code: def learn_from_batch(self, batch):
      raise NotImplementedError(
          "PolicyOptimizationAgent is an abstract agent. Not to be used directly."
      )
  
file_path: coach/rl_coach/agents/policy_optimization_agent.py
imports: from collections import OrderedDict
  from enum import Enum
  from typing import Union
  import numpy
  from rl_coach.agents.agent import Agent
  from rl_coach.core_types import Batch, ActionInfo
  from rl_coach.logger import screen
  from rl_coach.spaces import DiscreteActionSpace, BoxActionSpace
  from rl_coach.utils import eps
label_desc: Use image node_id 5 for calling the PolicyOptimizationAgent obj's underlying member method code with example usage: obj.learn_from_batch(batch) without return types