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8d5c07b781
This PR adds a user guide to AIR for using Ray Train. It provides a high level overview of the trainers and removes redundant sections. The main file to review is here: doc/source/ray-air/trainer.rst. Signed-off-by: xwjiang2010 <xwjiang2010@gmail.com> Signed-off-by: Richard Liaw <rliaw@berkeley.edu> Signed-off-by: Kai Fricke <kai@anyscale.com> Co-authored-by: Richard Liaw <rliaw@berkeley.edu> Co-authored-by: Kai Fricke <kai@anyscale.com>
16 lines
476 B
Python
16 lines
476 B
Python
from ray.air.config import RunConfig, ScalingConfig
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from ray.train.rl import RLTrainer
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trainer = RLTrainer(
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run_config=RunConfig(stop={"training_iteration": 5}),
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scaling_config=ScalingConfig(num_workers=2, use_gpu=False),
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algorithm="PPO",
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config={
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"env": "CartPole-v0",
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"framework": "tf",
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"evaluation_num_workers": 1,
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"evaluation_interval": 1,
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"evaluation_config": {"input": "sampler"},
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},
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)
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result = trainer.fit()
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