#!/usr/bin/env python
import argparse
import ray
from ray import tune
from ray.tune.schedulers.pb2 import PB2
from ray.tune.examples.pbt_function import pbt_function
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument(
"--smoke-test", action="store_true", help="Finish quickly for testing")
args, _ = parser.parse_known_args()
if args.smoke_test:
ray.init(num_cpus=2) # force pausing to happen for test
else:
ray.init()
pbt = PB2(
perturbation_interval=20,
hyperparam_bounds={
# hyperparameter bounds.
"lr": [0.0001, 0.02],
})
analysis = tune.run(
pbt_function,
name="pbt_test",
scheduler=pbt,
metric="mean_accuracy",
mode="max",
verbose=False,
stop={
"training_iteration": 30,
},
num_samples=8,
fail_fast=True,
config={
"lr": 0.0001,
# note: this parameter is perturbed but has no effect on
# the model training in this example
"some_other_factor": 1,
})
print("Best hyperparameters found were: ", analysis.best_config)
