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https://github.com/wassname/ray.git
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Richard Liaw
86 lines
2.3 KiB
Python
86 lines
2.3 KiB
Python
"""This test checks that Dragonfly is functional.
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It also checks that it is usable with a separate scheduler.
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"""
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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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import numpy as np
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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 ray.tune.suggest import ConcurrencyLimiter
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from ray.tune.schedulers import AsyncHyperBandScheduler
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from ray.tune.suggest.dragonfly import DragonflySearch
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def objective(config):
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for i in range(config["iterations"]):
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vol1 = config["point"][0] # LiNO3
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vol2 = config["point"][1] # Li2SO4
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vol3 = config["point"][2] # NaClO4
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vol4 = 10 - (vol1 + vol2 + vol3) # Water
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# Synthetic functions
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conductivity = vol1 + 0.1 * (vol2 + vol3)**2 + 2.3 * vol4 * (vol1**1.5)
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# Add Gaussian noise to simulate experimental noise
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conductivity += np.random.normal() * 0.01
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tune.report(timesteps_total=i, objective=conductivity)
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time.sleep(0.02)
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if __name__ == "__main__":
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import argparse
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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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args, _ = parser.parse_known_args()
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ray.init()
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tune_kwargs = {
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"num_samples": 10 if args.smoke_test else 50,
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"config": {
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"iterations": 100,
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"LiNO3_vol": tune.uniform(0, 7),
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"Li2SO4_vol": tune.uniform(0, 7),
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"NaClO4_vol": tune.uniform(0, 7)
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},
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}
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# Optional: Pass the parameter space yourself
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# space = [{
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# "name": "LiNO3_vol",
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# "type": "float",
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# "min": 0,
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# "max": 7
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# }, {
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# "name": "Li2SO4_vol",
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# "type": "float",
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# "min": 0,
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# "max": 7
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# }, {
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# "name": "NaClO4_vol",
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# "type": "float",
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# "min": 0,
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# "max": 7
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# }]
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df_search = DragonflySearch(
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optimizer="bandit",
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domain="euclidean",
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# space=space, # If you want to set the space manually
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)
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df_search = ConcurrencyLimiter(df_search, max_concurrent=4)
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scheduler = AsyncHyperBandScheduler()
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tune.run(
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objective,
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metric="objective",
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mode="max",
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name="dragonfly_search",
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search_alg=df_search,
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scheduler=scheduler,
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**tune_kwargs)
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