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Dont call parameters_changed ever yourself anymore and parameters are now inplace once in memory

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Max Zwiessele 2014-03-04 17:32:46 +00:00
parent 56d749ded8
commit 0df263956f
21 changed files with 601 additions and 284 deletions
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15
GPy/core/sparse_gp.py
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@ -48,7 +48,6 @@ class SparseGP(GP):
GP.__init__(self, X, Y, kernel, likelihood, inference_method=inference_method, name=name)
self.add_parameter(self.Z, index=0)
self.parameters_changed()
def has_uncertain_inputs(self):
return isinstance(self.X, VariationalPosterior)
@ -60,11 +59,9 @@ class SparseGP(GP):
#gradients wrt kernel
dL_dKmm = self.grad_dict.pop('dL_dKmm')
self.kern.update_gradients_full(dL_dKmm, self.Z, None)
target = np.zeros(self.kern.size)
self.kern._collect_gradient(target)
target = self.kern.gradient.copy()
self.kern.update_gradients_expectations(variational_posterior=self.X, Z=self.Z, **self.grad_dict)
self.kern._collect_gradient(target)
self.kern._set_gradient(target)
self.kern.gradient += target
#gradients wrt Z
self.Z.gradient = self.kern.gradients_X(dL_dKmm, self.Z)
@ -72,14 +69,12 @@ class SparseGP(GP):
self.grad_dict['dL_dpsi1'], self.grad_dict['dL_dpsi2'], Z=self.Z, variational_posterior=self.X)
else:
#gradients wrt kernel
target = np.zeros(self.kern.size)
self.kern.update_gradients_diag(self.grad_dict['dL_dKdiag'], self.X)
self.kern._collect_gradient(target)
target = self.kern.gradient.copy()
self.kern.update_gradients_full(self.grad_dict['dL_dKnm'], self.X, self.Z)
self.kern._collect_gradient(target)
target += self.kern.gradient
self.kern.update_gradients_full(self.grad_dict['dL_dKmm'], self.Z, None)
self.kern._collect_gradient(target)
self.kern._set_gradient(target)
self.kern.gradient += target
#gradients wrt Z
self.Z.gradient = self.kern.gradients_X(self.grad_dict['dL_dKmm'], self.Z)