code: def __init__(self):
      td3_algorithm_params = TD3AlgorithmParameters()
      super().__init__(
          algorithm=td3_algorithm_params,
          exploration=TD3AgentExplorationParameters(),
          memory=EpisodicExperienceReplayParameters(),
          networks=OrderedDict(
              [
                  ("actor", TD3ActorNetworkParameters()),
                  (
                      "critic",
                      TD3CriticNetworkParameters(
                          td3_algorithm_params.num_q_networks
                      ),
                  ),
              ]
          ),
      )
  
imports: import copy
  from typing import Union
  from collections import OrderedDict
  import numpy
  from rl_coach.agents.agent import Agent
  from rl_coach.agents.ddpg_agent import DDPGAgent
  from rl_coach.architectures.embedder_parameters import InputEmbedderParameters
  from rl_coach.architectures.head_parameters import DDPGActorHeadParameters, TD3VHeadParameters
  from rl_coach.architectures.middleware_parameters import FCMiddlewareParameters
  from rl_coach.base_parameters import NetworkParameters, AlgorithmParameters, AgentParameters, EmbedderScheme
  from rl_coach.core_types import ActionInfo, TrainingSteps, Transition
  from rl_coach.exploration_policies.additive_noise import AdditiveNoiseParameters
  from rl_coach.memories.episodic.episodic_experience_replay import EpisodicExperienceReplayParameters
  from rl_coach.spaces import BoxActionSpace, GoalsSpace
label_desc: Use image node_id 1 to create a new TD3AgentParameters object from inherited base classes: AgentParameters with example: obj = TD3AgentParameters()