<commit_before>import os
import sys
import time
import numpy as np

import logging
logging.basicConfig(level=logging.INFO)

from sklearn import svm

from robo.fmin import fabolas_fmin

# This function loads the MNIST data, its copied from the Lasagne tutorial
def load_dataset():
    # We first define a download function, supporting both Python 2 and 3.
    if sys.version_info[0] == 2:
        from urllib import urlretrieve
    else:
        from urllib.request import urlretrieve
<commit_msg>small fix<commit_after>import os
import sys
import time
import numpy as np

from sklearn import svm

from robo.fmin import fabolas_fmin


# Example script to optimize the C and gamma parameter of a
# support vector machine on MNIST with Fabolas.
# Have a look into the paper " Fast Bayesian Optimization of Machine Learning
# Hyperparameters on Large Datasets" (http://arxiv.org/abs/1605.07079)
# to see how it works


def load_dataset():
    # This function loads the MNIST data, its copied from the Lasagne tutorial
    # We first define a download function, supporting both Python 2 and 3.
    if sys.version_info[0] == 2:
        from urllib import urlretrieve
    else:
        from urllib.request import urlretrieve

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