class_docstr: Naive Marsaglia & Tsang rejection sampler for standard Gamma distibution.
  This assumes `concentration >= 1` and does not boost `concentration` or augment shape.
code: def log_prob_accept(self, value):
      v = value / self._d
      y = torch.pow(v, 1.0 / 3.0)
      x = (y - 1.0) / self._c
      log_prob_accept = 0.5 * x * x + self._d * (1.0 - v + torch.log(v))
      log_prob_accept[y <= 0] = -float("inf")
      return log_prob_accept
  
imports: import torch
  from pyro.distributions.rejector import Rejector
  from pyro.distributions.score_parts import ScoreParts
  from pyro.distributions.torch import Beta, Dirichlet, Gamma, Normal
  from pyro.distributions.util import copy_docs_from, weakmethod
label_desc: Use image node_id 5 for calling the RejectionStandardGamma obj's underlying member method code with example usage: obj.log_prob_accept(value) and returns: log_prob_accept