def get_preprocessor_as_wrapper(cls, env, options=dict()):
"""Returns a preprocessor as a gym observation wrapper.
Args:
env (gym.Env): The gym environment to wrap.
options (dict): Options to pass to the preprocessor.
Returns:
wrapper (gym.ObservationWrapper): Preprocessor in wrapper form.
"""
preprocessor = cls.get_preprocessor(env, options)
return _RLlibPreprocessorWrapper(env, preprocessor)
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