class_docstr: A dummy implementation of a policy that wraps a TorchPolicy, as supported by ES.
docstr: Env state not required by `compute_action`
docstr_tok: ["Env","state","not","required","by","`","compute_action","`"]
code: def needs_state(self) -> bool:
      """Env state not required by `compute_action`"""
      return False
  
imports: from typing import Tuple, Optional, Sequence, Dict, List
  import torch
  import torch.nn
  from maze.core.agent.policy import Policy
  from maze.core.agent.torch_model import TorchModel
  from maze.core.agent.torch_policy import TorchPolicy
  from maze.core.annotations import override
  from maze.core.env.action_conversion import ActionType
  from maze.core.env.base_env import BaseEnv
  from maze.core.env.maze_env import MazeEnv
  from maze.core.env.maze_state import MazeStateType
  from maze.core.env.observation_conversion import ObservationType
  from maze.core.env.structured_env import StructuredEnv, ActorID
  from maze.core.wrappers.maze_gym_env_wrapper import GymMazeEnv
  from maze.distributions.distribution_mapper import DistributionMapper
  from maze.perception.models.built_in.flatten_concat import FlattenConcatPolicyNet
  from maze.train.trainers.es.distributed.es_dummy_distributed_rollouts import ESDummyDistributedRollouts
  from maze.train.trainers.es.distributed.es_subproc_distributed_rollouts import ESSubprocDistributedRollouts
  from maze.train.trainers.es.es_algorithm_config import ESAlgorithmConfig
  from maze.train.trainers.es.es_shared_noise_table import SharedNoiseTable
  from maze.train.trainers.es.es_trainer import ESTrainer
  from maze.train.trainers.es.optimizers.adam import Adam
label_desc: Use image node_id 3 for calling the DummyPolicyWrapper obj's underlying member method code with example usage: obj.needs_state() and returns: False