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Merge branch 'cython-fix' of git://github.com/jayanthkoushik/GPy into jayanthkoushik-cython-fix

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This commit is contained in:
mzwiessele 2018-09-02 19:10:19 +01:00
commit da82f356a8
6 changed files with 55 additions and 37 deletions
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20
GPy/testing/cython_tests.py
View file

@ -2,21 +2,27 @@ import numpy as np
import scipy as sp
from GPy.util import choleskies
import GPy
from ..util.config import config
import unittest
from ..util.config import config
try:
from ..util import linalg_cython
from ..util import choleskies_cython
config.set('cython', 'working', 'True')
choleskies_cython_working = config.getboolean('cython', 'working')
except ImportError:
config.set('cython', 'working', 'False')
choleskies_cython_working = False
try:
from ..kern.src import stationary_cython
stationary_cython_working = config.getboolean('cython', 'working')
except ImportError:
stationary_cython_working = False
"""
These tests make sure that the pure python and cython codes work the same
"""
@unittest.skipIf(not config.getboolean('cython', 'working'),"Cython modules have not been built on this machine")
@unittest.skipIf(not choleskies_cython_working,"Cython cholesky module has not been built on this machine")
class CythonTestChols(np.testing.TestCase):
def setUp(self):
self.flat = np.random.randn(45,5)
@ -30,7 +36,7 @@ class CythonTestChols(np.testing.TestCase):
A2 = choleskies._triang_to_flat_cython(self.triang)
np.testing.assert_allclose(A1, A2)
@unittest.skipIf(not config.getboolean('cython', 'working'),"Cython modules have not been built on this machine")
@unittest.skipIf(not stationary_cython_working,"Cython stationary module has not been built on this machine")
class test_stationary(np.testing.TestCase):
def setUp(self):
self.k = GPy.kern.RBF(10)
@ -60,7 +66,7 @@ class test_stationary(np.testing.TestCase):
g2 = self.k._lengthscale_grads_cython(self.dKxz, self.X, self.Z)
np.testing.assert_allclose(g1, g2)
@unittest.skipIf(not config.getboolean('cython', 'working'),"Cython modules have not been built on this machine")
@unittest.skipIf(not choleskies_cython_working,"Cython cholesky module has not been built on this machine")
class test_choleskies_backprop(np.testing.TestCase):
def setUp(self):
a =np.random.randn(10,12)

38
GPy/testing/kernel_tests.py
View file

@ -14,10 +14,10 @@ from ..util.config import config
verbose = 0
try:
from ..util import linalg_cython
config.set('cython', 'working', 'True')
from ..kern.src import coregionalize_cython
cython_coregionalize_working = config.getboolean('cython', 'working')
except ImportError:
config.set('cython', 'working', 'False')
cython_coregionalize_working = False
class Kern_check_model(GPy.core.Model):
@ -641,7 +641,7 @@ class KernelTestsNonContinuous(unittest.TestCase):
kern = GPy.kern.Coregionalize(1, output_dim=3, active_dims=[-1])
self.assertTrue(check_kernel_gradient_functions(kern, X=self.X, X2=self.X2, verbose=verbose, fixed_X_dims=-1))
@unittest.skipIf(not config.getboolean('cython', 'working'),"Cython modules have not been built on this machine")
@unittest.skipIf(not cython_coregionalize_working,"Cython coregionalize module has not been built on this machine")
class Coregionalize_cython_test(unittest.TestCase):
"""
Make sure that the coregionalize kernel work with and without cython enabled
@ -654,42 +654,44 @@ class Coregionalize_cython_test(unittest.TestCase):
def test_sym(self):
dL_dK = np.random.randn(self.N1, self.N1)
GPy.util.config.config.set('cython', 'working', 'True')
K_cython = self.k.K(self.X)
K_cython = self.k._K_cython(self.X)
self.k.update_gradients_full(dL_dK, self.X)
grads_cython = self.k.gradient.copy()
GPy.util.config.config.set('cython', 'working', 'False')
K_numpy = self.k.K(self.X)
K_numpy = self.k._K_numpy(self.X)
# Nasty hack to ensure the numpy version is used for update_gradients
# If this test is running, cython is working, so override the cython
# function with the numpy function
_gradient_reduce_cython = self.k._gradient_reduce_cython
self.k._gradient_reduce_cython = self.k._gradient_reduce_numpy
self.k.update_gradients_full(dL_dK, self.X)
# Undo hack
self.k._gradient_reduce_cython = _gradient_reduce_cython
grads_numpy = self.k.gradient.copy()
self.assertTrue(np.allclose(K_numpy, K_cython))
self.assertTrue(np.allclose(grads_numpy, grads_cython))
#reset the cython state for any other tests
GPy.util.config.config.set('cython', 'working', 'true')
def test_nonsym(self):
dL_dK = np.random.randn(self.N1, self.N2)
GPy.util.config.config.set('cython', 'working', 'True')
K_cython = self.k.K(self.X, self.X2)
K_cython = self.k._K_cython(self.X, self.X2)
self.k.gradient = 0.
self.k.update_gradients_full(dL_dK, self.X, self.X2)
grads_cython = self.k.gradient.copy()
GPy.util.config.config.set('cython', 'working', 'False')
K_numpy = self.k.K(self.X, self.X2)
K_numpy = self.k._K_numpy(self.X, self.X2)
self.k.gradient = 0.
# Same hack as in test_sym (Line 639)
_gradient_reduce_cython = self.k._gradient_reduce_cython
self.k._gradient_reduce_cython = self.k._gradient_reduce_numpy
self.k.update_gradients_full(dL_dK, self.X, self.X2)
# Undo hack
self.k._gradient_reduce_cython = _gradient_reduce_cython
grads_numpy = self.k.gradient.copy()
self.assertTrue(np.allclose(K_numpy, K_cython))
self.assertTrue(np.allclose(grads_numpy, grads_cython))
#reset the cython state for any other tests
GPy.util.config.config.set('cython', 'working', 'true')
class KernelTestsProductWithZeroValues(unittest.TestCase):