class_docstr: Wrapper to add per-example caching to a LIT model.
code: def _get_results_from_cache(self, input_keys: list[CacheKey]):
      with self._cache.lock:
          return [
              self._cache.get(input_key) for input_key in input_keys
          ]
  
imports: from collections.abc import Callable, Iterable
  import os
  import pickle
  import threading
  from typing import Any, Optional, Union
  from absl import logging
  from lit_nlp.api import dataset
  from lit_nlp.api import model
  from lit_nlp.api import types
  from lit_nlp.lib import serialize
label_desc: Use image node_id 8 for calling the CachingModelWrapper obj's underlying member method code with example usage: obj._get_results_from_cache(input_keys) and returns: unknown