code: def __init__(self):
      super().__init__(
          algorithm=ActorCriticAlgorithmParameters(),
          exploration={
              DiscreteActionSpace: CategoricalParameters(),
              BoxActionSpace: ContinuousEntropyParameters(),
          },
          memory=SingleEpisodeBufferParameters(),
          networks={"main": ActorCriticNetworkParameters()},
      )
  
imports: from typing import Union
  import numpy
  import scipy.signal
  from rl_coach.agents.policy_optimization_agent import PolicyOptimizationAgent, PolicyGradientRescaler
  from rl_coach.architectures.embedder_parameters import InputEmbedderParameters
  from rl_coach.architectures.head_parameters import PolicyHeadParameters, VHeadParameters
  from rl_coach.architectures.middleware_parameters import FCMiddlewareParameters
  from rl_coach.base_parameters import AlgorithmParameters, NetworkParameters, AgentParameters
  from rl_coach.exploration_policies.categorical import CategoricalParameters
  from rl_coach.exploration_policies.continuous_entropy import ContinuousEntropyParameters
  from rl_coach.logger import screen
  from rl_coach.memories.episodic.single_episode_buffer import SingleEpisodeBufferParameters
  from rl_coach.spaces import DiscreteActionSpace, BoxActionSpace
  from rl_coach.utils import last_sample
label_desc: Use image node_id 1 to create a new ActorCriticAgentParameters object from inherited base classes: AgentParameters with example: obj = ActorCriticAgentParameters()