code: def verify_result(
      result_dict: Dict[str, float], expected_top_features: List[str]
  ):
      top_feature = max(result_dict, key=result_dict.get)
      assert (
          top_feature in expected_top_features
      ), f"top_feature: {top_feature}, expected_top_features: {expected_top_features}"
  
imports: import logging
  import os
  import unittest
  from typing import Dict, List, Optional
  import gym
  import numpy
  import reagent.core.types
  import torch
  from reagent.evaluation.world_model_evaluator import FeatureImportanceEvaluator, FeatureSensitivityEvaluator
  from reagent.gym.agents.agent import Agent
  from reagent.gym.envs import EnvWrapper, Gym
  from reagent.gym.envs.pomdp.state_embed_env import StateEmbedEnvironment
  from reagent.gym.policies.random_policies import make_random_policy_for_env
  from reagent.gym.preprocessors import make_replay_buffer_trainer_preprocessor
  from reagent.gym.runners.gymrunner import evaluate_for_n_episodes
  from reagent.gym.utils import build_normalizer, fill_replay_buffer
  from reagent.model_managers.union import ModelManager__Union
  from reagent.models.world_model import MemoryNetwork
  from reagent.replay_memory.circular_replay_buffer import ReplayBuffer
  from reagent.test.base.horizon_test_base import HorizonTestBase
  from reagent.training.world_model.mdnrnn_trainer import MDNRNNTrainer
  from reagent.workflow.types import RewardOptions
  from tqdm import tqdm
label_desc: Use image node_id 1 for calling the TestWorldModel obj's underlying member method code with example usage: obj.verify_result(result_dict, expected_top_features) without return types