class_docstr: Doubly Robust (DR) estimator:
      reference: https://arxiv.org/abs/1103.4601 (deterministic reward model)
                 https://arxiv.org/abs/1612.01205 (distributed reward model)
code: def __init__(
      self,
      trainer: Optional[Trainer] = None,
      weight_clamper: Optional[Clamper] = None,
      device=None,
  ):
      super().__init__(trainer, device)
      self._weight_clamper = (
          Clamper() if weight_clamper is None else weight_clamper
      )
  
imports: import logging
  import time
  from abc import ABC, abstractmethod
  from dataclasses import dataclass
  from typing import Optional, Sequence, Tuple, Union
  import numpy
  import torch
  from reagent.ope.estimators.estimator import Estimator, EstimatorResult
  from reagent.ope.estimators.types import Action, ActionDistribution, ActionSpace, Reward, Trainer, TrainingData, Values
  from reagent.ope.utils import Clamper, RunningAverage
  from torch import Tensor
label_desc: Use image node_id 1 to create a new DoublyRobustEstimator object from inherited base classes: DMEstimator with example: obj = DoublyRobustEstimator(trainer, weight_clamper, device)