code: def test_exp_transform_rv():
      base_rv = pt.random.normal(0, 1, size=3, name="base_rv")
      y_rv = pt.exp(base_rv)
      y_rv.name = "y"
  
      y_vv = y_rv.clone()
      logp_fn = pytensor.function([y_vv], logp(y_rv, y_vv))
      logcdf_fn = pytensor.function([y_vv], logcdf(y_rv, y_vv))
      icdf_fn = pytensor.function([y_vv], icdf(y_rv, y_vv))
  
      y_val = [-2.0, 0.1, 0.3]
      q_val = [0.2, 0.5, 0.9]
      np.testing.assert_allclose(
          logp_fn(y_val),
          sp.stats.lognorm(s=1).logpdf(y_val),
      )
      np.testing.assert_almost_equal(
          logcdf_fn(y_val),
          sp.stats.lognorm(s=1).logcdf(y_val),
      )
      np.testing.assert_almost_equal(
          icdf_fn(q_val),
          sp.stats.lognorm(s=1).ppf(q_val),
      )
  
imports: import numpy
  import pytensor
  import pytensor.tensor
  import pytest
  import scipy
  import scipy.special
  from pytensor.graph.basic import equal_computations
  from pymc.distributions.continuous import Cauchy, ChiSquared
  from pymc.logprob.basic import conditional_logp, icdf, logcdf, logp
  from pymc.logprob.transforms import ArccoshTransform, ArcsinhTransform, ArctanhTransform, ChainedTransform, CoshTransform, ErfcTransform, ErfcxTransform, ErfTransform, ExpTransform, LocTransform, LogTransform, ScaleTransform, SinhTransform, TanhTransform, Transform
  from pymc.logprob.utils import ParameterValueError
  from pymc.testing import Rplusbig, Vector, assert_no_rvs
  from tests.distributions.test_transform import check_jacobian_det
label_desc: Use image node_id 1 for calling a global function with example usage: test_exp_transform_rv() without return types