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https://github.com/vale981/ray
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49 lines
1.3 KiB
Python
49 lines
1.3 KiB
Python
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"""Examples demonstrating the usage of RE3 exploration strategy.
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To use RE3 user will need to patch the callbacks with RE3 specific callbacks
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and set the `exploration_config` with RE3 configs.
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```Python
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config["exploration_config"] = {"type": "RE3"}
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"""
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from functools import partial
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import ray
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from ray.rllib.agents import sac
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from ray.rllib.agents.callbacks import MultiCallbacks, RE3UpdateCallbacks
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if __name__ == "__main__":
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ray.init()
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config = sac.DEFAULT_CONFIG.copy()
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# Add a new RE3UpdateCallbacks
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config["callbacks"] = MultiCallbacks(
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[
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config["callbacks"],
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partial(
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RE3UpdateCallbacks,
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embeds_dim=128,
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beta_schedule="linear_decay",
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k_nn=50,
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),
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]
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)
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config["env"] = "LunarLanderContinuous-v2"
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config["seed"] = 12345
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# Add type as RE3 in the exploration_config parameter
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config["exploration_config"] = {
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"type": "RE3",
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"sub_exploration": {
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"type": "StochasticSampling",
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},
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}
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num_iterations = 2000
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trainer = sac.SACTrainer(config=config)
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for i in range(num_iterations):
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result = trainer.train()
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print(result)
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trainer.stop()
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ray.shutdown()
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