class_docstr: Wrapper class for torch.distributions.
class_docstr_tok: ["Wrapper","class","for","torch.distributions","."]
code: def rsample(
      self,
      *,
      sample_shape=torch.Size(),
  ) -> Union[TensorType, Tuple[TensorType, TensorType]]:
      rsample = self._dist.rsample(sample_shape)
      return rsample
  
imports: import gymnasium
  import numpy
  from typing import Optional, List, Mapping, Iterable, Dict
  import tree
  import abc
  from ray.rllib.models.distributions import Distribution
  from ray.rllib.utils.annotations import override, DeveloperAPI
  from ray.rllib.utils.framework import try_import_torch
  from ray.rllib.utils.typing import TensorType, Union, Tuple
label_desc: Use image node_id 7 for calling the TorchDistribution obj's underlying member method code with example usage: obj.rsample() and returns: rsample