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https://github.com/wassname/ray.git
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Noah Golmant
1ef9c0729d
Introduces a minimally invasive utility for logging experiment results. A broad requirement for this tool is that it should integrate seamlessly with Tune execution.
19 lines
718 B
Python
19 lines
718 B
Python
from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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from ray.tune.error import TuneError
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from ray.tune.tune import run_experiments, run
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from ray.tune.experiment import Experiment
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from ray.tune.registry import register_env, register_trainable
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from ray.tune.trainable import Trainable
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from ray.tune.suggest import grid_search
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from ray.tune.sample import (function, sample_from, uniform, choice, randint,
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randn)
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__all__ = [
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"Trainable", "TuneError", "grid_search", "register_env",
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"register_trainable", "run", "run_experiments", "Experiment", "function",
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"sample_from", "track", "uniform", "choice", "randint", "randn"
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]
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