code: def test_exponential_ordered(self, lam, size):
      initval = np.sort(np.abs(np.random.randn(*size)))
      model = self.build_model(
          pm.Exponential,
          {"lam": lam},
          size=size,
          initval=initval,
          transform=tr.Chain([tr.log, tr.ordered]),
      )
      self.check_vectortransform_elementwise_logp(model)
  
imports: import numpy
  import pytensor
  import pytensor.tensor
  import pytest
  from numpy.testing import assert_allclose, assert_array_equal
  from pytensor.tensor.variable import TensorConstant
  import pymc
  import pymc.distributions.transforms
  from pymc.logprob.basic import transformed_conditional_logp
  from pymc.logprob.transforms import Transform
  from pymc.pytensorf import floatX, jacobian
  from pymc.testing import Circ, MultiSimplex, R, Rminusbig, Rplusbig, Simplex, SortedVector, Unit, UnitSortedVector, Vector
label_desc: Use image node_id 13 for calling the TestElementWiseLogp obj's underlying member method code with example usage: obj.test_exponential_ordered(lam, size) without return types