code: def test_proposal_dist_shape(self):
      with pm.Model() as m:
          x = pm.Normal("x", 0, 1)
          y = pm.Normal("y", x, 1, observed=0)
          with warnings.catch_warnings():
              warnings.filterwarnings(
                  "ignore", ".*number of samples.*", UserWarning
              )
              trace = pm.sample_smc(
                  draws=10,
                  chains=1,
                  kernel=pm.smc.MH,
                  return_inferencedata=False,
              )
  
imports: import logging
  import platform
  import warnings
  import numpy
  import pytensor.tensor
  import pytest
  import scipy.stats
  from arviz.data.inference_data import InferenceData
  import pymc
  from pymc.backends.base import MultiTrace
  from pymc.pytensorf import floatX
  from pymc.smc.kernels import IMH, systematic_resampling
  from tests.helpers import assert_random_state_equal
label_desc: Use image node_id 2 for calling the TestMHKernel obj's underlying member method code with example usage: obj.test_proposal_dist_shape() without return types