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[spgp minibatch] linear calls the right psicomps and add kernel

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Max Zwiessele 2015-09-04 13:30:15 +01:00
parent bf3c579cc6
commit 8fa5b67089
5 changed files with 16 additions and 13 deletions
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6
GPy/models/sparse_gp_minibatch.py
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@ -171,8 +171,7 @@ class SparseGPMiniBatch(SparseGP):
variational_posterior=self.X,
Z=self.Z, dL_dpsi0=full_values['dL_dpsi0'],
dL_dpsi1=full_values['dL_dpsi1'],
dL_dpsi2=full_values['dL_dpsi2'],
psi0=self.psi0, psi1=self.psi1, psi2=self.psi2)
dL_dpsi2=full_values['dL_dpsi2'])
self.kern.gradient += kgrad
@ -182,8 +181,7 @@ class SparseGPMiniBatch(SparseGP):
variational_posterior=self.X,
Z=self.Z, dL_dpsi0=full_values['dL_dpsi0'],
dL_dpsi1=full_values['dL_dpsi1'],
dL_dpsi2=full_values['dL_dpsi2'],
psi0=self.psi0, psi1=self.psi1, psi2=self.psi2)
dL_dpsi2=full_values['dL_dpsi2'])
else:
#gradients wrt kernel
self.kern.update_gradients_diag(full_values['dL_dKdiag'], self.X)