code: def distribution_prediction_to_q_values(self, prediction):
      return np.dot(prediction, self.z_values)
  
imports: from typing import Union
  import numpy
  from rl_coach.agents.dqn_agent import DQNNetworkParameters, DQNAlgorithmParameters, DQNAgentParameters
  from rl_coach.agents.value_optimization_agent import ValueOptimizationAgent
  from rl_coach.architectures.head_parameters import CategoricalQHeadParameters
  from rl_coach.core_types import StateType
  from rl_coach.exploration_policies.e_greedy import EGreedyParameters
  from rl_coach.memories.non_episodic.prioritized_experience_replay import PrioritizedExperienceReplay
  from rl_coach.schedules import LinearSchedule
label_desc: Use image node_id 3 for calling the CategoricalDQNAgent obj's underlying member method code with example usage: obj.distribution_prediction_to_q_values(prediction) and returns: np