38 lines
1.0 KiB
Python
38 lines
1.0 KiB
Python
import alr_envs
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def example_mp(env_name, seed=1, render=True):
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"""
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Example for running a motion primitive based version of a OpenAI-gym environment, which is already registered.
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For more information on motion primitive specific stuff, look at the traj_gen examples.
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Args:
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env_name: ProMP env_id
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seed: seed
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render: boolean
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Returns:
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"""
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# While in this case gym.make() is possible to use as well, we recommend our custom make env function.
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env = alr_envs.make(env_name, seed)
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returns = 0
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obs = env.reset()
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# number of samples/full trajectories (multiple environment steps)
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for i in range(10):
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if render and i % 2 == 0:
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env.render(mode="human")
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else:
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env.render(mode=None)
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ac = env.action_space.sample()
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obs, reward, done, info = env.step(ac)
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returns += reward
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if done:
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print(returns)
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obs = env.reset()
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if __name__ == '__main__':
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example_mp("ReacherProMP-v2")
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