code: def test_clip_transform():
      x_rv = pt.random.normal(0.5, 1)
      cens_x_rv = pt.clip(x_rv, 0, x_rv)
  
      cens_x_vv = cens_x_rv.clone()
  
      transform = TransformValuesRewrite({cens_x_vv: LogTransform()})
      logp = conditional_logp(
          {cens_x_rv: cens_x_vv}, extra_rewrites=transform
      )
      logp_combined = pt.sum(
          [pt.sum(factor) for factor in logp.values()]
      )
  
      cens_x_vv_testval = -1
      obs_logp = logp_combined.eval({cens_x_vv: cens_x_vv_testval})
      exp_logp = (
          sp.stats.norm(0.5, 1).logpdf(np.exp(cens_x_vv_testval))
          + cens_x_vv_testval
      )
  
      assert np.isclose(obs_logp, exp_logp)
  
imports: import numpy
  import pytensor
  import pytensor.tensor
  import pytest
  import scipy
  import scipy.stats
  from pymc import logp
  from pymc.logprob import conditional_logp
  from pymc.logprob.transform_value import TransformValuesRewrite
  from pymc.logprob.transforms import LogTransform
  from pymc.testing import assert_no_rvs
label_desc: Use image node_id 11 for calling a global function with example usage: test_clip_transform() without return types