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476455e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | import os
import ray
import ray.rllib.agents.ppo as ppo
from ray.tune.logger import pretty_print
# Based on https://github.com/ray-project/ray/blob/master/doc/source/rllib-training.rst#python-api
ray.init(log_to_driver=False)
config = ppo.DEFAULT_CONFIG.copy()
config["num_gpus"] = int(os.environ.get("SM_NUM_GPUS", 0))
checkpoint_dir = os.environ.get("SM_MODEL_DIR", "/tmp")
config["num_workers"] = 1
agent = ppo.PPOTrainer(config=config, env="CartPole-v0")
# Can optionally call agent.restore(path) to load a checkpoint.
for i in range(5):
# Perform one iteration of training the policy with PPO
result = agent.train()
print(pretty_print(result))
checkpoint = agent.save(checkpoint_dir=checkpoint_dir)
print("checkpoint saved at", checkpoint)
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