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added kernel tests for gradients_XX

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alessandratosi 2016-04-20 14:50:39 +01:00
parent a9c8ef817a
commit a1e4728f8a
5 changed files with 90 additions and 34 deletions
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57
GPy/testing/kernel_tests.py
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@ -101,7 +101,21 @@ class Kern_check_dKdiag_dX(Kern_check_dK_dX):
def parameters_changed(self):
self.X.gradient[:] = self.kernel.gradients_X_diag(self.dL_dK.diagonal(), self.X)
class Kern_check_d2K_dXdX(Kern_check_model):
"""This class allows gradient checks for the secondderivative of a kernel with respect to X. """
def __init__(self, kernel=None, dL_dK=None, X=None, X2=None):
Kern_check_model.__init__(self,kernel=kernel,dL_dK=dL_dK, X=X, X2=X2)
self.X = Param('X',X)
self.link_parameter(self.X)
def log_likelihood(self):
return np.sum(self.kernel.gradients_X(self.dL_dK,self.X, self.X2))
def parameters_changed(self):
self.X.gradient[:] = self.kernel.gradients_XX(self.dL_dK, self.X, self.X2,cov=True).sum(0).sum(1)
# class Kern_check_d2Kdiag_dXdX(Kern_check_model):
# """This class allows gradient checks for the secondderivative of a kernel diagonal with respect to X. """
def check_kernel_gradient_functions(kern, X=None, X2=None, output_ind=None, verbose=False, fixed_X_dims=None):
"""
@ -239,6 +253,49 @@ def check_kernel_gradient_functions(kern, X=None, X2=None, output_ind=None, verb
assert(result)
return False
if verbose:
print("Checking gradients of dK(X, X) wrt X.")
try:
testmodel = Kern_check_d2K_dXdX(kern, X=X, X2=None)
if fixed_X_dims is not None:
testmodel.X[:,fixed_X_dims].fix()
result = testmodel.checkgrad(verbose=verbose)
except NotImplementedError:
result=True
if verbose:
print(("gradients_XX not implemented for " + kern.name))
if result and verbose:
print("Check passed.")
if not result:
print(("Gradient of dK(X, X) wrt X failed for " + kern.name + " covariance function. Gradient values as follows:"))
testmodel.checkgrad(verbose=True)
assert(result)
pass_checks = False
return False
if verbose:
print("Checking gradients of dK(X, X2) wrt X.")
try:
testmodel = Kern_check_d2K_dXdX(kern, X=X, X2=X2)
if fixed_X_dims is not None:
testmodel.X[:,fixed_X_dims].fix()
result = testmodel.checkgrad(verbose=verbose)
except NotImplementedError:
result=True
if verbose:
print(("gradients_XX not implemented for " + kern.name))
if result and verbose:
print("Check passed.")
if not result:
print(("Gradient of dK(X, X2) wrt X failed for " + kern.name + " covariance function. Gradient values as follows:"))
testmodel.checkgrad(verbose=True)
assert(result)
pass_checks = False
return False
# if verbose:
# print("Checking gradients of dKdiag(X, X) wrt X.")
return pass_checks