code: def test_potentially_measurable_operand():
      x_rv = pt.random.normal(2)
      z_rv = pt.random.normal(x_rv)
      y_rv = pt.lt(x_rv, z_rv)
  
      y_vv = y_rv.clone()
      z_vv = z_rv.clone()
  
      logprob = conditional_logp({z_rv: z_vv, y_rv: y_vv})[y_vv]
      assert_no_rvs(logprob)
  
      fn = function([z_vv, y_vv], logprob)
      z_vv_test = 0.5
      y_vv_test = True
      np.testing.assert_array_almost_equal(
          fn(z_vv_test, y_vv_test),
          st.norm(2, 1).logcdf(z_vv_test),
      )
  
      with pytest.raises(
          NotImplementedError,
          match="Logprob method not implemented",
      ):
          logp(y_rv, y_vv).eval({y_vv: y_vv_test})
  
file_path: pymc/tests/logprob/test_binary.py
imports: import numpy
  import pytensor
  import pytensor.tensor
  import pytest
  import scipy.stats
  from pytensor import function
  from pymc import logp
  from pymc.logprob import conditional_logp
  from pymc.testing import assert_no_rvs
label_desc: Use image node_id 3 for calling a global function with example usage: test_potentially_measurable_operand() without return types