code: def test_potential_fn_initial_params(Kernel):
      target = torch.distributions.Normal(
          loc=torch.tensor([10.0, 0.0]), scale=torch.tensor([1.0, 1.0])
      )
  
      def potential_fn(z):
          z = z["points"]
          return -target.log_prob(z).sum(1)[None]
  
      initial_params = {"points": torch.tensor([[0.0, 0.0]])}
      kernel = Kernel(potential_fn=potential_fn)
      mcmc = MCMC(
          kernel=kernel,
          warmup_steps=20,
          initial_params=initial_params,
          num_samples=10,
      )
  
      mcmc.run()
      mcmc.get_samples()["points"]
  
imports: import io
  import logging
  import pytest
  import torch
  import pyro
  import pyro.distributions
  import pyro.poutine
  from pyro.infer import config_enumerate
  from pyro.infer.mcmc import HMC, NUTS
  from pyro.infer.mcmc.api import MCMC
  from pyro.infer.mcmc.util import TraceEinsumEvaluator, TraceTreeEvaluator, initialize_model
  from pyro.infer.reparam import LatentStableReparam
  from pyro.poutine.subsample_messenger import _Subsample
  from tests.common import assert_close, assert_equal, xfail_param
label_desc: Use image node_id 18 for calling a global function with example usage: test_potential_fn_initial_params(Kernel) and returns: unknown