code: def test_broadcasted_clip_random():
      lb_rv = pt.random.normal(0, 1)
      x_rv = pt.random.normal(0, 2, size=2)
      cens_x_rv = pt.clip(x_rv, lb_rv, 1)
  
      lb_vv = lb_rv.clone()
      cens_x_vv = cens_x_rv.clone()
  
      logp = conditional_logp({cens_x_rv: cens_x_vv, lb_rv: lb_vv})
      logp_combined = pt.sum(
          [pt.sum(factor) for factor in logp.values()]
      )
  
      assert_no_rvs(logp_combined)
  
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 7 for calling a global function with example usage: test_broadcasted_clip_random() without return types