code: def test_include_transformed(self):
      with pm.Model():
          pm.Uniform("p", 0, 1)
  
          # First check that the default is to exclude the transformed variables
          sample_kwargs = dict(
              tune=5,
              draws=7,
              chains=2,
              cores=1,
              compute_convergence_checks=False,
          )
          inference_data = pm.sample(
              **sample_kwargs, step=pm.Metropolis()
          )
          assert "p_interval__" not in inference_data.posterior
  
          # Now check that they are included when requested
          inference_data = pm.sample(
              **sample_kwargs,
              step=pm.Metropolis(),
              idata_kwargs={"include_transformed": True},
          )
          assert "p_interval__" in inference_data.posterior
  
imports: import warnings
  from typing import Dict, Tuple
  import numpy
  import pytensor.tensor
  import pytest
  from arviz import InferenceData
  from arviz.tests.helpers import check_multiple_attrs
  from numpy import ma
  from pytensor.tensor.subtensor import AdvancedIncSubtensor, AdvancedIncSubtensor1
  import pymc
  from pymc.backends.arviz import InferenceDataConverter, predictions_to_inference_data, to_inference_data
  from pymc.exceptions import ImputationWarning
label_desc: Use image node_id 26 for calling the TestDataPyMC obj's underlying member method code with example usage: obj.test_include_transformed() without return types