code: def test_mcmc_helper_parameters() -> None:
      data = build_data()
      model = build_model(data)
  
      hmc_helper = gpflow.optimizers.SamplingHelper(
          model.log_posterior_density, model.trainable_parameters
      )
  
      for i in range(len(model.trainable_parameters)):
          assert (
              model.trainable_parameters[i].shape
              == hmc_helper.current_state[i].shape
          )
          assert (
              model.trainable_parameters[i] == hmc_helper._parameters[i]
          )
          assert (
              model.trainable_parameters[i].unconstrained_variable
              == hmc_helper.current_state[i]
          )
  
imports: from typing import Tuple
  import numpy
  import pytest
  import tensorflow
  import tensorflow_probability
  from check_shapes import ShapeChecker, check_shapes
  from tensorflow_probability.python.distributions import Gamma, Uniform
  import gpflow
  from gpflow.base import AnyNDArray, PriorOn
  from gpflow.models import GPR
  from gpflow.utilities import to_default_float
label_desc: Use image node_id 4 for calling a global function with example usage: test_mcmc_helper_parameters() without return types