.named_vars_to_dims["y"] == ["test_dim"]
  
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 9 for calling a global function with example usage: test_do_dims() without return types