80 lines
2.7 KiB
Python
80 lines
2.7 KiB
Python
"""Wrapper for adding time aware observations to environment observation."""
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import numpy as np
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import gymnasium as gym
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from gymnasium.spaces import Box
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class TimeAwareObservation(gym.ObservationWrapper, gym.utils.RecordConstructorArgs):
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"""Augment the observation with the current time step in the episode.
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The observation space of the wrapped environment is assumed to be a flat :class:`Box`.
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In particular, pixel observations are not supported. This wrapper will append the current timestep within the current episode to the observation.
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Example:
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>>> import gymnasium as gym
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>>> from gymnasium.wrappers import TimeAwareObservation
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>>> env = gym.make("CartPole-v1")
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>>> env = TimeAwareObservation(env)
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>>> env.reset(seed=42)
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(array([ 0.0273956 , -0.00611216, 0.03585979, 0.0197368 , 0. ]), {})
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>>> _ = env.action_space.seed(42)
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>>> env.step(env.action_space.sample())[0]
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array([ 0.02727336, -0.20172954, 0.03625453, 0.32351476, 1. ])
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"""
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def __init__(self, env: gym.Env):
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"""Initialize :class:`TimeAwareObservation` that requires an environment with a flat :class:`Box` observation space.
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Args:
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env: The environment to apply the wrapper
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"""
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gym.utils.RecordConstructorArgs.__init__(self)
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gym.ObservationWrapper.__init__(self, env)
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assert isinstance(env.observation_space, Box)
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assert env.observation_space.dtype == np.float32
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low = np.append(self.observation_space.low, 0.0)
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high = np.append(self.observation_space.high, np.inf)
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self.observation_space = Box(low, high, dtype=np.float32)
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try:
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self.is_vector_env = self.get_wrapper_attr("is_vector_env")
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except AttributeError:
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self.is_vector_env = False
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def observation(self, observation):
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"""Adds to the observation with the current time step.
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Args:
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observation: The observation to add the time step to
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Returns:
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The observation with the time step appended to
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"""
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return np.append(observation, self.t)
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def step(self, action):
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"""Steps through the environment, incrementing the time step.
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Args:
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action: The action to take
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Returns:
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The environment's step using the action.
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"""
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self.t += 1
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return super().step(action)
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def reset(self, **kwargs):
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"""Reset the environment setting the time to zero.
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Args:
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**kwargs: Kwargs to apply to env.reset()
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Returns:
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The reset environment
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"""
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self.t = 0
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return super().reset(**kwargs)
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