code: def __init__(
      self, action_names, gamma, model, metrics_to_score=None
  ) -> None:
      self.action_names = action_names
      self.metrics_to_score = metrics_to_score
  
      self.gamma = gamma
      self.model = model
  
      self.doubly_robust_estimator = DoublyRobustEstimator()
      self.sequential_doubly_robust_estimator = (
          SequentialDoublyRobustEstimator(gamma)
      )
      self.weighted_sequential_doubly_robust_estimator = (
          WeightedSequentialDoublyRobustEstimator(gamma)
      )
  
file_path: ReAgent/reagent/evaluation/evaluator.py
imports: import logging
  from collections import Counter
  from typing import Dict, List, Optional
  import torch
  import torch.nn.functional
  from reagent.core.tracker import observable
  from reagent.evaluation.cpe import CpeDetails, CpeEstimateSet
  from reagent.evaluation.doubly_robust_estimator import DoublyRobustEstimator
  from reagent.evaluation.evaluation_data_page import EvaluationDataPage
  from reagent.evaluation.sequential_doubly_robust_estimator import SequentialDoublyRobustEstimator
  from reagent.evaluation.weighted_sequential_doubly_robust_estimator import WeightedSequentialDoublyRobustEstimator
label_desc: Use image node_id 1 to create a new Evaluator object  with example: obj = Evaluator(action_names, gamma, model, metrics_to_score)