code: def get_all_q_values_for_states(
      self, states: StateType, additional_outputs: List = None
  ):
      # we need to store the state embeddings regardless if the action is random or not
      return self.get_prediction_and_update_embeddings(states)
  
imports: import os
  import pickle
  from typing import Union, List
  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 DNDQHeadParameters
  from rl_coach.architectures.middleware_parameters import FCMiddlewareParameters
  from rl_coach.base_parameters import AlgorithmParameters, NetworkParameters, AgentParameters
  from rl_coach.core_types import RunPhase, EnvironmentSteps, Episode, StateType
  from rl_coach.exploration_policies.e_greedy import EGreedyParameters
  from rl_coach.logger import screen
  from rl_coach.memories.episodic.episodic_experience_replay import EpisodicExperienceReplayParameters, MemoryGranularity
  from rl_coach.schedules import ConstantSchedule
label_desc: Use image node_id 5 for calling the NECAgent obj's underlying member method code with example usage: obj.get_all_q_values_for_states(states, additional_outputs) and returns: self