class_docstr: A structured representation of a policy output over a full (flat) environment step.
class_docstr_tok: ["A","structured","representation","of","a","policy","output","over","a","full","(","flat",")","environment","step","."]
docstr: Append a given PolicySubStepOutput.
docstr_tok: ["Append","a","given","PolicySubStepOutput","."]
code: def append(self, value: PolicySubStepOutput):
      """Append a given PolicySubStepOutput."""
      self._step_policy_outputs.append(value)
  
file_path: maze/maze/core/agent/torch_policy_output.py
imports: import dataclasses
  from typing import List, Dict, Optional
  import torch
  from maze.core.env.action_conversion import TorchActionType
  from maze.core.env.structured_env import ActorID
  from maze.distributions.dict import DictProbabilityDistribution
label_desc: Use image node_id 3 for calling the PolicyOutput obj's underlying member method code with example usage: obj.append(value) without return types