Running Tune experiments with HyperOpt#
In this tutorial we introduce HyperOpt, while running a simple Ray Tune experiment. Tune’s Search Algorithms integrate with HyperOpt and, as a result, allow you to seamlessly scale up a Hyperopt optimization process - without sacrificing performance.
HyperOpt provides gradient/derivative-free optimization able to handle noise over the objective landscape, including evolutionary, bandit, and Bayesian optimization algorithms. HyperOpt internally supports search spaces which are continuous, discrete or a mixture of thereof. It also provides a library of functions on which to test the optimization algorithms and compare with other benchmarks.
In this example we minimize a simple objective to briefly demonstrate the usage of HyperOpt with Ray Tune via HyperOptSearch
. It’s useful to keep in mind that despite the emphasis on machine learning experiments, Ray Tune optimizes any implicit or explicit objective. Here we assume hyperopt==0.2.5
library is installed. To learn more, please refer to HyperOpt website.
We include a important example on conditional search spaces (stringing together relationships among hyperparameters).
Background information:
Necessary requirements:
pip install ray[tune]
pip install hyperopt==0.2.5
Click below to see all the imports we need for this example. You can also launch directly into a Binder instance to run this notebook yourself. Just click on the rocket symbol at the top of the navigation.
Show code cell source
import time
import ray
from ray import train, tune
from ray.tune.search import ConcurrencyLimiter
from ray.tune.search.hyperopt import HyperOptSearch
from hyperopt import hp
Let’s start by defining a simple evaluation function.
We artificially sleep for a bit (0.1
seconds) to simulate a long-running ML experiment.
This setup assumes that we’re running multiple step
s of an experiment and try to tune two hyperparameters,
namely width
and height
.
def evaluate(step, width, height):
time.sleep(0.1)
return (0.1 + width * step / 100) ** (-1) + height * 0.1
Next, our objective
function takes a Tune config
, evaluates the score
of your experiment in a training loop,
and uses train.report
to report the score
back to Tune.
def objective(config):
for step in range(config["steps"]):
score = evaluate(step, config["width"], config["height"])
train.report({"iterations": step, "mean_loss": score})
While defining the search algorithm, we may choose to provide an initial set of hyperparameters that we believe are especially promising or informative, and
pass this information as a helpful starting point for the HyperOptSearch
object.
We also set the maximum concurrent trials to 4
with a ConcurrencyLimiter
.
initial_params = [
{"width": 1, "height": 2, "activation": "relu"},
{"width": 4, "height": 2, "activation": "tanh"},
]
algo = HyperOptSearch(points_to_evaluate=initial_params)
algo = ConcurrencyLimiter(algo, max_concurrent=4)
The number of samples is the number of hyperparameter combinations that will be tried out. This Tune run is set to 1000
samples.
(you can decrease this if it takes too long on your machine).
num_samples = 1000
Next we define a search space. The critical assumption is that the optimal hyperparamters live within this space. Yet, if the space is very large, then those hyperparameters may be difficult to find in a short amount of time.
search_config = {
"steps": 100,
"width": tune.uniform(0, 20),
"height": tune.uniform(-100, 100),
"activation": tune.choice(["relu", "tanh"])
}
Finally, we run the experiment to "min"
imize the “mean_loss” of the objective
by searching search_config
via algo
, num_samples
times. This previous sentence is fully characterizes the search problem we aim to solve. With this in mind, notice how efficient it is to execute tuner.fit()
.
tuner = tune.Tuner(
objective,
tune_config=tune.TuneConfig(
metric="mean_loss",
mode="min",
search_alg=algo,
num_samples=num_samples,
),
param_space=search_config,
)
results = tuner.fit()
Current time: 2022-07-22 15:31:49 (running for 00:00:43.71)
Memory usage on this node: 10.4/16.0 GiB
Using FIFO scheduling algorithm.
Resources requested: 0/16 CPUs, 0/0 GPUs, 0.0/5.29 GiB heap, 0.0/2.0 GiB objects
Current best trial: f59fe9d6 with mean_loss=-2.5719085451008423 and parameters={'steps': 100, 'width': 5.584304853357766, 'height': -27.49576980043919, 'activation': 'tanh'}
Result logdir: /Users/kai/ray_results/objective_2022-07-22_15-31-04
Number of trials: 10/10 (10 TERMINATED)
Trial name | status | loc | activation | height | steps | width | loss | iter | total time (s) | iterations | neg_mean_loss |
---|---|---|---|---|---|---|---|---|---|---|---|
objective_eb74f122 | TERMINATED | 127.0.0.1:47156 | relu | 2 | 100 | 1 | 1.11743 | 100 | 10.9008 | 99 | -1.11743 |
objective_ed2010ec | TERMINATED | 127.0.0.1:47161 | tanh | 2 | 100 | 4 | 0.446305 | 100 | 11.5098 | 99 | -0.446305 |
objective_ed217cf2 | TERMINATED | 127.0.0.1:47162 | tanh | -20.6075 | 100 | 13.061 | -1.98401 | 100 | 11.5623 | 99 | 1.98401 |
objective_ed2322be | TERMINATED | 127.0.0.1:47163 | tanh | 19.9564 | 100 | 10.6836 | 2.0893 | 100 | 11.6053 | 99 | -2.0893 |
objective_f3a0bef8 | TERMINATED | 127.0.0.1:47180 | tanh | -7.43915 | 100 | 2.23969 | -0.312378 | 100 | 10.7378 | 99 | 0.312378 |
objective_f59fe9d6 | TERMINATED | 127.0.0.1:47185 | tanh | -27.4958 | 100 | 5.5843 | -2.57191 | 100 | 10.7145 | 99 | 2.57191 |
objective_f5aedf9a | TERMINATED | 127.0.0.1:47188 | tanh | 48.706 | 100 | 19.7352 | 4.92153 | 100 | 10.7341 | 99 | -4.92153 |
objective_f5b1ec08 | TERMINATED | 127.0.0.1:47189 | tanh | 4.14098 | 100 | 16.2739 | 0.475784 | 100 | 10.7034 | 99 | -0.475784 |
objective_fb926d32 | TERMINATED | 127.0.0.1:47205 | tanh | 44.778 | 100 | 10.0724 | 4.57708 | 100 | 13.1109 | 99 | -4.57708 |
objective_fd91e28e | TERMINATED | 127.0.0.1:47214 | relu | -2.9623 | 100 | 11.8215 | -0.211508 | 100 | 10.7934 | 99 | 0.211508 |
Result for objective_eb74f122:
date: 2022-07-22_15-31-08
done: false
experiment_id: 0ed1b6ba6d99477dba0632102d1bc531
hostname: Kais-MacBook-Pro.local
iterations: 0
iterations_since_restore: 1
mean_loss: 10.2
neg_mean_loss: -10.2
node_ip: 127.0.0.1
pid: 47156
time_since_restore: 0.10458922386169434
time_this_iter_s: 0.10458922386169434
time_total_s: 0.10458922386169434
timestamp: 1658500268
timesteps_since_restore: 0
training_iteration: 1
trial_id: eb74f122
warmup_time: 0.002730131149291992
Result for objective_ed2010ec:
date: 2022-07-22_15-31-11
done: false
experiment_id: 3acf6a8ccf8442a7adcf98cc92362216
hostname: Kais-MacBook-Pro.local
iterations: 0
iterations_since_restore: 1
mean_loss: 10.2
neg_mean_loss: -10.2
node_ip: 127.0.0.1
pid: 47161
time_since_restore: 0.1025240421295166
time_this_iter_s: 0.1025240421295166
time_total_s: 0.1025240421295166
timestamp: 1658500271
timesteps_since_restore: 0
training_iteration: 1
trial_id: ed2010ec
warmup_time: 0.0034351348876953125
Result for objective_ed2322be:
date: 2022-07-22_15-31-11
done: false
experiment_id: e95895ab00b54841933d324c3de8f58e
hostname: Kais-MacBook-Pro.local
iterations: 0
iterations_since_restore: 1
mean_loss: 11.99564236159307
neg_mean_loss: -11.99564236159307
node_ip: 127.0.0.1
pid: 47163
time_since_restore: 0.10490107536315918
time_this_iter_s: 0.10490107536315918
time_total_s: 0.10490107536315918
timestamp: 1658500271
timesteps_since_restore: 0
training_iteration: 1
trial_id: ed2322be
warmup_time: 0.0032410621643066406
Result for objective_ed217cf2:
date: 2022-07-22_15-31-11
done: false
experiment_id: 52186ede891e429aac44318036e7a7bb
hostname: Kais-MacBook-Pro.local
iterations: 0
iterations_since_restore: 1
mean_loss: 7.939249801790311
neg_mean_loss: -7.939249801790311
node_ip: 127.0.0.1
pid: 47162
time_since_restore: 0.10419487953186035
time_this_iter_s: 0.10419487953186035
time_total_s: 0.10419487953186035
timestamp: 1658500271
timesteps_since_restore: 0
training_iteration: 1
trial_id: ed217cf2
warmup_time: 0.0031850337982177734
Result for objective_eb74f122:
date: 2022-07-22_15-31-13
done: false
experiment_id: 0ed1b6ba6d99477dba0632102d1bc531
hostname: Kais-MacBook-Pro.local
iterations: 46
iterations_since_restore: 47
mean_loss: 1.9857142857142855
neg_mean_loss: -1.9857142857142855
node_ip: 127.0.0.1
pid: 47156
time_since_restore: 5.155240058898926
time_this_iter_s: 0.11003398895263672
time_total_s: 5.155240058898926
timestamp: 1658500273
timesteps_since_restore: 0
training_iteration: 47
trial_id: eb74f122
warmup_time: 0.002730131149291992
Result for objective_ed2010ec:
date: 2022-07-22_15-31-16
done: false
experiment_id: 3acf6a8ccf8442a7adcf98cc92362216
hostname: Kais-MacBook-Pro.local
iterations: 47
iterations_since_restore: 48
mean_loss: 0.7050505050505051
neg_mean_loss: -0.7050505050505051
node_ip: 127.0.0.1
pid: 47161
time_since_restore: 5.1636271476745605
time_this_iter_s: 0.1071469783782959
time_total_s: 5.1636271476745605
timestamp: 1658500276
timesteps_since_restore: 0
training_iteration: 48
trial_id: ed2010ec
warmup_time: 0.0034351348876953125
Result for objective_ed2322be:
date: 2022-07-22_15-31-16
done: false
experiment_id: e95895ab00b54841933d324c3de8f58e
hostname: Kais-MacBook-Pro.local
iterations: 47
iterations_since_restore: 48
mean_loss: 2.1909053484385796
neg_mean_loss: -2.1909053484385796
node_ip: 127.0.0.1
pid: 47163
time_since_restore: 5.168597936630249
time_this_iter_s: 0.10674691200256348
time_total_s: 5.168597936630249
timestamp: 1658500276
timesteps_since_restore: 0
training_iteration: 48
trial_id: ed2322be
warmup_time: 0.0032410621643066406
Result for objective_ed217cf2:
date: 2022-07-22_15-31-16
done: false
experiment_id: 52186ede891e429aac44318036e7a7bb
hostname: Kais-MacBook-Pro.local
iterations: 47
iterations_since_restore: 48
mean_loss: -1.9004596703789314
neg_mean_loss: 1.9004596703789314
node_ip: 127.0.0.1
pid: 47162
time_since_restore: 5.14047384262085
time_this_iter_s: 0.10724306106567383
time_total_s: 5.14047384262085
timestamp: 1658500276
timesteps_since_restore: 0
training_iteration: 48
trial_id: ed217cf2
warmup_time: 0.0031850337982177734
Result for objective_eb74f122:
date: 2022-07-22_15-31-18
done: false
experiment_id: 0ed1b6ba6d99477dba0632102d1bc531
hostname: Kais-MacBook-Pro.local
iterations: 93
iterations_since_restore: 94
mean_loss: 1.170873786407767
neg_mean_loss: -1.170873786407767
node_ip: 127.0.0.1
pid: 47156
time_since_restore: 10.253305196762085
time_this_iter_s: 0.10791301727294922
time_total_s: 10.253305196762085
timestamp: 1658500278
timesteps_since_restore: 0
training_iteration: 94
trial_id: eb74f122
warmup_time: 0.002730131149291992
Result for objective_eb74f122:
date: 2022-07-22_15-31-19
done: true
experiment_id: 0ed1b6ba6d99477dba0632102d1bc531
experiment_tag: 1_activation=relu,height=2.0000,steps=100,width=1.0000
hostname: Kais-MacBook-Pro.local
iterations: 99
iterations_since_restore: 100
mean_loss: 1.1174311926605505
neg_mean_loss: -1.1174311926605505
node_ip: 127.0.0.1
pid: 47156
time_since_restore: 10.900829076766968
time_this_iter_s: 0.10532379150390625
time_total_s: 10.900829076766968
timestamp: 1658500279
timesteps_since_restore: 0
training_iteration: 100
trial_id: eb74f122
warmup_time: 0.002730131149291992
Result for objective_ed217cf2:
date: 2022-07-22_15-31-21
done: false
experiment_id: 52186ede891e429aac44318036e7a7bb
hostname: Kais-MacBook-Pro.local
iterations: 91
iterations_since_restore: 92
mean_loss: -1.9773161428398818
neg_mean_loss: 1.9773161428398818
node_ip: 127.0.0.1
pid: 47162
time_since_restore: 9.86834192276001
time_this_iter_s: 0.10606908798217773
time_total_s: 9.86834192276001
timestamp: 1658500281
timesteps_since_restore: 0
training_iteration: 92
trial_id: ed217cf2
warmup_time: 0.0031850337982177734
Result for objective_ed2322be:
date: 2022-07-22_15-31-21
done: false
experiment_id: e95895ab00b54841933d324c3de8f58e
hostname: Kais-MacBook-Pro.local
iterations: 91
iterations_since_restore: 92
mean_loss: 2.0974537058269864
neg_mean_loss: -2.0974537058269864
node_ip: 127.0.0.1
pid: 47163
time_since_restore: 9.877221822738647
time_this_iter_s: 0.10554194450378418
time_total_s: 9.877221822738647
timestamp: 1658500281
timesteps_since_restore: 0
training_iteration: 92
trial_id: ed2322be
warmup_time: 0.0032410621643066406
Result for objective_ed2010ec:
date: 2022-07-22_15-31-21
done: false
experiment_id: 3acf6a8ccf8442a7adcf98cc92362216
hostname: Kais-MacBook-Pro.local
iterations: 92
iterations_since_restore: 93
mean_loss: 0.46455026455026455
neg_mean_loss: -0.46455026455026455
node_ip: 127.0.0.1
pid: 47161
time_since_restore: 10.010878086090088
time_this_iter_s: 0.12952017784118652
time_total_s: 10.010878086090088
timestamp: 1658500281
timesteps_since_restore: 0
training_iteration: 93
trial_id: ed2010ec
warmup_time: 0.0034351348876953125
Result for objective_f3a0bef8:
date: 2022-07-22_15-31-22
done: false
experiment_id: 7bbba7b85dbc4029bc8b22b7866d091f
hostname: Kais-MacBook-Pro.local
iterations: 0
iterations_since_restore: 1
mean_loss: 9.256084922802092
neg_mean_loss: -9.256084922802092
node_ip: 127.0.0.1
pid: 47180
time_since_restore: 0.10452008247375488
time_this_iter_s: 0.10452008247375488
time_total_s: 0.10452008247375488
timestamp: 1658500282
timesteps_since_restore: 0
training_iteration: 1
trial_id: f3a0bef8
warmup_time: 0.003498077392578125
Result for objective_ed2010ec:
date: 2022-07-22_15-31-22
done: true
experiment_id: 3acf6a8ccf8442a7adcf98cc92362216
experiment_tag: 2_activation=tanh,height=2.0000,steps=100,width=4.0000
hostname: Kais-MacBook-Pro.local
iterations: 99
iterations_since_restore: 100
mean_loss: 0.44630541871921187
neg_mean_loss: -0.44630541871921187
node_ip: 127.0.0.1
pid: 47161
time_since_restore: 11.509758949279785
time_this_iter_s: 0.10628509521484375
time_total_s: 11.509758949279785
timestamp: 1658500282
timesteps_since_restore: 0
training_iteration: 100
trial_id: ed2010ec
warmup_time: 0.0034351348876953125
Result for objective_ed217cf2:
date: 2022-07-22_15-31-22
done: true
experiment_id: 52186ede891e429aac44318036e7a7bb
experiment_tag: 3_activation=tanh,height=-20.6075,steps=100,width=13.0610
hostname: Kais-MacBook-Pro.local
iterations: 99
iterations_since_restore: 100
mean_loss: -1.9840065470391304
neg_mean_loss: 1.9840065470391304
node_ip: 127.0.0.1
pid: 47162
time_since_restore: 11.562283754348755
time_this_iter_s: 0.10557794570922852
time_total_s: 11.562283754348755
timestamp: 1658500282
timesteps_since_restore: 0
training_iteration: 100
trial_id: ed217cf2
warmup_time: 0.0031850337982177734
Result for objective_ed2322be:
date: 2022-07-22_15-31-22
done: true
experiment_id: e95895ab00b54841933d324c3de8f58e
experiment_tag: 4_activation=tanh,height=19.9564,steps=100,width=10.6836
hostname: Kais-MacBook-Pro.local
iterations: 99
iterations_since_restore: 100
mean_loss: 2.0893035832616653
neg_mean_loss: -2.0893035832616653
node_ip: 127.0.0.1
pid: 47163
time_since_restore: 11.605261087417603
time_this_iter_s: 0.10673737525939941
time_total_s: 11.605261087417603
timestamp: 1658500282
timesteps_since_restore: 0
training_iteration: 100
trial_id: ed2322be
warmup_time: 0.0032410621643066406
Result for objective_f59fe9d6:
date: 2022-07-22_15-31-25
done: false
experiment_id: efbda212c15c4bd38cfc5f39dfae8b73
hostname: Kais-MacBook-Pro.local
iterations: 0
iterations_since_restore: 1
mean_loss: 7.250423019956081
neg_mean_loss: -7.250423019956081
node_ip: 127.0.0.1
pid: 47185
time_since_restore: 0.10512709617614746
time_this_iter_s: 0.10512709617614746
time_total_s: 0.10512709617614746
timestamp: 1658500285
timesteps_since_restore: 0
training_iteration: 1
trial_id: f59fe9d6
warmup_time: 0.003314971923828125
Result for objective_f5b1ec08:
date: 2022-07-22_15-31-25
done: false
experiment_id: dadb542868ba4b10adf1ef161c75ea17
hostname: Kais-MacBook-Pro.local
iterations: 0
iterations_since_restore: 1
mean_loss: 10.41409792482367
neg_mean_loss: -10.41409792482367
node_ip: 127.0.0.1
pid: 47189
time_since_restore: 0.10109281539916992
time_this_iter_s: 0.10109281539916992
time_total_s: 0.10109281539916992
timestamp: 1658500285
timesteps_since_restore: 0
training_iteration: 1
trial_id: f5b1ec08
warmup_time: 0.0031630992889404297
Result for objective_f5aedf9a:
date: 2022-07-22_15-31-25
done: false
experiment_id: 9f7847b7440648cb86e73bf1be0ccc05
hostname: Kais-MacBook-Pro.local
iterations: 0
iterations_since_restore: 1
mean_loss: 14.870604096990785
neg_mean_loss: -14.870604096990785
node_ip: 127.0.0.1
pid: 47188
time_since_restore: 0.10486412048339844
time_this_iter_s: 0.10486412048339844
time_total_s: 0.10486412048339844
timestamp: 1658500285
timesteps_since_restore: 0
training_iteration: 1
trial_id: f5aedf9a
warmup_time: 0.002830028533935547
Result for objective_f3a0bef8:
date: 2022-07-22_15-31-27
done: false
experiment_id: 7bbba7b85dbc4029bc8b22b7866d091f
hostname: Kais-MacBook-Pro.local
iterations: 47
iterations_since_restore: 48
mean_loss: 0.12364690126601663
neg_mean_loss: -0.12364690126601663
node_ip: 127.0.0.1
pid: 47180
time_since_restore: 5.149861097335815
time_this_iter_s: 0.1075279712677002
time_total_s: 5.149861097335815
timestamp: 1658500287
timesteps_since_restore: 0
training_iteration: 48
trial_id: f3a0bef8
warmup_time: 0.003498077392578125
Result for objective_f59fe9d6:
date: 2022-07-22_15-31-30
done: false
experiment_id: efbda212c15c4bd38cfc5f39dfae8b73
hostname: Kais-MacBook-Pro.local
iterations: 47
iterations_since_restore: 48
mean_loss: -2.3825537636804834
neg_mean_loss: 2.3825537636804834
node_ip: 127.0.0.1
pid: 47185
time_since_restore: 5.170727014541626
time_this_iter_s: 0.10740494728088379
time_total_s: 5.170727014541626
timestamp: 1658500290
timesteps_since_restore: 0
training_iteration: 48
trial_id: f59fe9d6
warmup_time: 0.003314971923828125
Result for objective_f5b1ec08:
date: 2022-07-22_15-31-30
done: false
experiment_id: dadb542868ba4b10adf1ef161c75ea17
hostname: Kais-MacBook-Pro.local
iterations: 47
iterations_since_restore: 48
mean_loss: 0.5431509247331814
neg_mean_loss: -0.5431509247331814
node_ip: 127.0.0.1
pid: 47189
time_since_restore: 5.153015613555908
time_this_iter_s: 0.10737276077270508
time_total_s: 5.153015613555908
timestamp: 1658500290
timesteps_since_restore: 0
training_iteration: 48
trial_id: f5b1ec08
warmup_time: 0.0031630992889404297
Result for objective_f5aedf9a:
date: 2022-07-22_15-31-30
done: false
experiment_id: 9f7847b7440648cb86e73bf1be0ccc05
hostname: Kais-MacBook-Pro.local
iterations: 47
iterations_since_restore: 48
mean_loss: 4.977264708542528
neg_mean_loss: -4.977264708542528
node_ip: 127.0.0.1
pid: 47188
time_since_restore: 5.183044195175171
time_this_iter_s: 0.10844588279724121
time_total_s: 5.183044195175171
timestamp: 1658500290
timesteps_since_restore: 0
training_iteration: 48
trial_id: f5aedf9a
warmup_time: 0.002830028533935547
Result for objective_f3a0bef8:
date: 2022-07-22_15-31-32
done: false
experiment_id: 7bbba7b85dbc4029bc8b22b7866d091f
hostname: Kais-MacBook-Pro.local
iterations: 94
iterations_since_restore: 95
mean_loss: -0.29046425326874115
neg_mean_loss: 0.29046425326874115
node_ip: 127.0.0.1
pid: 47180
time_since_restore: 10.200733184814453
time_this_iter_s: 0.10860228538513184
time_total_s: 10.200733184814453
timestamp: 1658500292
timesteps_since_restore: 0
training_iteration: 95
trial_id: f3a0bef8
warmup_time: 0.003498077392578125
Result for objective_f3a0bef8:
date: 2022-07-22_15-31-32
done: true
experiment_id: 7bbba7b85dbc4029bc8b22b7866d091f
experiment_tag: 5_activation=tanh,height=-7.4392,steps=100,width=2.2397
hostname: Kais-MacBook-Pro.local
iterations: 99
iterations_since_restore: 100
mean_loss: -0.3123775218508783
neg_mean_loss: 0.3123775218508783
node_ip: 127.0.0.1
pid: 47180
time_since_restore: 10.737780094146729
time_this_iter_s: 0.10722112655639648
time_total_s: 10.737780094146729
timestamp: 1658500292
timesteps_since_restore: 0
training_iteration: 100
trial_id: f3a0bef8
warmup_time: 0.003498077392578125
Result for objective_fb926d32:
date: 2022-07-22_15-31-35
done: false
experiment_id: c6af4463441e4a3a8ca1298a043e6151
hostname: Kais-MacBook-Pro.local
iterations: 0
iterations_since_restore: 1
mean_loss: 14.477795797697073
neg_mean_loss: -14.477795797697073
node_ip: 127.0.0.1
pid: 47205
time_since_restore: 0.10373091697692871
time_this_iter_s: 0.10373091697692871
time_total_s: 0.10373091697692871
timestamp: 1658500295
timesteps_since_restore: 0
training_iteration: 1
trial_id: fb926d32
warmup_time: 0.0029900074005126953
Result for objective_f59fe9d6:
date: 2022-07-22_15-31-35
done: false
experiment_id: efbda212c15c4bd38cfc5f39dfae8b73
hostname: Kais-MacBook-Pro.local
iterations: 94
iterations_since_restore: 95
mean_loss: -2.5626347652141552
neg_mean_loss: 2.5626347652141552
node_ip: 127.0.0.1
pid: 47185
time_since_restore: 10.179347038269043
time_this_iter_s: 0.1074531078338623
time_total_s: 10.179347038269043
timestamp: 1658500295
timesteps_since_restore: 0
training_iteration: 95
trial_id: f59fe9d6
warmup_time: 0.003314971923828125
Result for objective_f5b1ec08:
date: 2022-07-22_15-31-35
done: false
experiment_id: dadb542868ba4b10adf1ef161c75ea17
hostname: Kais-MacBook-Pro.local
iterations: 94
iterations_since_restore: 95
mean_loss: 0.4790434958168009
neg_mean_loss: -0.4790434958168009
node_ip: 127.0.0.1
pid: 47189
time_since_restore: 10.170033931732178
time_this_iter_s: 0.10643315315246582
time_total_s: 10.170033931732178
timestamp: 1658500295
timesteps_since_restore: 0
training_iteration: 95
trial_id: f5b1ec08
warmup_time: 0.0031630992889404297
Result for objective_f5aedf9a:
date: 2022-07-22_15-31-35
done: false
experiment_id: 9f7847b7440648cb86e73bf1be0ccc05
hostname: Kais-MacBook-Pro.local
iterations: 94
iterations_since_restore: 95
mean_loss: 4.924220339829169
neg_mean_loss: -4.924220339829169
node_ip: 127.0.0.1
pid: 47188
time_since_restore: 10.189186096191406
time_this_iter_s: 0.1078641414642334
time_total_s: 10.189186096191406
timestamp: 1658500295
timesteps_since_restore: 0
training_iteration: 95
trial_id: f5aedf9a
warmup_time: 0.002830028533935547
Result for objective_f59fe9d6:
date: 2022-07-22_15-31-36
done: true
experiment_id: efbda212c15c4bd38cfc5f39dfae8b73
experiment_tag: 6_activation=tanh,height=-27.4958,steps=100,width=5.5843
hostname: Kais-MacBook-Pro.local
iterations: 99
iterations_since_restore: 100
mean_loss: -2.5719085451008423
neg_mean_loss: 2.5719085451008423
node_ip: 127.0.0.1
pid: 47185
time_since_restore: 10.714513063430786
time_this_iter_s: 0.1071622371673584
time_total_s: 10.714513063430786
timestamp: 1658500296
timesteps_since_restore: 0
training_iteration: 100
trial_id: f59fe9d6
warmup_time: 0.003314971923828125
Result for objective_f5b1ec08:
date: 2022-07-22_15-31-36
done: true
experiment_id: dadb542868ba4b10adf1ef161c75ea17
experiment_tag: 8_activation=tanh,height=4.1410,steps=100,width=16.2739
hostname: Kais-MacBook-Pro.local
iterations: 99
iterations_since_restore: 100
mean_loss: 0.4757836498809659
neg_mean_loss: -0.4757836498809659
node_ip: 127.0.0.1
pid: 47189
time_since_restore: 10.703420877456665
time_this_iter_s: 0.10684394836425781
time_total_s: 10.703420877456665
timestamp: 1658500296
timesteps_since_restore: 0
training_iteration: 100
trial_id: f5b1ec08
warmup_time: 0.0031630992889404297
Result for objective_f5aedf9a:
date: 2022-07-22_15-31-36
done: true
experiment_id: 9f7847b7440648cb86e73bf1be0ccc05
experiment_tag: 7_activation=tanh,height=48.7060,steps=100,width=19.7352
hostname: Kais-MacBook-Pro.local
iterations: 99
iterations_since_restore: 100
mean_loss: 4.9215262379377105
neg_mean_loss: -4.9215262379377105
node_ip: 127.0.0.1
pid: 47188
time_since_restore: 10.734119176864624
time_this_iter_s: 0.11568498611450195
time_total_s: 10.734119176864624
timestamp: 1658500296
timesteps_since_restore: 0
training_iteration: 100
trial_id: f5aedf9a
warmup_time: 0.002830028533935547
Result for objective_fd91e28e:
date: 2022-07-22_15-31-38
done: false
experiment_id: 5c3693eeb55b476088ce1de9127c5a39
hostname: Kais-MacBook-Pro.local
iterations: 0
iterations_since_restore: 1
mean_loss: 9.70376987633604
neg_mean_loss: -9.70376987633604
node_ip: 127.0.0.1
pid: 47214
time_since_restore: 0.10451984405517578
time_this_iter_s: 0.10451984405517578
time_total_s: 0.10451984405517578
timestamp: 1658500298
timesteps_since_restore: 0
training_iteration: 1
trial_id: fd91e28e
warmup_time: 0.00302886962890625
Result for objective_fb926d32:
date: 2022-07-22_15-31-40
done: false
experiment_id: c6af4463441e4a3a8ca1298a043e6151
hostname: Kais-MacBook-Pro.local
iterations: 25
iterations_since_restore: 26
mean_loss: 4.859752718513368
neg_mean_loss: -4.859752718513368
node_ip: 127.0.0.1
pid: 47205
time_since_restore: 5.151448011398315
time_this_iter_s: 0.11450004577636719
time_total_s: 5.151448011398315
timestamp: 1658500300
timesteps_since_restore: 0
training_iteration: 26
trial_id: fb926d32
warmup_time: 0.0029900074005126953
Result for objective_fd91e28e:
date: 2022-07-22_15-31-43
done: false
experiment_id: 5c3693eeb55b476088ce1de9127c5a39
hostname: Kais-MacBook-Pro.local
iterations: 46
iterations_since_restore: 47
mean_loss: -0.11565561363589152
neg_mean_loss: 0.11565561363589152
node_ip: 127.0.0.1
pid: 47214
time_since_restore: 5.126538991928101
time_this_iter_s: 0.10815834999084473
time_total_s: 5.126538991928101
timestamp: 1658500303
timesteps_since_restore: 0
training_iteration: 47
trial_id: fd91e28e
warmup_time: 0.00302886962890625
Result for objective_fb926d32:
date: 2022-07-22_15-31-45
done: false
experiment_id: c6af4463441e4a3a8ca1298a043e6151
hostname: Kais-MacBook-Pro.local
iterations: 72
iterations_since_restore: 73
mean_loss: 4.613811037170093
neg_mean_loss: -4.613811037170093
node_ip: 127.0.0.1
pid: 47205
time_since_restore: 10.208579063415527
time_this_iter_s: 0.10763001441955566
time_total_s: 10.208579063415527
timestamp: 1658500305
timesteps_since_restore: 0
training_iteration: 73
trial_id: fb926d32
warmup_time: 0.0029900074005126953
Result for objective_fb926d32:
date: 2022-07-22_15-31-48
done: true
experiment_id: c6af4463441e4a3a8ca1298a043e6151
experiment_tag: 9_activation=tanh,height=44.7780,steps=100,width=10.0724
hostname: Kais-MacBook-Pro.local
iterations: 99
iterations_since_restore: 100
mean_loss: 4.577084283144497
neg_mean_loss: -4.577084283144497
node_ip: 127.0.0.1
pid: 47205
time_since_restore: 13.110869884490967
time_this_iter_s: 0.10806989669799805
time_total_s: 13.110869884490967
timestamp: 1658500308
timesteps_since_restore: 0
training_iteration: 100
trial_id: fb926d32
warmup_time: 0.0029900074005126953
Result for objective_fd91e28e:
date: 2022-07-22_15-31-48
done: false
experiment_id: 5c3693eeb55b476088ce1de9127c5a39
hostname: Kais-MacBook-Pro.local
iterations: 93
iterations_since_restore: 94
mean_loss: -0.20609110794676003
neg_mean_loss: 0.20609110794676003
node_ip: 127.0.0.1
pid: 47214
time_since_restore: 10.14166784286499
time_this_iter_s: 0.10436320304870605
time_total_s: 10.14166784286499
timestamp: 1658500308
timesteps_since_restore: 0
training_iteration: 94
trial_id: fd91e28e
warmup_time: 0.00302886962890625
Result for objective_fd91e28e:
date: 2022-07-22_15-31-49
done: true
experiment_id: 5c3693eeb55b476088ce1de9127c5a39
experiment_tag: 10_activation=relu,height=-2.9623,steps=100,width=11.8215
hostname: Kais-MacBook-Pro.local
iterations: 99
iterations_since_restore: 100
mean_loss: -0.21150779503682235
neg_mean_loss: 0.21150779503682235
node_ip: 127.0.0.1
pid: 47214
time_since_restore: 10.793406963348389
time_this_iter_s: 0.10776925086975098
time_total_s: 10.793406963348389
timestamp: 1658500309
timesteps_since_restore: 0
training_iteration: 100
trial_id: fd91e28e
warmup_time: 0.00302886962890625
Here are the hyperparamters found to minimize the mean loss of the defined objective.
print("Best hyperparameters found were: ", results.get_best_result().config)
Best hyperparameters found were: {'steps': 100, 'width': 5.584304853357766, 'height': -27.49576980043919, 'activation': 'tanh'}
Conditional search spaces#
Sometimes we may want to build a more complicated search space that has conditional dependencies on other hyperparameters. In this case, we pass a nested dictionary to objective_two
, which has been slightly adjusted from objective
to deal with the conditional search space.
def evaluation_fn(step, width, height, mult=1):
return (0.1 + width * step / 100) ** (-1) + height * 0.1 * mult
def objective_two(config):
width, height = config["width"], config["height"]
sub_dict = config["activation"]
mult = sub_dict.get("mult", 1)
for step in range(config["steps"]):
intermediate_score = evaluation_fn(step, width, height, mult)
train.report({"iterations": step, "mean_loss": intermediate_score})
time.sleep(0.1)
conditional_space = {
"activation": hp.choice(
"activation",
[
{"activation": "relu", "mult": hp.uniform("mult", 1, 2)},
{"activation": "tanh"},
],
),
"width": hp.uniform("width", 0, 20),
"height": hp.uniform("height", -100, 100),
"steps": 100,
}
Now we the define the search algorithm built from HyperOptSearch
constrained by ConcurrencyLimiter
. When the hyperparameter search space is conditional, we pass it (conditional_space
) into HyperOptSearch
.
algo = HyperOptSearch(space=conditional_space, metric="mean_loss", mode="min")
algo = ConcurrencyLimiter(algo, max_concurrent=4)
Now we run the experiment, this time with an empty config
because we instead provided space
to the HyperOptSearch
search_alg
.
tuner = tune.Tuner(
objective_two,
tune_config=tune.TuneConfig(
metric="mean_loss",
mode="min",
search_alg=algo,
num_samples=num_samples,
),
)
results = tuner.fit()
Current time: 2022-07-22 15:32:33 (running for 00:00:44.21)
Memory usage on this node: 10.7/16.0 GiB
Using FIFO scheduling algorithm.
Resources requested: 0/16 CPUs, 0/0 GPUs, 0.0/5.29 GiB heap, 0.0/2.0 GiB objects
Current best trial: 0de7d38c with mean_loss=-9.200364093875208 and parameters={'activation': {'activation': 'relu', 'mult': 1.3982639549501585}, 'height': -66.3136247260571, 'steps': 100, 'width': 13.922128223483856}
Result logdir: /Users/kai/ray_results/objective_two_2022-07-22_15-31-49
Number of trials: 10/10 (10 TERMINATED)
Trial name | status | loc | activation/activa... | activation/mult | height | steps | width | loss | iter | total time (s) | iterations | neg_mean_loss |
---|---|---|---|---|---|---|---|---|---|---|---|---|
objective_two_05a0ad52 | TERMINATED | 127.0.0.1:47229 | tanh | -63.0091 | 100 | 10.1954 | -6.20281 | 100 | 10.8547 | 99 | 6.20281 | |
objective_two_075f0d78 | TERMINATED | 127.0.0.1:47236 | relu | 1.22098 | 46.4977 | 100 | 13.6093 | 5.75095 | 100 | 12.0174 | 99 | -5.75095 |
objective_two_07617f54 | TERMINATED | 127.0.0.1:47237 | tanh | -41.2706 | 100 | 7.34134 | -3.99133 | 100 | 11.8677 | 99 | 3.99133 | |
objective_two_07636cd8 | TERMINATED | 127.0.0.1:47238 | tanh | 49.0313 | 100 | 0.828826 | 5.98945 | 100 | 12.0258 | 99 | -5.98945 | |
objective_two_0de7d38c | TERMINATED | 127.0.0.1:47256 | relu | 1.39826 | -66.3136 | 100 | 13.9221 | -9.20036 | 100 | 10.7072 | 99 | 9.20036 |
objective_two_100ebe3c | TERMINATED | 127.0.0.1:47265 | tanh | -38.8555 | 100 | 15.9966 | -3.82281 | 100 | 10.6571 | 99 | 3.82281 | |
objective_two_101e702a | TERMINATED | 127.0.0.1:47268 | relu | 1.51022 | 5.84901 | 100 | 0.431039 | 2.78184 | 100 | 10.7202 | 99 | -2.78184 |
objective_two_1022212a | TERMINATED | 127.0.0.1:47269 | relu | 1.32257 | 71.2885 | 100 | 11.4466 | 9.51591 | 100 | 10.7072 | 99 | -9.51591 |
objective_two_15fbf8dc | TERMINATED | 127.0.0.1:47288 | relu | 1.22166 | -32.1584 | 100 | 9.43222 | -3.82272 | 100 | 10.5991 | 99 | 3.82272 |
objective_two_18090732 | TERMINATED | 127.0.0.1:47302 | tanh | 52.7613 | 100 | 16.7268 | 5.33616 | 100 | 10.6336 | 99 | -5.33616 |
Result for objective_two_05a0ad52:
date: 2022-07-22_15-31-52
done: false
experiment_id: af7041e0b2c947aa8a30c2e30f94ba83
hostname: Kais-MacBook-Pro.local
iterations: 0
iterations_since_restore: 1
mean_loss: 3.699090470918877
neg_mean_loss: -3.699090470918877
node_ip: 127.0.0.1
pid: 47229
time_since_restore: 0.00011491775512695312
time_this_iter_s: 0.00011491775512695312
time_total_s: 0.00011491775512695312
timestamp: 1658500312
timesteps_since_restore: 0
training_iteration: 1
trial_id: 05a0ad52
warmup_time: 0.0027589797973632812
Result for objective_two_07636cd8:
date: 2022-07-22_15-31-55
done: false
experiment_id: 5c9d75b036ae410b9fdea303f14fe4cd
hostname: Kais-MacBook-Pro.local
iterations: 0
iterations_since_restore: 1
mean_loss: 14.903126957374846
neg_mean_loss: -14.903126957374846
node_ip: 127.0.0.1
pid: 47238
time_since_restore: 0.00011110305786132812
time_this_iter_s: 0.00011110305786132812
time_total_s: 0.00011110305786132812
timestamp: 1658500315
timesteps_since_restore: 0
training_iteration: 1
trial_id: 07636cd8
warmup_time: 0.0037419795989990234
Result for objective_two_07617f54:
date: 2022-07-22_15-31-55
done: false
experiment_id: 32155cb3b7f04dc3b7b5b679eecd8c46
hostname: Kais-MacBook-Pro.local
iterations: 0
iterations_since_restore: 1
mean_loss: 5.872941741395985
neg_mean_loss: -5.872941741395985
node_ip: 127.0.0.1
pid: 47237
time_since_restore: 0.00015211105346679688
time_this_iter_s: 0.00015211105346679688
time_total_s: 0.00015211105346679688
timestamp: 1658500315
timesteps_since_restore: 0
training_iteration: 1
trial_id: 07617f54
warmup_time: 0.00436091423034668
Result for objective_two_075f0d78:
date: 2022-07-22_15-31-55
done: false
experiment_id: 5a46a57ef1164628bac1618e39078e0e
hostname: Kais-MacBook-Pro.local
iterations: 0
iterations_since_restore: 1
mean_loss: 15.677277832165048
neg_mean_loss: -15.677277832165048
node_ip: 127.0.0.1
pid: 47236
time_since_restore: 0.00011396408081054688
time_this_iter_s: 0.00011396408081054688
time_total_s: 0.00011396408081054688
timestamp: 1658500315
timesteps_since_restore: 0
training_iteration: 1
trial_id: 075f0d78
warmup_time: 0.0035758018493652344
Result for objective_two_05a0ad52:
date: 2022-07-22_15-31-57
done: false
experiment_id: af7041e0b2c947aa8a30c2e30f94ba83
hostname: Kais-MacBook-Pro.local
iterations: 45
iterations_since_restore: 46
mean_loss: -6.087595964816368
neg_mean_loss: 6.087595964816368
node_ip: 127.0.0.1
pid: 47229
time_since_restore: 5.055715799331665
time_this_iter_s: 0.10677886009216309
time_total_s: 5.055715799331665
timestamp: 1658500317
timesteps_since_restore: 0
training_iteration: 46
trial_id: 05a0ad52
warmup_time: 0.0027589797973632812
Result for objective_two_07617f54:
date: 2022-07-22_15-32-00
done: false
experiment_id: 32155cb3b7f04dc3b7b5b679eecd8c46
hostname: Kais-MacBook-Pro.local
iterations: 47
iterations_since_restore: 48
mean_loss: -3.8454022145530584
neg_mean_loss: 3.8454022145530584
node_ip: 127.0.0.1
pid: 47237
time_since_restore: 5.048717021942139
time_this_iter_s: 0.10686898231506348
time_total_s: 5.048717021942139
timestamp: 1658500320
timesteps_since_restore: 0
training_iteration: 48
trial_id: 07617f54
warmup_time: 0.00436091423034668
Result for objective_two_07636cd8:
date: 2022-07-22_15-32-00
done: false
experiment_id: 5c9d75b036ae410b9fdea303f14fe4cd
hostname: Kais-MacBook-Pro.local
iterations: 47
iterations_since_restore: 48
mean_loss: 6.9458266379188185
neg_mean_loss: -6.9458266379188185
node_ip: 127.0.0.1
pid: 47238
time_since_restore: 5.097726821899414
time_this_iter_s: 0.1087799072265625
time_total_s: 5.097726821899414
timestamp: 1658500320
timesteps_since_restore: 0
training_iteration: 48
trial_id: 07636cd8
warmup_time: 0.0037419795989990234
Result for objective_two_075f0d78:
date: 2022-07-22_15-32-00
done: false
experiment_id: 5a46a57ef1164628bac1618e39078e0e
hostname: Kais-MacBook-Pro.local
iterations: 47
iterations_since_restore: 48
mean_loss: 5.83121027007688
neg_mean_loss: -5.83121027007688
node_ip: 127.0.0.1
pid: 47236
time_since_restore: 5.118211269378662
time_this_iter_s: 0.10918712615966797
time_total_s: 5.118211269378662
timestamp: 1658500320
timesteps_since_restore: 0
training_iteration: 48
trial_id: 075f0d78
warmup_time: 0.0035758018493652344
Result for objective_two_05a0ad52:
date: 2022-07-22_15-32-02
done: false
experiment_id: af7041e0b2c947aa8a30c2e30f94ba83
hostname: Kais-MacBook-Pro.local
iterations: 92
iterations_since_restore: 93
mean_loss: -6.195421815991769
neg_mean_loss: 6.195421815991769
node_ip: 127.0.0.1
pid: 47229
time_since_restore: 10.10265588760376
time_this_iter_s: 0.10532593727111816
time_total_s: 10.10265588760376
timestamp: 1658500322
timesteps_since_restore: 0
training_iteration: 93
trial_id: 05a0ad52
warmup_time: 0.0027589797973632812
Result for objective_two_05a0ad52:
date: 2022-07-22_15-32-03
done: true
experiment_id: af7041e0b2c947aa8a30c2e30f94ba83
experiment_tag: 1_activation=tanh,height=-63.0091,steps=100,width=10.1954
hostname: Kais-MacBook-Pro.local
iterations: 99
iterations_since_restore: 100
mean_loss: -6.202807371456877
neg_mean_loss: 6.202807371456877
node_ip: 127.0.0.1
pid: 47229
time_since_restore: 10.854680061340332
time_this_iter_s: 0.10699224472045898
time_total_s: 10.854680061340332
timestamp: 1658500323
timesteps_since_restore: 0
training_iteration: 100
trial_id: 05a0ad52
warmup_time: 0.0027589797973632812
Result for objective_two_075f0d78:
date: 2022-07-22_15-32-04
done: false
experiment_id: 5a46a57ef1164628bac1618e39078e0e
hostname: Kais-MacBook-Pro.local
iterations: 91
iterations_since_restore: 92
mean_loss: 5.757377572321986
neg_mean_loss: -5.757377572321986
node_ip: 127.0.0.1
pid: 47236
time_since_restore: 9.820771932601929
time_this_iter_s: 0.10582685470581055
time_total_s: 9.820771932601929
timestamp: 1658500324
timesteps_since_restore: 0
training_iteration: 92
trial_id: 075f0d78
warmup_time: 0.0035758018493652344
Result for objective_two_07617f54:
date: 2022-07-22_15-32-04
done: false
experiment_id: 32155cb3b7f04dc3b7b5b679eecd8c46
hostname: Kais-MacBook-Pro.local
iterations: 92
iterations_since_restore: 93
mean_loss: -3.981158750752472
neg_mean_loss: 3.981158750752472
node_ip: 127.0.0.1
pid: 47237
time_since_restore: 9.865068197250366
time_this_iter_s: 0.1065821647644043
time_total_s: 9.865068197250366
timestamp: 1658500324
timesteps_since_restore: 0
training_iteration: 93
trial_id: 07617f54
warmup_time: 0.00436091423034668
Result for objective_two_0de7d38c:
date: 2022-07-22_15-32-06
done: false
experiment_id: 81d62307312a447e97c5d1f1cdad2687
hostname: Kais-MacBook-Pro.local
iterations: 0
iterations_since_restore: 1
mean_loss: 0.7276048823462773
neg_mean_loss: -0.7276048823462773
node_ip: 127.0.0.1
pid: 47256
time_since_restore: 0.00012803077697753906
time_this_iter_s: 0.00012803077697753906
time_total_s: 0.00012803077697753906
timestamp: 1658500326
timesteps_since_restore: 0
training_iteration: 1
trial_id: 0de7d38c
warmup_time: 0.0027358531951904297
Result for objective_two_07636cd8:
date: 2022-07-22_15-32-04
done: false
experiment_id: 5c9d75b036ae410b9fdea303f14fe4cd
hostname: Kais-MacBook-Pro.local
iterations: 91
iterations_since_restore: 92
mean_loss: 6.073769581173668
neg_mean_loss: -6.073769581173668
node_ip: 127.0.0.1
pid: 47238
time_since_restore: 9.813458919525146
time_this_iter_s: 0.10477709770202637
time_total_s: 9.813458919525146
timestamp: 1658500324
timesteps_since_restore: 0
training_iteration: 92
trial_id: 07636cd8
warmup_time: 0.0037419795989990234
Result for objective_two_07617f54:
date: 2022-07-22_15-32-06
done: true
experiment_id: 32155cb3b7f04dc3b7b5b679eecd8c46
experiment_tag: 3_activation=tanh,height=-41.2706,steps=100,width=7.3413
hostname: Kais-MacBook-Pro.local
iterations: 99
iterations_since_restore: 100
mean_loss: -3.9913348635947523
neg_mean_loss: 3.9913348635947523
node_ip: 127.0.0.1
pid: 47237
time_since_restore: 11.867748260498047
time_this_iter_s: 0.10774397850036621
time_total_s: 11.867748260498047
timestamp: 1658500326
timesteps_since_restore: 0
training_iteration: 100
trial_id: 07617f54
warmup_time: 0.00436091423034668
Result for objective_two_075f0d78:
date: 2022-07-22_15-32-07
done: true
experiment_id: 5a46a57ef1164628bac1618e39078e0e
experiment_tag: 2_activation=relu,mult=1.2210,height=46.4977,steps=100,width=13.6093
hostname: Kais-MacBook-Pro.local
iterations: 99
iterations_since_restore: 100
mean_loss: 5.7509525535298085
neg_mean_loss: -5.7509525535298085
node_ip: 127.0.0.1
pid: 47236
time_since_restore: 12.017354011535645
time_this_iter_s: 0.10736513137817383
time_total_s: 12.017354011535645
timestamp: 1658500327
timesteps_since_restore: 0
training_iteration: 100
trial_id: 075f0d78
warmup_time: 0.0035758018493652344
Result for objective_two_07636cd8:
date: 2022-07-22_15-32-07
done: true
experiment_id: 5c9d75b036ae410b9fdea303f14fe4cd
experiment_tag: 4_activation=tanh,height=49.0313,steps=100,width=0.8288
hostname: Kais-MacBook-Pro.local
iterations: 99
iterations_since_restore: 100
mean_loss: 5.989448515159168
neg_mean_loss: -5.989448515159168
node_ip: 127.0.0.1
pid: 47238
time_since_restore: 12.025846004486084
time_this_iter_s: 0.10526180267333984
time_total_s: 12.025846004486084
timestamp: 1658500327
timesteps_since_restore: 0
training_iteration: 100
trial_id: 07636cd8
warmup_time: 0.0037419795989990234
Result for objective_two_100ebe3c:
date: 2022-07-22_15-32-09
done: false
experiment_id: f31e00c7c87c4884bef04183585473d1
hostname: Kais-MacBook-Pro.local
iterations: 0
iterations_since_restore: 1
mean_loss: 6.11444579492732
neg_mean_loss: -6.11444579492732
node_ip: 127.0.0.1
pid: 47265
time_since_restore: 0.00012183189392089844
time_this_iter_s: 0.00012183189392089844
time_total_s: 0.00012183189392089844
timestamp: 1658500329
timesteps_since_restore: 0
training_iteration: 1
trial_id: 100ebe3c
warmup_time: 0.002948284149169922
Result for objective_two_101e702a:
date: 2022-07-22_15-32-09
done: false
experiment_id: 8c013d0ff6434dfe9719fa317f95feb8
hostname: Kais-MacBook-Pro.local
iterations: 0
iterations_since_restore: 1
mean_loss: 10.883328850459264
neg_mean_loss: -10.883328850459264
node_ip: 127.0.0.1
pid: 47268
time_since_restore: 0.00011587142944335938
time_this_iter_s: 0.00011587142944335938
time_total_s: 0.00011587142944335938
timestamp: 1658500329
timesteps_since_restore: 0
training_iteration: 1
trial_id: 101e702a
warmup_time: 0.003309965133666992
Result for objective_two_1022212a:
date: 2022-07-22_15-32-09
done: false
experiment_id: c3c0bdb8b68146c68f2c34e08fa2f184
hostname: Kais-MacBook-Pro.local
iterations: 0
iterations_since_restore: 1
mean_loss: 19.42843735686162
neg_mean_loss: -19.42843735686162
node_ip: 127.0.0.1
pid: 47269
time_since_restore: 0.00011324882507324219
time_this_iter_s: 0.00011324882507324219
time_total_s: 0.00011324882507324219
timestamp: 1658500329
timesteps_since_restore: 0
training_iteration: 1
trial_id: 1022212a
warmup_time: 0.0029020309448242188
Result for objective_two_0de7d38c:
date: 2022-07-22_15-32-11
done: false
experiment_id: 81d62307312a447e97c5d1f1cdad2687
hostname: Kais-MacBook-Pro.local
iterations: 47
iterations_since_restore: 48
mean_loss: -9.121869790245293
neg_mean_loss: 9.121869790245293
node_ip: 127.0.0.1
pid: 47256
time_since_restore: 5.047628164291382
time_this_iter_s: 0.10473132133483887
time_total_s: 5.047628164291382
timestamp: 1658500331
timesteps_since_restore: 0
training_iteration: 48
trial_id: 0de7d38c
warmup_time: 0.0027358531951904297
Result for objective_two_100ebe3c:
date: 2022-07-22_15-32-14
done: false
experiment_id: f31e00c7c87c4884bef04183585473d1
hostname: Kais-MacBook-Pro.local
iterations: 47
iterations_since_restore: 48
mean_loss: -3.7542934113649324
neg_mean_loss: 3.7542934113649324
node_ip: 127.0.0.1
pid: 47265
time_since_restore: 5.057713985443115
time_this_iter_s: 0.10337996482849121
time_total_s: 5.057713985443115
timestamp: 1658500334
timesteps_since_restore: 0
training_iteration: 48
trial_id: 100ebe3c
warmup_time: 0.002948284149169922
Result for objective_two_101e702a:
date: 2022-07-22_15-32-14
done: false
experiment_id: 8c013d0ff6434dfe9719fa317f95feb8
hostname: Kais-MacBook-Pro.local
iterations: 47
iterations_since_restore: 48
mean_loss: 4.188150411466976
neg_mean_loss: -4.188150411466976
node_ip: 127.0.0.1
pid: 47268
time_since_restore: 5.101155757904053
time_this_iter_s: 0.10826706886291504
time_total_s: 5.101155757904053
timestamp: 1658500334
timesteps_since_restore: 0
training_iteration: 48
trial_id: 101e702a
warmup_time: 0.003309965133666992
Result for objective_two_1022212a:
date: 2022-07-22_15-32-14
done: false
experiment_id: c3c0bdb8b68146c68f2c34e08fa2f184
hostname: Kais-MacBook-Pro.local
iterations: 47
iterations_since_restore: 48
mean_loss: 9.610922254324745
neg_mean_loss: -9.610922254324745
node_ip: 127.0.0.1
pid: 47269
time_since_restore: 5.09367823600769
time_this_iter_s: 0.11145401000976562
time_total_s: 5.09367823600769
timestamp: 1658500334
timesteps_since_restore: 0
training_iteration: 48
trial_id: 1022212a
warmup_time: 0.0029020309448242188
Result for objective_two_0de7d38c:
date: 2022-07-22_15-32-16
done: false
experiment_id: 81d62307312a447e97c5d1f1cdad2687
hostname: Kais-MacBook-Pro.local
iterations: 93
iterations_since_restore: 94
mean_loss: -9.195752548100788
neg_mean_loss: 9.195752548100788
node_ip: 127.0.0.1
pid: 47256
time_since_restore: 10.068511009216309
time_this_iter_s: 0.10715794563293457
time_total_s: 10.068511009216309
timestamp: 1658500336
timesteps_since_restore: 0
training_iteration: 94
trial_id: 0de7d38c
warmup_time: 0.0027358531951904297
Result for objective_two_0de7d38c:
date: 2022-07-22_15-32-16
done: true
experiment_id: 81d62307312a447e97c5d1f1cdad2687
experiment_tag: 5_activation=relu,mult=1.3983,height=-66.3136,steps=100,width=13.9221
hostname: Kais-MacBook-Pro.local
iterations: 99
iterations_since_restore: 100
mean_loss: -9.200364093875208
neg_mean_loss: 9.200364093875208
node_ip: 127.0.0.1
pid: 47256
time_since_restore: 10.707159996032715
time_this_iter_s: 0.1063990592956543
time_total_s: 10.707159996032715
timestamp: 1658500336
timesteps_since_restore: 0
training_iteration: 100
trial_id: 0de7d38c
warmup_time: 0.0027358531951904297
Result for objective_two_100ebe3c:
date: 2022-07-22_15-32-19
done: false
experiment_id: f31e00c7c87c4884bef04183585473d1
hostname: Kais-MacBook-Pro.local
iterations: 94
iterations_since_restore: 95
mean_loss: -3.8194902277136236
neg_mean_loss: 3.8194902277136236
node_ip: 127.0.0.1
pid: 47265
time_since_restore: 10.118366956710815
time_this_iter_s: 0.10590505599975586
time_total_s: 10.118366956710815
timestamp: 1658500339
timesteps_since_restore: 0
training_iteration: 95
trial_id: 100ebe3c
warmup_time: 0.002948284149169922
Result for objective_two_15fbf8dc:
date: 2022-07-22_15-32-19
done: false
experiment_id: 825ceb15d1134810ba19f09bb90c2b35
hostname: Kais-MacBook-Pro.local
iterations: 0
iterations_since_restore: 1
mean_loss: 6.071327317808535
neg_mean_loss: -6.071327317808535
node_ip: 127.0.0.1
pid: 47288
time_since_restore: 0.0002067089080810547
time_this_iter_s: 0.0002067089080810547
time_total_s: 0.0002067089080810547
timestamp: 1658500339
timesteps_since_restore: 0
training_iteration: 1
trial_id: 15fbf8dc
warmup_time: 0.005033969879150391
Result for objective_two_101e702a:
date: 2022-07-22_15-32-19
done: false
experiment_id: 8c013d0ff6434dfe9719fa317f95feb8
hostname: Kais-MacBook-Pro.local
iterations: 94
iterations_since_restore: 95
mean_loss: 2.86283543260466
neg_mean_loss: -2.86283543260466
node_ip: 127.0.0.1
pid: 47268
time_since_restore: 10.181840896606445
time_this_iter_s: 0.10625004768371582
time_total_s: 10.181840896606445
timestamp: 1658500339
timesteps_since_restore: 0
training_iteration: 95
trial_id: 101e702a
warmup_time: 0.003309965133666992
Result for objective_two_1022212a:
date: 2022-07-22_15-32-19
done: false
experiment_id: c3c0bdb8b68146c68f2c34e08fa2f184
hostname: Kais-MacBook-Pro.local
iterations: 94
iterations_since_restore: 95
mean_loss: 9.520519990087298
neg_mean_loss: -9.520519990087298
node_ip: 127.0.0.1
pid: 47269
time_since_restore: 10.166353225708008
time_this_iter_s: 0.10583710670471191
time_total_s: 10.166353225708008
timestamp: 1658500339
timesteps_since_restore: 0
training_iteration: 95
trial_id: 1022212a
warmup_time: 0.0029020309448242188
Result for objective_two_100ebe3c:
date: 2022-07-22_15-32-20
done: true
experiment_id: f31e00c7c87c4884bef04183585473d1
experiment_tag: 6_activation=tanh,height=-38.8555,steps=100,width=15.9966
hostname: Kais-MacBook-Pro.local
iterations: 99
iterations_since_restore: 100
mean_loss: -3.8228058558351754
neg_mean_loss: 3.8228058558351754
node_ip: 127.0.0.1
pid: 47265
time_since_restore: 10.657065153121948
time_this_iter_s: 0.10721731185913086
time_total_s: 10.657065153121948
timestamp: 1658500340
timesteps_since_restore: 0
training_iteration: 100
trial_id: 100ebe3c
warmup_time: 0.002948284149169922
Result for objective_two_101e702a:
date: 2022-07-22_15-32-20
done: true
experiment_id: 8c013d0ff6434dfe9719fa317f95feb8
experiment_tag: 7_activation=relu,mult=1.5102,height=5.8490,steps=100,width=0.4310
hostname: Kais-MacBook-Pro.local
iterations: 99
iterations_since_restore: 100
mean_loss: 2.781840740489214
neg_mean_loss: -2.781840740489214
node_ip: 127.0.0.1
pid: 47268
time_since_restore: 10.72019100189209
time_this_iter_s: 0.1079869270324707
time_total_s: 10.72019100189209
timestamp: 1658500340
timesteps_since_restore: 0
training_iteration: 100
trial_id: 101e702a
warmup_time: 0.003309965133666992
Result for objective_two_1022212a:
date: 2022-07-22_15-32-20
done: true
experiment_id: c3c0bdb8b68146c68f2c34e08fa2f184
experiment_tag: 8_activation=relu,mult=1.3226,height=71.2885,steps=100,width=11.4466
hostname: Kais-MacBook-Pro.local
iterations: 99
iterations_since_restore: 100
mean_loss: 9.515910032420853
neg_mean_loss: -9.515910032420853
node_ip: 127.0.0.1
pid: 47269
time_since_restore: 10.707203149795532
time_this_iter_s: 0.10514593124389648
time_total_s: 10.707203149795532
timestamp: 1658500340
timesteps_since_restore: 0
training_iteration: 100
trial_id: 1022212a
warmup_time: 0.0029020309448242188
Result for objective_two_18090732:
date: 2022-07-22_15-32-23
done: false
experiment_id: 7cb1145f46214bc4a5dd35e796969e53
hostname: Kais-MacBook-Pro.local
iterations: 0
iterations_since_restore: 1
mean_loss: 15.276134004304078
neg_mean_loss: -15.276134004304078
node_ip: 127.0.0.1
pid: 47302
time_since_restore: 0.00011110305786132812
time_this_iter_s: 0.00011110305786132812
time_total_s: 0.00011110305786132812
timestamp: 1658500343
timesteps_since_restore: 0
training_iteration: 1
trial_id: '18090732'
warmup_time: 0.0028650760650634766
Result for objective_two_15fbf8dc:
date: 2022-07-22_15-32-24
done: false
experiment_id: 825ceb15d1134810ba19f09bb90c2b35
hostname: Kais-MacBook-Pro.local
iterations: 47
iterations_since_restore: 48
mean_loss: -3.708075105876967
neg_mean_loss: 3.708075105876967
node_ip: 127.0.0.1
pid: 47288
time_since_restore: 5.015958786010742
time_this_iter_s: 0.10610795021057129
time_total_s: 5.015958786010742
timestamp: 1658500344
timesteps_since_restore: 0
training_iteration: 48
trial_id: 15fbf8dc
warmup_time: 0.005033969879150391
Result for objective_two_18090732:
date: 2022-07-22_15-32-28
done: false
experiment_id: 7cb1145f46214bc4a5dd35e796969e53
hostname: Kais-MacBook-Pro.local
iterations: 47
iterations_since_restore: 48
mean_loss: 5.4017373166361775
neg_mean_loss: -5.4017373166361775
node_ip: 127.0.0.1
pid: 47302
time_since_restore: 5.047500133514404
time_this_iter_s: 0.10670995712280273
time_total_s: 5.047500133514404
timestamp: 1658500348
timesteps_since_restore: 0
training_iteration: 48
trial_id: '18090732'
warmup_time: 0.0028650760650634766
Result for objective_two_15fbf8dc:
date: 2022-07-22_15-32-29
done: false
experiment_id: 825ceb15d1134810ba19f09bb90c2b35
hostname: Kais-MacBook-Pro.local
iterations: 94
iterations_since_restore: 95
mean_loss: -3.8171437433543964
neg_mean_loss: 3.8171437433543964
node_ip: 127.0.0.1
pid: 47288
time_since_restore: 10.057979822158813
time_this_iter_s: 0.10869002342224121
time_total_s: 10.057979822158813
timestamp: 1658500349
timesteps_since_restore: 0
training_iteration: 95
trial_id: 15fbf8dc
warmup_time: 0.005033969879150391
Result for objective_two_15fbf8dc:
date: 2022-07-22_15-32-30
done: true
experiment_id: 825ceb15d1134810ba19f09bb90c2b35
experiment_tag: 9_activation=relu,mult=1.2217,height=-32.1584,steps=100,width=9.4322
hostname: Kais-MacBook-Pro.local
iterations: 99
iterations_since_restore: 100
mean_loss: -3.8227168355020016
neg_mean_loss: 3.8227168355020016
node_ip: 127.0.0.1
pid: 47288
time_since_restore: 10.599114894866943
time_this_iter_s: 0.10727405548095703
time_total_s: 10.599114894866943
timestamp: 1658500350
timesteps_since_restore: 0
training_iteration: 100
trial_id: 15fbf8dc
warmup_time: 0.005033969879150391
Result for objective_two_18090732:
date: 2022-07-22_15-32-33
done: false
experiment_id: 7cb1145f46214bc4a5dd35e796969e53
hostname: Kais-MacBook-Pro.local
iterations: 94
iterations_since_restore: 95
mean_loss: 5.339332557853146
neg_mean_loss: -5.339332557853146
node_ip: 127.0.0.1
pid: 47302
time_since_restore: 10.092173099517822
time_this_iter_s: 0.1067051887512207
time_total_s: 10.092173099517822
timestamp: 1658500353
timesteps_since_restore: 0
training_iteration: 95
trial_id: '18090732'
warmup_time: 0.0028650760650634766
Result for objective_two_18090732:
date: 2022-07-22_15-32-33
done: true
experiment_id: 7cb1145f46214bc4a5dd35e796969e53
experiment_tag: 10_activation=tanh,height=52.7613,steps=100,width=16.7268
hostname: Kais-MacBook-Pro.local
iterations: 99
iterations_since_restore: 100
mean_loss: 5.336159871047403
neg_mean_loss: -5.336159871047403
node_ip: 127.0.0.1
pid: 47302
time_since_restore: 10.633639097213745
time_this_iter_s: 0.1067359447479248
time_total_s: 10.633639097213745
timestamp: 1658500353
timesteps_since_restore: 0
training_iteration: 100
trial_id: '18090732'
warmup_time: 0.0028650760650634766
Finally, we again show the hyperparameters that minimize the mean loss defined by the score of the objective function above.
print("Best hyperparameters found were: ", results.get_best_result().config)
Best hyperparameters found were: {'activation': {'activation': 'relu', 'mult': 1.3982639549501585}, 'height': -66.3136247260571, 'steps': 100, 'width': 13.922128223483856}