code: def __init__(self):
      super().__init__()
      self.input_embedders_parameters = {
          "observation": InputEmbedderParameters()
      }
      self.middleware_parameters = FCMiddlewareParameters()
      self.heads_parameters = [PolicyHeadParameters()]
      self.async_training = True
  
imports: from typing import Union
  import numpy
  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
  from rl_coach.architectures.middleware_parameters import FCMiddlewareParameters
  from rl_coach.base_parameters import NetworkParameters, AlgorithmParameters, AgentParameters
  from rl_coach.exploration_policies.additive_noise import AdditiveNoiseParameters
  from rl_coach.exploration_policies.categorical import CategoricalParameters
  from rl_coach.logger import screen
  from rl_coach.memories.episodic.single_episode_buffer import SingleEpisodeBufferParameters
  from rl_coach.spaces import DiscreteActionSpace, BoxActionSpace
label_desc: Use image node_id 1 to create a new PolicyGradientNetworkParameters object from inherited base classes: NetworkParameters with example: obj = PolicyGradientNetworkParameters()