class_docstr: Evaluate state feature sensitivity caused by varying actions
class_docstr_tok: ["Evaluate","state","feature","sensitivity","caused","by","varying","actions"]
code: def __init__(
      self,
      trainer: MDNRNNTrainer,
      state_feature_num: int,
      sorted_state_feature_start_indices: List[int],
  ) -> None:
      self.trainer = trainer
      self.state_feature_num = state_feature_num
      self.sorted_state_feature_start_indices = (
          sorted_state_feature_start_indices
      )
  
file_path: ReAgent/reagent/evaluation/world_model_evaluator.py
imports: import logging
  from typing import Dict, List
  import torch
  from reagent.core.types import FeatureData, MemoryNetworkInput
  from reagent.training.world_model.mdnrnn_trainer import MDNRNNTrainer
label_desc: Use image node_id 1 to create a new FeatureSensitivityEvaluator object  with example: obj = FeatureSensitivityEvaluator(trainer, state_feature_num, sorted_state_feature_start_indices)