variational_posteriors.log_prob error for run_smc_ in SMC Demo file

Hello, I ran SMC Demo and when I ran "run_smc_()", the error below occured

"""
94
95 def _tempered_target_log_prob(*args):
--> 96 priorlogprob = tf.identity(prior_log_prob_fn(*args),
97 name='prior_log_prob')
98 loglike = tf.identity(likelihood_log_prob_fn(*args),

TypeError: in user code:

File "<ipython-input-61-86b08bf263c9>", line 3, in run_smc_  *
    (
File "/usr/local/lib/python3.7/dist-packages/tensorflow_probability/python/experimental/mcmc/sample_sequential_monte_carlo.py", line 387, in sample_sequential_monte_carlo  **
    pkr = kernel.bootstrap_results(current_state)
File "/usr/local/lib/python3.7/dist-packages/tensorflow_probability/python/mcmc/transformed_kernel.py", line 493, in bootstrap_results
    transformed_init_state))
File "/usr/local/lib/python3.7/dist-packages/tensorflow_probability/python/mcmc/hmc.py", line 561, in bootstrap_results
    kernel_results = self._impl.bootstrap_results(init_state)
File "/usr/local/lib/python3.7/dist-packages/tensorflow_probability/python/mcmc/metropolis_hastings.py", line 273, in bootstrap_results
    pkr = self.inner_kernel.bootstrap_results(init_state)
File "/usr/local/lib/python3.7/dist-packages/tensorflow_probability/python/mcmc/hmc.py", line 775, in bootstrap_results
    ] = mcmc_util.maybe_call_fn_and_grads(self.target_log_prob_fn, init_state)
File "/usr/local/lib/python3.7/dist-packages/tensorflow_probability/python/mcmc/internal/util.py", line 297, in maybe_call_fn_and_grads
    result, grads = _value_and_gradients(fn, fn_arg_list, result, grads)
File "/usr/local/lib/python3.7/dist-packages/tensorflow_probability/python/mcmc/internal/util.py", line 265, in _value_and_gradients
    return tfp_math_value_and_gradients(fn, fn_arg_list)
File "/usr/local/lib/python3.7/dist-packages/tensorflow_probability/python/math/gradient.py", line 117, in value_and_gradient
    **kwargs)
File "/usr/local/lib/python3.7/dist-packages/tensorflow_probability/python/math/gradient.py", line 380, in _value_and_grad_impl
    output_gradients)
File "/usr/local/lib/python3.7/dist-packages/tensorflow_probability/python/math/gradient.py", line 330, in _gradient_old
    y, aux = f()
File "/usr/local/lib/python3.7/dist-packages/tensorflow_probability/python/math/gradient.py", line 378, in <lambda>
    y, dydx, aux = grad_fn(lambda: f(*args, **kwargs) if _has_args(f) else f(),
File "/usr/local/lib/python3.7/dist-packages/tensorflow_probability/python/math/gradient.py", line 376, in <lambda>
    if _has_args(real_f) else real_f(), ())
File "/usr/local/lib/python3.7/dist-packages/tensorflow_probability/python/mcmc/transformed_kernel.py", line 123, in transformed_log_prob_fn
    tlp = log_prob_fn(*fn(state_parts))
File "/usr/local/lib/python3.7/dist-packages/tensorflow_probability/python/experimental/mcmc/sample_sequential_monte_carlo.py", line 96, in _tempered_target_log_prob
    priorlogprob = tf.identity(prior_log_prob_fn(*args),

TypeError: log_prob() takes from 2 to 3 positional arguments but 5 were given

"""

Any ideas about the error and how to fix it?

Reproduce the failure in the linked SMC Demo notebook by running run_smc_(). Start with tensorflow_probability/python/experimental/mcmc/sample_sequential_monte_carlo.py at _tempered_target_log_prob and trace the prior_log_prob_fn call; done means the demo no longer raises the reported TypeError.