wehub-resource-sync
63 lines
1.8 KiB
Python
63 lines
1.8 KiB
Python
#!/usr/bin/env python
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import argparse
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import ray
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from ray import tune
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from ray.tune.examples.pbt_function import pbt_function
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from ray.tune.schedulers.pb2 import PB2
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if __name__ == "__main__":
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parser = argparse.ArgumentParser()
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parser.add_argument(
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"--smoke-test", action="store_true", help="Finish quickly for testing"
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)
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args, _ = parser.parse_known_args()
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if args.smoke_test:
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ray.init(num_cpus=2) # force pausing to happen for test
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perturbation_interval = 5
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pbt = PB2(
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time_attr="training_iteration",
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perturbation_interval=perturbation_interval,
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hyperparam_bounds={
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# hyperparameter bounds.
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"lr": [0.0001, 0.02],
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},
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)
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tuner = tune.Tuner(
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pbt_function,
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run_config=tune.RunConfig(
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name="pbt_test",
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verbose=False,
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stop={
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"training_iteration": 30,
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},
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failure_config=tune.FailureConfig(
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fail_fast=True,
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),
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),
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tune_config=tune.TuneConfig(
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scheduler=pbt,
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metric="mean_accuracy",
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mode="max",
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num_samples=8,
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reuse_actors=True,
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),
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param_space={
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"lr": 0.0001,
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# note: this parameter is perturbed but has no effect on
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# the model training in this example
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"some_other_factor": 1,
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# This parameter is not perturbed and is used to determine
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# checkpoint frequency. We set checkpoints and perturbations
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# to happen at the same frequency.
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"checkpoint_interval": perturbation_interval,
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},
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)
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results = tuner.fit()
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print("Best hyperparameters found were: ", results.get_best_result().config)
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