class_docstr: Agent that plays randomly.
class_docstr_tok: ["Agent","that","plays","randomly","."]
code: def act(
      self,
      observation: tp.Any,
      reward: tp.Any,
      done: bool,
      info: tp.Optional[tp.Dict[tp.Any, tp.Any]] = None,
  ) -> tp.Any:
      return np.random.randint(self.num_outputs)
  
imports: import warnings
  import operator
  import copy
  import typing
  import gym
  import numpy
  from nevergrad.common.tools import pytorch_import_fix
  from nevergrad.parametrization import parameter
  from ..base import ExperimentFunction
  from .None import base
  from .None import envs
  import torch
  import torch.nn.functional
  from torch import nn
  from torch.utils.data import WeightedRandomSampler
label_desc: Use image node_id 2 for calling the RandomAgent obj's underlying member method code with example usage: obj.act(observation, reward, done, info) and returns: np