code: def get_prediction(self, states):
      tf_input_state = self.prepare_batch_for_inference(states, "main")
      return self.networks["main"].online_network.predict(
          tf_input_state
      )
  
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 6 for calling the PolicyOptimizationAgent obj's underlying member method code with example usage: obj.get_prediction(states) and returns: self