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33 lines
993 B
Python
33 lines
993 B
Python
from gym.envs.classic_control.pendulum import PendulumEnv
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from gym.utils import EzPickle
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import numpy as np
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from ray.rllib.env.apis.task_settable_env import TaskSettableEnv
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class PendulumMassEnv(PendulumEnv, EzPickle, TaskSettableEnv):
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"""PendulumMassEnv varies the weight of the pendulum
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Tasks are defined to be weight uniformly sampled between [0.5,2]
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"""
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def sample_tasks(self, n_tasks):
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# Sample new pendulum masses (random floats between 0.5 and 2).
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return np.random.uniform(low=0.5, high=2.0, size=(n_tasks,))
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def set_task(self, task):
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"""
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Args:
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task: Task of the meta-learning environment (here: mass of
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the pendulum).
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"""
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# self.m is the mass property of the pendulum.
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self.m = task
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def get_task(self):
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"""
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Returns:
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float: The current mass of the pendulum (self.m in the PendulumEnv
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object).
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"""
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return self.m
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