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@cottrell
Last active Mar 27, 2020
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WrappedTrackFunc error
import numpy as np
import pandas as pd
import ray
import ray.tune
import ray.tune.track
import tensorflow as tf
import tensorflow.keras
def ray_init(load_code_from_local=False):
if not ray.is_initialized():
print(f'load_code_from_local={load_code_from_local}')
return ray.init(
memory=2000 * 1024 * 1024,
object_store_memory=200 * 1024 * 1024,
driver_object_store_memory=100 * 1024 * 1024,
load_code_from_local=load_code_from_local,
)
def ray_bounce():
ray.disconnect()
return ray_init()
@ray.remote
def somesubfun(config):
# import tensorflow as tf # UNCOMMENT THIS TO SEE ERROR GO AWAY
# do something with tensorflow
opt = tf.keras.optimizers.Adam(learning_rate=0.1)
time.sleep(1)
return np.random.randn(1)
def somefun(config):
res = list()
for i in range(10):
res.append(somesubfun.remote(config))
res = ray.get(res)
res = np.mean(res)
ray.tune.track.init()
ray.tune.track.log(something=res, test="asdf")
return res
import hyperopt as ho
def test_ray_tuner():
space = dict(
l1=ho.hp.loguniform("l1", -2, 2),
l2=ho.hp.loguniform("l2", -2, 2),
concentration=ho.hp.loguniform("concentration", 0, 5),
)
from ray.tune.suggest.hyperopt import HyperOptSearch
search = HyperOptSearch(space, max_concurrent=10,
reward_attr="something", mode="min")
analysis = ray.tune.run(somefun, search_alg=search)
return analysis
if __name__ == '__main__':
ray_init()
print(test_ray_tuner())
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