from robo.initial_design import init_random_uniform
from hpolib.benchmarks.ml.surrogate_svm import SurrogateSVM
from hpolib.benchmarks.ml.surrogate_cnn import SurrogateCNN
from hpolib.benchmarks.ml.surrogate_fcnet import SurrogateFCNet
run_id = int(sys.argv[1])
benchmark = sys.argv[2]
n_iters = 50
output_path = "./experiments/RoBO/surrogates/"
if benchmark == "svm_mnist":
b = SurrogateSVM(path="/ihome/kleinaa/devel/git/HPOlib/surrogates/")
elif benchmark == "cnn_cifar10":
b = SurrogateCNN(path="/ihome/kleinaa/devel/git/HPOlib/surrogates/")
elif benchmark == "fcnet_mnist":
b = SurrogateFCNet(path="/ihome/kleinaa/devel/git/HPOlib/surrogates/")
info = b.get_meta_information()
X = []
y = []
def wrapper(x):
X.append(x.tolist())
y_ = b.objective_function(x)['function_value']
y.append(y_)
import numpy as np
logging.basicConfig(level=logging.INFO)
from robo.fmin import fabolas
from hpolib.benchmarks.ml.surrogate_svm import SurrogateSVM
from hpolib.benchmarks.ml.surrogate_cnn import SurrogateCNN
from hpolib.benchmarks.ml.surrogate_fcnet import SurrogateFCNet
run_id = int(sys.argv[1])
benchmark = sys.argv[2]
if benchmark == "svm_mnist":
f = SurrogateSVM(path="/ihome/kleinaa/devel/git/HPOlib/surrogates/")
elif benchmark == "cnn_cifar10":
f = SurrogateCNN(path="/ihome/kleinaa/devel/git/HPOlib/surrogates/")
elif benchmark == "fcnet_mnist":
f = SurrogateFCNet(path="/ihome/kleinaa/devel/git/HPOlib/surrogates/")
output_path = "./experiments/RoBO/surrogates"
rng = np.random.RandomState(run_id)
num_iterations = 150
s_max = 50000
s_min = 100
subsets = [128] * 8
subsets.extend([64] * 4)
subsets.extend([32] * 2)
import logging
import numpy as np
logging.basicConfig(level=logging.INFO)
from robo.solver.hyperband_datasets_size import HyperBand_DataSubsets
from hpolib.benchmarks.ml.surrogate_svm import SurrogateSVM
run_id = int(sys.argv[1])
seed = int(sys.argv[2])
rng = np.random.RandomState(seed)
dataset = "surrogate"
f = SurrogateSVM(
path="/mhome/kleinaa/experiments/fabolas/dataset/svm_on_mnist_grid",
rng=rng)
output_path = "/mhome/kleinaa/experiments/fabolas_journal/results/svm_%s/hyperband_last_seen_incumbent_%d" % (
dataset, run_id)
os.makedirs(output_path, exist_ok=True)
eta = 3.
B = -int(np.log(f.s_min) / np.log(3))
print(B)
opt = HyperBand_DataSubsets(f,
eta,
eta**(-(B - 1)),
output_path=output_path,
from hpolib.benchmarks.ml.surrogate_svm import SurrogateSVM
from hpolib.benchmarks.ml.surrogate_cnn import SurrogateCNN
from hpolib.benchmarks.ml.surrogate_fcnet import SurrogateFCNet
from hpolib.benchmarks.ml.surrogate_paramnet import SurrogateParamNet
run_id = int(sys.argv[1])
benchmark = sys.argv[2]
method = sys.argv[3]
n_iters = 50
n_init = 2
output_path = "./experiments/RoBO/surrogates"
if benchmark == "svm_mnist":
f = SurrogateSVM(path="/ihome/kleinaa/devel/git/HPOlib/surrogates/")
elif benchmark == "cnn_cifar10":
f = SurrogateCNN(path="/ihome/kleinaa/devel/git/HPOlib/surrogates/")
elif benchmark == "fcnet_mnist":
f = SurrogateFCNet(path="/ihome/kleinaa/devel/git/HPOlib/surrogates/")
elif benchmark == "paramnet":
dataset = sys.argv[4]
f = SurrogateParamNet(dataset, "/ihome/kleinaa/devel/git/HPOlib/surrogates/")
benchmark += "_" + dataset
info = f.get_meta_information()
bounds = np.array(info['bounds'])
if method == "entropy_search":
results = entropy_search(f, bounds[:, 0], bounds[:, 1],
logging.basicConfig(level=logging.INFO)
from robo.solver.hyperband_datasets_size import HyperBand_DataSubsets
from hpolib.benchmarks.ml.surrogate_svm import SurrogateSVM
from hpolib.benchmarks.ml.surrogate_cnn import SurrogateCNN
from hpolib.benchmarks.ml.surrogate_fcnet import SurrogateFCNet
run_id = int(sys.argv[1])
benchmark = sys.argv[2]
rng = np.random.RandomState(run_id)
dataset = "surrogate"
if benchmark == "svm_mnist":
f = SurrogateSVM(path="/ihome/kleinaa/devel/git/HPOlib/surrogates/")
elif benchmark == "cnn_cifar10":
f = SurrogateCNN(path="/ihome/kleinaa/devel/git/HPOlib/surrogates/")
elif benchmark == "fcnet_mnist":
f = SurrogateFCNet(path="/ihome/kleinaa/devel/git/HPOlib/surrogates/")
output_path = "./experiments/RoBO/surrogates"
eta = 3.
B = -int(np.log(f.s_min)/np.log(3))
opt = HyperBand_DataSubsets(f, eta, eta**(-(B-1)), rng=rng)
opt.run(int(20 / B * 1.5))
results = dict()
import numpy as np
logging.basicConfig(level=logging.INFO)
from robo.fmin import mtbo
from hpolib.benchmarks.ml.surrogate_svm import SurrogateSVM
run_id = int(sys.argv[1])
seed = int(sys.argv[2])
auxillay_dataset = int(sys.argv[3])
dataset = "surrogate"
rng = np.random.RandomState(seed)
f = SurrogateSVM(path="/home/kleinaa/experiments/fabolas/dataset/svm_on_mnist_grid", rng=rng)
num_iterations = 80
output_path = "./experiments/fabolas_journal/results/svm_%s/mtbo_%d_%d" % (dataset, auxillay_dataset, run_id)
os.makedirs(output_path, exist_ok=True)
def objective(x, task):
if task == 0:
dataset_fraction = float(1/auxillay_dataset)
elif task == 1:
dataset_fraction = 1
res = f.objective_function(x, dataset_fraction=dataset_fraction)
return res["function_value"], res["cost"]
logging.basicConfig(level=logging.INFO)
from robo.fmin import mtbo
from hpolib.benchmarks.ml.surrogate_svm import SurrogateSVM
from hpolib.benchmarks.ml.surrogate_cnn import SurrogateCNN
from hpolib.benchmarks.ml.surrogate_fcnet import SurrogateFCNet
run_id = int(sys.argv[1])
benchmark = sys.argv[2]
auxillay_dataset = int(sys.argv[3])
rng = np.random.RandomState(run_id)
if benchmark == "svm_mnist":
f = SurrogateSVM(path="/ihome/kleinaa/devel/git/HPOlib/surrogates/")
elif benchmark == "cnn_cifar10":
f = SurrogateCNN(path="/ihome/kleinaa/devel/git/HPOlib/surrogates/")
elif benchmark == "fcnet_mnist":
f = SurrogateFCNet(path="/ihome/kleinaa/devel/git/HPOlib/surrogates/")
num_iterations = 80
output_path = "./experiments/RoBO/surrogate/"
os.makedirs(output_path, exist_ok=True)
def objective(x, task):
if task == 0:
dataset_fraction = float(1 / auxillay_dataset)
elif task == 1:
import logging import numpy as np logging.basicConfig(level=logging.INFO) from robo.solver.hyperband_datasets_size import HyperBand_DataSubsets from hpolib.benchmarks.ml.surrogate_svm import SurrogateSVM run_id = int(sys.argv[1]) seed = int(sys.argv[2]) rng = np.random.RandomState(seed) dataset = "surrogate" f = SurrogateSVM(path="/mhome/kleinaa/experiments/fabolas/dataset/svm_on_mnist_grid", rng=rng) output_path = "/mhome/kleinaa/experiments/fabolas_journal/results/svm_%s/hyperband_last_seen_incumbent_%d" % (dataset, run_id) os.makedirs(output_path, exist_ok=True) eta = 3. B = -int(np.log(f.s_min)/np.log(3)) print(B) opt = HyperBand_DataSubsets(f, eta, eta**(-(B-1)), output_path=output_path, rng=rng) opt.run(int(20 / B * 1.5)) test_error = [] runtime = []