docstr: Save the model of the agent to the disk. This can contain the network parameters, the memory of the agent, etc.
  :param checkpoint_prefix: The prefix of the checkpoint file to save
  :return: None
docstr_tok: ["Save","the","model","of","the","agent","to","the","disk",".","This","can","contain","the","network","parameters",",","the","memory","of","the","agent",",","etc",".",":","param","checkpoint_prefix",":","The","prefix","of","the","checkpoint","file","to","save",":","return",":","None"]
code: def save_checkpoint(self, checkpoint_prefix: str) -> None:
      """
      Save the model of the agent to the disk. This can contain the network parameters, the memory of the agent, etc.
      :param checkpoint_prefix: The prefix of the checkpoint file to save
      :return: None
      """
      raise NotImplementedError("")
  
imports: from typing import Union, List, Dict
  import numpy
  from rl_coach.core_types import EnvResponse, ActionInfo, RunPhase, PredictionType, ActionType, Transition
  from rl_coach.saver import SaverCollection
label_desc: Use image node_id 10 for calling the AgentInterface obj's underlying member method code with example usage: obj.save_checkpoint(checkpoint_prefix) without return types