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https://github.com/vale981/ray
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32 lines
1 KiB
Python
32 lines
1 KiB
Python
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import numpy as np
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import gym
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from gym.envs.classic_control.cartpole import CartPoleEnv
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from ray.rllib.env.meta_env import MetaEnv
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class CartPoleMassEnv(CartPoleEnv, gym.utils.EzPickle, MetaEnv):
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"""CartPoleMassEnv varies the weights of the cart and the pole.
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"""
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def sample_tasks(self, n_tasks):
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# Sample new cart- and pole masses (random floats between 0.5 and 2.0
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# (cart) and between 0.05 and 0.2 (pole)).
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cart_masses = np.random.uniform(low=0.5, high=2.0, size=(n_tasks, 1))
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pole_masses = np.random.uniform(low=0.05, high=0.2, size=(n_tasks, 1))
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return np.concatenate([cart_masses, pole_masses], axis=-1)
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def set_task(self, task):
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"""
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Args:
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task (Tuple[float]): Masses of the cart and the pole.
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"""
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self.masscart = task[0]
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self.masspole = task[1]
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def get_task(self):
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"""
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Returns:
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Tuple[float]: The current mass of the cart- and pole.
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"""
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return np.array([self.masscart, self.masspole])
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