code: def __init__(self):
      super().__init__()
      self.input_embedders_parameters = {
          "observation": InputEmbedderParameters()
      }
      self.middleware_parameters = FCMiddlewareParameters(
          scheme=MiddlewareScheme.Medium
      )
      self.heads_parameters = [QHeadParameters()]
      self.optimizer_type = "Adam"
      self.batch_size = 32
      self.replace_mse_with_huber_loss = True
      self.create_target_network = True
      self.should_get_softmax_probabilities = False
  
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 QHeadParameters
  from rl_coach.architectures.middleware_parameters import FCMiddlewareParameters
  from rl_coach.base_parameters import AlgorithmParameters, NetworkParameters, AgentParameters, MiddlewareScheme
  from rl_coach.core_types import EnvironmentSteps
  from rl_coach.exploration_policies.e_greedy import EGreedyParameters
  from rl_coach.memories.non_episodic.experience_replay import ExperienceReplayParameters
  from rl_coach.schedules import LinearSchedule
label_desc: Use image node_id 1 to create a new DQNNetworkParameters object from inherited base classes: NetworkParameters with example: obj = DQNNetworkParameters()