class_docstr: Randomly select a subsample of a range of indices.
  
  Internal use only. This should only be used by `plate`.
class_docstr_tok: ["Randomly","select","a","subsample","of","a","range","of","indices",".","Internal","use","only",".","This","should","only","be","used","by","`","plate","`","."]
code: def log_prob(self, x: torch.Tensor) -> torch.Tensor:
      # This is zero so that plate can provide an unbiased estimate of
      # the non-subsampled log_prob.
      result = torch.tensor(0.0, device=self.device)
      return result.cuda() if self.use_cuda else result
  
file_path: pyro/pyro/poutine/subsample_messenger.py
imports: from typing import Optional, Tuple
  import torch
  from pyro.distributions.distribution import Distribution
  from pyro.poutine.indep_messenger import CondIndepStackFrame, IndepMessenger
  from pyro.poutine.runtime import Message, apply_stack
  from pyro.poutine.util import is_validation_enabled
  from pyro.util import ignore_jit_warnings
label_desc: Use image node_id 3 for calling the _Subsample obj's underlying member method code with example usage: obj.log_prob(x) and returns: unknown