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https://github.com/wassname/ray.git
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Philipp MoritzandRobert Nishihara
164a8f368e
* rename algorithms * fix * fix jenkins test * fix documentation * fix
45 lines
1.3 KiB
Python
Executable File
45 lines
1.3 KiB
Python
Executable File
#!/usr/bin/env python
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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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import ray
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import random
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from ray.rllib.dqn import (DQNAgent, DEFAULT_CONFIG as DQN_CONFIG)
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from ray.rllib.es import (ESAgent, DEFAULT_CONFIG as ES_CONFIG)
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from ray.rllib.ppo import (PPOAgent, DEFAULT_CONFIG as PG_CONFIG)
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from ray.rllib.a3c import (A3CAgent, DEFAULT_CONFIG as A3C_CONFIG)
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ray.init()
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for (cls, default_config) in [
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(DQNAgent, DQN_CONFIG),
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# TODO(ekl) this fails with multiple ES instances in a process
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(ESAgent, ES_CONFIG),
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(PPOAgent, PG_CONFIG),
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(A3CAgent, A3C_CONFIG)]:
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config = default_config.copy()
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config["num_sgd_iter"] = 5
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config["episodes_per_batch"] = 100
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config["timesteps_per_batch"] = 1000
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alg1 = cls('CartPole-v0', config)
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alg2 = cls('CartPole-v0', config)
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for _ in range(3):
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res = alg1.train()
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print("current status: " + str(res))
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# Sync the models
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alg2.restore(alg1.save())
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for _ in range(10):
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obs = [
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random.random(), random.random(), random.random(), random.random()]
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a1 = alg1.compute_action(obs)
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a2 = alg2.compute_action(obs)
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print("Checking computed actions", obs, a1, a2)
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# TODO(ekl) this fails for stochastic policies
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assert(a1 == a2)
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