mirror of
https://github.com/vale981/ray
synced 2025-03-06 02:21:39 -05:00
862d10c162
Removes all ML related code from `ray.util` Removes: - `ray.util.xgboost` - `ray.util.lightgbm` - `ray.util.horovod` - `ray.util.ray_lightning` Moves `ray.util.ml_utils` to other locations Closes #23900 Signed-off-by: Amog Kamsetty <amogkamsetty@yahoo.com> Signed-off-by: Kai Fricke <kai@anyscale.com> Co-authored-by: Kai Fricke <kai@anyscale.com>
72 lines
1.8 KiB
Python
72 lines
1.8 KiB
Python
"""Moderate Ray Tune run (4 trials, 32 actors).
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This training run will start 4 Ray Tune trials, each starting 32 actors.
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The cluster comprises 32 nodes.
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Test owner: Yard1 (primary), krfricke
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Acceptance criteria: Should run through and report final results, as well
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as the Ray Tune results table. No trials should error. All trials should
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run in parallel.
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"""
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from collections import Counter
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import json
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import os
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import time
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import ray
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from ray import tune
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from lightgbm_ray import RayParams
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from release_test_util import train_ray
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def train_wrapper(config, ray_params):
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train_ray(
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path="/data/classification.parquet",
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num_workers=None,
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num_boost_rounds=100,
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num_files=128,
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regression=False,
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use_gpu=False,
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ray_params=ray_params,
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lightgbm_params=config,
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)
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if __name__ == "__main__":
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search_space = {
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"eta": tune.loguniform(1e-4, 1e-1),
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"subsample": tune.uniform(0.5, 1.0),
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"max_depth": tune.randint(1, 9),
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}
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ray.init(address="auto", runtime_env={"working_dir": os.path.dirname(__file__)})
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ray_params = RayParams(
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elastic_training=False,
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max_actor_restarts=2,
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num_actors=16,
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cpus_per_actor=2,
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gpus_per_actor=0,
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)
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start = time.time()
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analysis = tune.run(
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tune.with_parameters(train_wrapper, ray_params=ray_params),
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config=search_space,
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num_samples=4,
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resources_per_trial=ray_params.get_tune_resources(),
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)
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taken = time.time() - start
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result = {
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"time_taken": taken,
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"trial_states": dict(Counter([trial.status for trial in analysis.trials])),
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}
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test_output_json = os.environ.get("TEST_OUTPUT_JSON", "/tmp/tune_4x16.json")
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with open(test_output_json, "wt") as f:
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json.dump(result, f)
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print("PASSED.")
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