code: def update_transition_priorities_and_get_weights(
      self, TD_errors, batch
  ):
      # update errors in prioritized replay buffer
      importance_weights = None
      if isinstance(self.memory, PrioritizedExperienceReplay):
          self.call_memory(
              "update_priorities", (batch.info("idx"), TD_errors)
          )
          importance_weights = batch.info("weight")
      return importance_weights
  
imports: from collections import OrderedDict
  from typing import Union, List
  import numpy
  from rl_coach.agents.agent import Agent
  from rl_coach.core_types import ActionInfo, StateType, Batch
  from rl_coach.filters.filter import NoInputFilter
  from rl_coach.logger import screen
  from rl_coach.memories.non_episodic.prioritized_experience_replay import PrioritizedExperienceReplay
  from rl_coach.spaces import DiscreteActionSpace
  from copy import deepcopy, copy
label_desc: Use image node_id 6 for calling the ValueOptimizationAgent obj's underlying member method code with example usage: obj.update_transition_priorities_and_get_weights(TD_errors, batch) and returns: importance_weights