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https://github.com/vale981/ray
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56 lines
1.8 KiB
Python
56 lines
1.8 KiB
Python
"""
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Example of an environment that uses a named remote actor as parameter
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server.
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"""
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from gym.envs.classic_control.cartpole import CartPoleEnv
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from gym.utils import seeding
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import ray
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@ray.remote
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class ParameterStorage:
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def get_params(self, rng):
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return {
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"MASSCART": rng.uniform(low=0.5, high=2.0),
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}
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class CartPoleWithRemoteParamServer(CartPoleEnv):
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"""CartPoleMassEnv varies the weights of the cart and the pole.
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"""
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def __init__(self, env_config):
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self.env_config = env_config
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super().__init__()
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# Get our param server (remote actor) by name.
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self._handler = ray.get_actor(
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env_config.get("param_server", "param-server"))
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# def seed(self, seed=None):
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# print(f"Seeding env (worker={self.env_config.worker_index}) "
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# f"with {seed}")
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# self.np_random, seed = seeding.np_random(seed)
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# return [seed]
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def reset(self):
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# Pass in our RNG to guarantee no race conditions.
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# If `self._handler` had its own RNG, this may clash with other
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# envs trying to use the same param-server.
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params = ray.get(self._handler.get_params.remote(self.np_random))
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# IMPORTANT: Advance the state of our RNG (self._rng was passed
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# above via ray (serialized) and thus not altered locally here!).
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# Or create a new RNG from another random number:
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new_seed = self.np_random.randint(0, 1000000)
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self.np_random, _ = seeding.np_random(new_seed)
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print(f"Env worker-idx={self.env_config.worker_index} "
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f"mass={params['MASSCART']}")
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self.masscart = params["MASSCART"]
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self.total_mass = (self.masspole + self.masscart)
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self.polemass_length = (self.masspole * self.length)
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return super().reset()
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