tensorflow_probability/python/mcmc/metropolis_hastings.py
def bootstrap_results(self, init_state):
    """Returns an object with the same type as returned by `one_step`.

    Args:
      init_state: `Tensor` or Python `list` of `Tensor`s representing the
        initial state(s) of the Markov chain(s).

    Returns:
      kernel_results: A (possibly nested) `tuple`, `namedtuple` or `list` of
        `Tensor`s representing internal calculations made within this function.

    Raises:
      ValueError: if `inner_kernel` results doesn't contain the member
        "target_log_prob".
    """
    with tf.compat.v1.name_scope(
        name=mcmc_util.make_name(self.name, 'mh', 'bootstrap_results'),
        values=[init_state]):
      pkr = self.inner_kernel.bootstrap_results(init_state)
      if not has_target_log_prob(pkr):
        raise ValueError(
            '"target_log_prob" must be a member of `inner_kernel` results.')
      x = pkr.target_log_prob
      return MetropolisHastingsKernelResults(
          accepted_results=pkr,
          is_accepted=tf.ones_like(x, dtype=tf.bool),
          log_accept_ratio=tf.zeros_like(x),
          proposed_state=init_state,
          proposed_results=pkr,
          extra=[],
      )
def bootstrap_results(self, init_state):
    """Returns an object with the same type as returned by `one_step`.

    Args:
      init_state: `Tensor` or Python `list` of `Tensor`s representing the
        initial state(s) of the Markov chain(s).

    Returns:
      kernel_results: A (possibly nested) `tuple`, `namedtuple` or `list` of
        `Tensor`s representing internal calculations made within this function.

    Raises:
      ValueError: if `inner_kernel` results doesn't contain the member
        "target_log_prob".
    """
    with tf.compat.v1.name_scope(
        name=mcmc_util.make_name(self.name, 'mh', 'bootstrap_results'),
        values=[init_state]):
      pkr = self.inner_kernel.bootstrap_results(init_state)
      if not has_target_log_prob(pkr):
        raise ValueError(
            '"target_log_prob" must be a member of `inner_kernel` results.')
      x = pkr.target_log_prob
      return MetropolisHastingsKernelResults(
          accepted_results=pkr,
          is_accepted=tf.ones_like(x, dtype=tf.bool),
          log_accept_ratio=tf.zeros_like(x),
          proposed_state=init_state,
          proposed_results=pkr,
          extra=[],
      )
Returns an object with the same type as returned by `one_step`.

    Args:
      init_state: `Tensor` or Python `list` of `Tensor`s representing the
        initial state(s) of the Markov chain(s).

    Returns:
      kernel_results: A (possibly nested) `tuple`, `namedtuple` or `list` of
        `Tensor`s representing internal calculations made within this function.

    Raises:
      ValueError: if `inner_kernel` results doesn't contain the member
        "target_log_prob".