code: def test_numpyro_nuts_kwargs_are_used(mocked: mock.MagicMock):
      mocked.side_effect = MCMC
  
      step_size = 0.13
      dense_mass = True
      adapt_step_size = False
      target_accept = 0.78
  
      with pm.Model():
          pm.Normal("a")
          sample_numpyro_nuts(
              10,
              tune=10,
              chains=1,
              target_accept=target_accept,
              nuts_kwargs={
                  "step_size": step_size,
                  "dense_mass": dense_mass,
                  "adapt_step_size": adapt_step_size,
              },
          )
      mocked.assert_called_once()
      nuts_sampler = mocked.call_args.args[0]
      assert nuts_sampler._step_size == step_size
      assert nuts_sampler._dense_mass == dense_mass
      assert nuts_sampler._adapt_step_size == adapt_step_size
      assert nuts_sampler._adapt_mass_matrix
      assert nuts_sampler._target_accept_prob == target_accept
  
imports: import warnings
  from typing import Any, Callable, Dict, Optional
  from unittest import mock
  import arviz
  import jax
  import jax.numpy
  import numpy
  import pytensor
  import pytensor.tensor
  import pytest
  from numpyro.infer import MCMC
  from pytensor.compile import SharedVariable
  from pytensor.graph import graph_inputs
  import pymc
  from pymc import ImputationWarning
  from pymc.distributions.multivariate import PosDefMatrix
  from pymc.sampling.jax import _get_batched_jittered_initial_points, _get_log_likelihood, _numpyro_nuts_defaults, _replace_shared_variables, _update_numpyro_nuts_kwargs, get_jaxified_graph, get_jaxified_logp, sample_blackjax_nuts, sample_numpyro_nuts
label_desc: Use image node_id 14 for calling a global function with example usage: test_numpyro_nuts_kwargs_are_used(mocked) without return types