code: def __init__(
      self,
      agent_parameters,
      parent: Union["LevelManager", "CompositeAgent"] = None,
  ):
      super().__init__(agent_parameters, parent)
      self.last_gradient_update_step_idx = 0
  
      # register signals to track (in learn_from_batch)
      self.policy_means = self.register_signal("Policy_mu_avg")
      self.policy_logsig = self.register_signal("Policy_logsig")
      self.policy_logprob_sampled = self.register_signal(
          "Policy_logp_sampled"
      )
      self.policy_grads = self.register_signal("Policy_grads_sumabs")
  
      self.q1_values = self.register_signal("Q1")
      self.TD_err1 = self.register_signal("TD err1")
      self.q2_values = self.register_signal("Q2")
      self.TD_err2 = self.register_signal("TD err2")
      self.v_tgt_ns = self.register_signal("V_tgt_ns")
      self.v_onl_ys = self.register_signal("V_onl_ys")
      self.action_signal = self.register_signal("actions")
  
imports: from typing import Union
  import copy
  import numpy
  from collections import OrderedDict
  from rl_coach.agents.agent import Agent
  from rl_coach.agents.policy_optimization_agent import PolicyOptimizationAgent
  from rl_coach.architectures.head_parameters import SACQHeadParameters, SACPolicyHeadParameters, VHeadParameters
  from rl_coach.architectures.middleware_parameters import FCMiddlewareParameters
  from rl_coach.base_parameters import AlgorithmParameters, NetworkParameters, AgentParameters, EmbedderScheme, MiddlewareScheme
  from rl_coach.core_types import ActionInfo, EnvironmentSteps, RunPhase
  from rl_coach.exploration_policies.additive_noise import AdditiveNoiseParameters
  from rl_coach.memories.non_episodic.experience_replay import ExperienceReplayParameters
  from rl_coach.architectures.embedder_parameters import InputEmbedderParameters
  from rl_coach.spaces import BoxActionSpace
label_desc: Use image node_id 1 to create a new SoftActorCriticAgent object from inherited base classes: PolicyOptimizationAgent with example: obj = SoftActorCriticAgent(agent_parameters, parent)