code: def test_observe_dims():
      with pm.Model(coords={"test_dim": range(5)}) as m_old:
          x = pm.Normal("x", dims="test_dim")
  
      m_new = observe(m_old, {x: np.arange(5, dtype=config.floatX)})
      assert m_new.named_vars_to_dims["x"] == ["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 4 for calling a global function with example usage: test_observe_dims() without return types