code: def zeta_nu_loss_callback(
      losses, estimated_values, input: RLEstimatorInput
  ):
      def callback_fn(zeta_loss, nu_loss, estimator):
          losses.append((zeta_loss, nu_loss))
          estimated_values.append(estimator._compute_estimates(input))
  
      return callback_fn
  
imports: import logging
  import gym
  import torch
  from reagent.ope.estimators.sequential_estimators import Action, ActionDistribution, ActionSpace, IPSEstimator, Model, NeuralDualDICE, RandomRLPolicy, RewardProbability, RLEstimatorInput, RLPolicy, State, StateDistribution, Transition
  from reagent.ope.utils import RunningAverage
label_desc: Use image node_id 2 for calling a global function with example usage: zeta_nu_loss_callback(losses, estimated_values, input) and returns: callback_fn