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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>
13 lines
418 B
Python
13 lines
418 B
Python
import ray
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from ray.train.sklearn import SklearnTrainer
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from sklearn.ensemble import RandomForestRegressor
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train_dataset = ray.data.from_items([{"x": x, "y": x + 1} for x in range(32)])
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trainer = SklearnTrainer(
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estimator=RandomForestRegressor(),
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label_column="y",
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scaling_config=ray.air.config.ScalingConfig(trainer_resources={"CPU": 4}),
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datasets={"train": train_dataset},
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)
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result = trainer.fit()
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