class_docstr: Interface for an off policy estimator for counterfactual evaluation.
class_docstr_tok: ["Interface","for","an","off","policy","estimator","for","counterfactual","evaluation","."]
docstr: This is called on each episode before it is passed to
  estimate_on_single_episode(). Using this method, you can get a peek at the
  entire validation dataset before runnining the estimation. For examlpe if you
  need to perform any normalizations of any sorts on the dataset, you can compute
  the normalization parameters here.
  
  Args:
      episode: The episode that is split from the original batch. This is a
      sample batch type that is a single episode.
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code: def peek_on_single_episode(self, episode: SampleBatch) -> None:
      """This is called on each episode before it is passed to
      estimate_on_single_episode(). Using this method, you can get a peek at the
      entire validation dataset before runnining the estimation. For examlpe if you
      need to perform any normalizations of any sorts on the dataset, you can compute
      the normalization parameters here.
  
      Args:
          episode: The episode that is split from the original batch. This is a
          sample batch type that is a single episode.
      """
      pass
  
imports: import gymnasium
  import numpy
  import tree
  from typing import Dict, Any, List
  import logging
  from ray.rllib.policy.sample_batch import SampleBatch
  from ray.rllib.policy import Policy
  from ray.rllib.policy.sample_batch import convert_ma_batch_to_sample_batch
  from ray.rllib.utils.policy import compute_log_likelihoods_from_input_dict
  from ray.rllib.utils.annotations import DeveloperAPI, ExperimentalAPI, OverrideToImplementCustomLogic
  from ray.rllib.utils.deprecation import Deprecated
  from ray.rllib.utils.numpy import convert_to_numpy
  from ray.rllib.utils.typing import TensorType, SampleBatchType
  from ray.rllib.offline.offline_evaluator import OfflineEvaluator
label_desc: Use image node_id 6 for calling the OffPolicyEstimator obj's underlying member method code with example usage: obj.peek_on_single_episode(episode) without return types