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I ran coverage run --source=robo -m unittest discover test -v and got
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ERROR: test_bayesian_optimization (test_fmin.test_fabolas.TestFminInterfaceFabolas)
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Traceback (most recent call last):
File "/home/andy/checkout/RoBO/test/test_fmin/test_fabolas.py", line 32, in test_bayesian_optimization
num_iterations=3)
File "/home/andy/checkout/RoBO/robo/fmin/fabolas.py", line 255, in fabolas
new_x = maximizer.maximize()
File "/home/andy/checkout/RoBO/robo/maximizers/direct.py", line 58, in maximize
maxf=self.n_func_evals)
File "/home/andy/anaconda3/lib/python3.6/site-packages/DIRECT/__init__.py", line 202, in solve
cdata
ValueError: data type must provide an itemsize
======================================================================
ERROR: test_bayesian_optimization (test_fmin.test_fmin_interface.TestFminInterface)
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Traceback (most recent call last):
File "/home/andy/checkout/RoBO/test/test_fmin/test_fmin_interface.py", line 31, in test_bayesian_optimization
num_iterations=3)
File "/home/andy/checkout/RoBO/robo/fmin/bayesian_optimization.py", line 133, in bayesian_optimization
x_best, f_min = bo.run(num_iterations)
File "/home/andy/checkout/RoBO/robo/solver/bayesian_optimization.py", line 167, in run
new_x = self.choose_next(self.X, self.y, do_optimize)
File "/home/andy/checkout/RoBO/robo/solver/bayesian_optimization.py", line 245, in choose_next
x = self.maximize_func.maximize()
File "/home/andy/checkout/RoBO/robo/maximizers/direct.py", line 69, in maximize
maxf=self.n_func_evals)
File "/home/andy/anaconda3/lib/python3.6/site-packages/DIRECT/__init__.py", line 202, in solve
cdata
ValueError: data type must provide an itemsize
======================================================================
ERROR: test_bohamiann (test_fmin.test_fmin_interface.TestFminInterface)
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Traceback (most recent call last):
File "/home/andy/checkout/RoBO/test/test_fmin/test_fmin_interface.py", line 41, in test_bohamiann
num_iterations=3)
File "/home/andy/checkout/RoBO/robo/fmin/bohamiann.py", line 59, in bohamiann
normalize_output=True)
File "/home/andy/checkout/RoBO/robo/models/bnn.py", line 122, in __init__
raise ValueError("If you want to use Bayesian Neural Networks you "
ValueError: If you want to use Bayesian Neural Networks you have to install the following dependencies:
Theano (pip install theano)
Lasagne (pip install lasagne)
sgmcmc (see https://github.com/stokasto/sgmcmc)
======================================================================
ERROR: test_bayesian_optimization (test_fmin.test_mtbo.TestFminInterface)
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Traceback (most recent call last):
File "/home/andy/checkout/RoBO/test/test_fmin/test_mtbo.py", line 28, in test_bayesian_optimization
num_iterations=3)
File "/home/andy/checkout/RoBO/robo/fmin/mtbo.py", line 228, in mtbo
new_x = maximizer.maximize()
File "/home/andy/checkout/RoBO/robo/maximizers/direct.py", line 58, in maximize
maxf=self.n_func_evals)
File "/home/andy/anaconda3/lib/python3.6/site-packages/DIRECT/__init__.py", line 202, in solve
cdata
ValueError: data type must provide an itemsize
======================================================================
ERROR: test_direct (test_maximizer.test_maximizers_one_dim.TestMaximizers1D)
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Traceback (most recent call last):
File "/home/andy/checkout/RoBO/test/test_maximizer/test_maximizers_one_dim.py", line 24, in test_direct
x = maximizer.maximize()
File "/home/andy/checkout/RoBO/robo/maximizers/direct.py", line 69, in maximize
maxf=self.n_func_evals)
File "/home/andy/anaconda3/lib/python3.6/site-packages/DIRECT/__init__.py", line 202, in solve
cdata
ValueError: data type must provide an itemsize
======================================================================
ERROR: test_cmaes (test_maximizer.test_maximizers_two_dim.TestMaximizers2D)
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Traceback (most recent call last):
File "/home/andy/checkout/RoBO/test/test_maximizer/test_maximizers_two_dim.py", line 33, in test_cmaes
x = maximizer.maximize()
File "/home/andy/checkout/RoBO/robo/maximizers/cmaes.py", line 81, in maximize
"maxfevals": self.n_func_evals})
File "/home/andy/anaconda3/lib/python3.6/site-packages/cma.py", line 5466, in fmin
es = CMAEvolutionStrategy(x0, sigma_factor * sigma0, opts)
File "/home/andy/anaconda3/lib/python3.6/site-packages/cma.py", line 2803, in __init__
if not self.boundary_handler.has_bounds():
File "/home/andy/anaconda3/lib/python3.6/site-packages/cma.py", line 957, in has_bounds
if bounds in (None, [None, None]):
ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()
======================================================================
ERROR: test_direct (test_maximizer.test_maximizers_two_dim.TestMaximizers2D)
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Traceback (most recent call last):
File "/home/andy/checkout/RoBO/test/test_maximizer/test_maximizers_two_dim.py", line 24, in test_direct
x = maximizer.maximize()
File "/home/andy/checkout/RoBO/robo/maximizers/direct.py", line 69, in maximize
maxf=self.n_func_evals)
File "/home/andy/anaconda3/lib/python3.6/site-packages/DIRECT/__init__.py", line 202, in solve
cdata
ValueError: data type must provide an itemsize
======================================================================
ERROR: test_get_incumbent (test_models.test_bnn.TestBayesianNeuralNetwork)
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Traceback (most recent call last):
File "/home/andy/checkout/RoBO/test/test_models/test_bnn.py", line 12, in setUp
self.model = BayesianNeuralNetwork(normalize_output=True, normalize_input=True)
File "/home/andy/checkout/RoBO/robo/models/bnn.py", line 122, in __init__
raise ValueError("If you want to use Bayesian Neural Networks you "
ValueError: If you want to use Bayesian Neural Networks you have to install the following dependencies:
Theano (pip install theano)
Lasagne (pip install lasagne)
sgmcmc (see https://github.com/stokasto/sgmcmc)
======================================================================
ERROR: test_predict (test_models.test_bnn.TestBayesianNeuralNetwork)
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Traceback (most recent call last):
File "/home/andy/checkout/RoBO/test/test_models/test_bnn.py", line 12, in setUp
self.model = BayesianNeuralNetwork(normalize_output=True, normalize_input=True)
File "/home/andy/checkout/RoBO/robo/models/bnn.py", line 122, in __init__
raise ValueError("If you want to use Bayesian Neural Networks you "
ValueError: If you want to use Bayesian Neural Networks you have to install the following dependencies:
Theano (pip install theano)
Lasagne (pip install lasagne)
sgmcmc (see https://github.com/stokasto/sgmcmc)
======================================================================
ERROR: test_models.test_dngo (unittest.loader._FailedTest)
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ImportError: Failed to import test module: test_models.test_dngo
Traceback (most recent call last):
File "/home/andy/checkout/RoBO/robo/models/dngo.py", line 11, in <module>
import lasagne
File "/home/andy/anaconda3/lib/python3.6/site-packages/lasagne/__init__.py", line 19, in <module>
from . import layers
File "/home/andy/anaconda3/lib/python3.6/site-packages/lasagne/layers/__init__.py", line 7, in <module>
from .pool import *
File "/home/andy/anaconda3/lib/python3.6/site-packages/lasagne/layers/pool.py", line 6, in <module>
from theano.tensor.signal import downsample
ImportError: cannot import name 'downsample'
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/home/andy/anaconda3/lib/python3.6/unittest/loader.py", line 428, in _find_test_path
module = self._get_module_from_name(name)
File "/home/andy/anaconda3/lib/python3.6/unittest/loader.py", line 369, in _get_module_from_name
__import__(name)
File "/home/andy/checkout/RoBO/test/test_models/test_dngo.py", line 4, in <module>
from robo.models.dngo import DNGO
File "/home/andy/checkout/RoBO/robo/models/dngo.py", line 14, in <module>
raise ValueError("If you want to use DNGO you have to install the following dependencies:\n"
ValueError: If you want to use DNGO you have to install the following dependencies:
Theano (pip install theano)
Lasagne (pip install lasagne)
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ERROR: test_choose_next (test_solver.test_bayesian_optimization.TestBayesianOptimization)
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Traceback (most recent call last):
File "/home/andy/checkout/RoBO/test/test_solver/test_bayesian_optimization.py", line 46, in test_choose_next
x_new = self.solver.choose_next(X, y)
File "/home/andy/checkout/RoBO/robo/solver/bayesian_optimization.py", line 245, in choose_next
x = self.maximize_func.maximize()
File "/home/andy/checkout/RoBO/robo/maximizers/direct.py", line 69, in maximize
maxf=self.n_func_evals)
File "/home/andy/anaconda3/lib/python3.6/site-packages/DIRECT/__init__.py", line 202, in solve
cdata
ValueError: data type must provide an itemsize
======================================================================
ERROR: test_run (test_solver.test_bayesian_optimization.TestBayesianOptimization)
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Traceback (most recent call last):
File "/home/andy/checkout/RoBO/test/test_solver/test_bayesian_optimization.py", line 30, in test_run
inc, inc_val = self.solver.run(n_iters)
File "/home/andy/checkout/RoBO/robo/solver/bayesian_optimization.py", line 167, in run
new_x = self.choose_next(self.X, self.y, do_optimize)
File "/home/andy/checkout/RoBO/robo/solver/bayesian_optimization.py", line 245, in choose_next
x = self.maximize_func.maximize()
File "/home/andy/checkout/RoBO/robo/maximizers/direct.py", line 69, in maximize
maxf=self.n_func_evals)
File "/home/andy/anaconda3/lib/python3.6/site-packages/DIRECT/__init__.py", line 202, in solve
cdata
ValueError: data type must provide an itemsize
======================================================================
ERROR: test_posterior_mean_optimization (test_util.test_posterior_optimization.TestPosteriorOptimization)
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Traceback (most recent call last):
File "/home/andy/checkout/RoBO/test/test_util/test_posterior_optimization.py", line 22, in test_posterior_mean_optimization
x = posterior_mean_optimization(self.model, self.lower, self.upper, method="cma", n_restarts=1)
File "/home/andy/checkout/RoBO/robo/util/posterior_optimization.py", line 61, in posterior_mean_optimization
res = cma.fmin(f, startpoint, 0.6, options={"bounds": [lower, upper]})
File "/home/andy/anaconda3/lib/python3.6/site-packages/cma.py", line 5466, in fmin
es = CMAEvolutionStrategy(x0, sigma_factor * sigma0, opts)
File "/home/andy/anaconda3/lib/python3.6/site-packages/cma.py", line 2803, in __init__
if not self.boundary_handler.has_bounds():
File "/home/andy/anaconda3/lib/python3.6/site-packages/cma.py", line 957, in has_bounds
if bounds in (None, [None, None]):
ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()
======================================================================
ERROR: test_posterior_mean_plus_std_optimization (test_util.test_posterior_optimization.TestPosteriorOptimization)
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Traceback (most recent call last):
File "/home/andy/checkout/RoBO/test/test_util/test_posterior_optimization.py", line 29, in test_posterior_mean_plus_std_optimization
x = posterior_mean_plus_std_optimization(self.model, self.lower, self.upper, method="cma", n_restarts=1)
File "/home/andy/checkout/RoBO/robo/util/posterior_optimization.py", line 129, in posterior_mean_plus_std_optimization
res = cma.fmin(f, startpoint, 0.6, options={"bounds": [lower, upper]})
File "/home/andy/anaconda3/lib/python3.6/site-packages/cma.py", line 5466, in fmin
es = CMAEvolutionStrategy(x0, sigma_factor * sigma0, opts)
File "/home/andy/anaconda3/lib/python3.6/site-packages/cma.py", line 2803, in __init__
if not self.boundary_handler.has_bounds():
File "/home/andy/anaconda3/lib/python3.6/site-packages/cma.py", line 957, in has_bounds
if bounds in (None, [None, None]):
ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()
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Ran 55 tests in 175.833s
FAILED (errors=14)
I'm using Python3.6 (which is not on your CI, I guess?) and
for req in $(cat all_requirements.txt); do pip install $req; done
so I would have thought that that at least installs the requirements to make the tests pass.
Maybe for the theano tests raise a SkipTest instead of failing?
The text was updated successfully, but these errors were encountered:
I ran
coverage run --source=robo -m unittest discover test -v
and gotI'm using Python3.6 (which is not on your CI, I guess?) and
I ran
so I would have thought that that at least installs the requirements to make the tests pass.
Maybe for the theano tests raise a
SkipTest
instead of failing?The text was updated successfully, but these errors were encountered: