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: List of action logits for the individual sub-steps
docstr_tok: ["List","of","action","logits","for","the","individual","sub-steps"]
code: def action_logits(self) -> List[Dict[str, torch.Tensor]]:
      """List of action logits for the individual sub-steps"""
      return [po.action_logits for po in self._step_policy_outputs]
  
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 5 for calling the PolicyOutput obj's underlying member method code with example usage: obj.action_logits() and returns: unknown