class_docstr: Rejection sampled distribution given an acceptance rate function.
  
  :param Distribution propose: A proposal distribution that samples batched
      proposals via ``propose()``. :meth:`rsample` supports a ``sample_shape``
      arg only if ``propose()`` supports a ``sample_shape`` arg.
  :param callable log_prob_accept: A callable that inputs a batch of
      proposals and returns a batch of log acceptance probabilities.
  :param log_scale: Total log probability of acceptance.
class_docstr_tok: ["Rejection","sampled","distribution","given","an","acceptance","rate","function",".",":","param","Distribution","propose",":","A","proposal","distribution","that","samples","batched","proposals","via","``","propose","(",")","``",".",":","meth",":","`","rsample","`","supports","a","``","sample_shape","``","arg","only","if","``","propose","(",")","``","supports","a","``","sample_shape","``","arg",".",":","param","callable","log_prob_accept",":","A","callable","that","inputs","a","batch","of","proposals","and","returns","a","batch","of","log","acceptance","probabilities",".",":","param","log_scale",":","Total","log","probability","of","acceptance","."]
code: def _propose_log_prob(self, x):
      if x is not self._propose_log_prob_cache[0]:
          self._propose_log_prob_cache = x, self.propose.log_prob(x)
      return self._propose_log_prob_cache[1]
  
file_path: pyro/pyro/distributions/rejector.py
imports: import torch
  from pyro.distributions.score_parts import ScoreParts
  from pyro.distributions.torch_distribution import TorchDistribution
label_desc: Use image node_id 3 for calling the Rejector obj's underlying member method code with example usage: obj._propose_log_prob(x) and returns: self