code: def __init__(self):
      super().__init__()
      self.num_consecutive_training_steps = 5
      self.num_steps_between_copying_online_weights_to_target = (
          EnvironmentSteps(1)
      )
      self.rate_for_copying_weights_to_target = 0.001
  
imports: from typing import Union
  import numpy
  from rl_coach.agents.value_optimization_agent import ValueOptimizationAgent
  from rl_coach.architectures.embedder_parameters import InputEmbedderParameters
  from rl_coach.architectures.head_parameters import NAFHeadParameters
  from rl_coach.architectures.middleware_parameters import FCMiddlewareParameters
  from rl_coach.base_parameters import AlgorithmParameters, AgentParameters, NetworkParameters
  from rl_coach.core_types import ActionInfo, EnvironmentSteps
  from rl_coach.exploration_policies.ou_process import OUProcessParameters
  from rl_coach.memories.episodic.episodic_experience_replay import EpisodicExperienceReplayParameters
  from rl_coach.spaces import BoxActionSpace
label_desc: Use image node_id 1 to create a new NAFAlgorithmParameters object from inherited base classes: AlgorithmParameters with example: obj = NAFAlgorithmParameters()