fmin code doesn't work

The code in the tutorial for black box function optimization doesn't work ( https://automl.github.io/RoBO/tutorials.html#blackbox-function-optimization-with-robo ).
Additionally test_fmin/test_fmin_interface.py throws the same errors:

`test_fmin $ python test_fmin_interface.py Traceback (most recent call last):
File "test_fmin_interface.py", line 4, in
from robo.fmin import random_search, bayesian_optimization, bohamiann
File "/usr/local/lib/python2.7/dist-packages/RoBO-0.2.1-py2.7.egg/robo/fmin/__init__.py", line 2, in
from .bayesian_optimization import bayesian_optimization
File "/usr/local/lib/python2.7/dist-packages/RoBO-0.2.1-py2.7.egg/robo/fmin/bayesian_optimization.py", line 6, in
from robo.models.gaussian_process import GaussianProcess
File "/usr/local/lib/python2.7/dist-packages/RoBO-0.2.1-py2.7.egg/robo/models/gaussian_process.py", line 14, in
class GaussianProcess(BaseModel):
File "/usr/local/lib/python2.7/dist-packages/RoBO-0.2.1-py2.7.egg/robo/models/gaussian_process.py", line 70, in GaussianProcess
def train(self, X, y, do_optimize=True):
TypeError: unbound method _check_shapes_train() must be called with BaseModel instance as first argument (got function instance instead)`

Start with the black-box function optimization tutorial and reproduce the failure using test_fmin/test_fmin_interface.py. Trace the import path through robo/fmin/__init__.py to robo/models/gaussian_process.py, where the reported TypeError occurs. Done means the fmin tutorial code and test_fmin_interface.py run without this error.

Written by the indexing model from the issue text.