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messing with kernels

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This commit is contained in:
James Hensman 2014-02-25 17:15:38 +00:00
parent 6a667e749f
commit 80acca640f
8 changed files with 66 additions and 57 deletions
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11
GPy/kern/_src/rbf.py
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@ -55,10 +55,7 @@ class RBF(Stationary):
self._psi_computations(Z, mu, S)
return self._psi2
def update_gradients_variational(self, dL_dKmm, dL_dpsi0, dL_dpsi1, dL_dpsi2, Z, variational_posterior):
#contributions from Kmm
sself.update_gradients_full(dL_dKmm, Z)
def update_gradients_expectations(self, dL_dpsi0, dL_dpsi1, dL_dpsi2, Z, variational_posterior):
mu = variational_posterior.mean
S = variational_posterior.variance
self._psi_computations(Z, mu, S)
@ -87,7 +84,7 @@ class RBF(Stationary):
else:
self.lengthscale.gradient += dpsi2_dlength.sum(0).sum(0).sum(0)
def gradients_Z_variational(self, dL_dKmm, dL_dpsi0, dL_dpsi1, dL_dpsi2, Z, variational_posterior):
def gradients_Z_expectations(self, dL_dpsi1, dL_dpsi2, Z, variational_posterior):
mu = variational_posterior.mean
S = variational_posterior.variance
self._psi_computations(Z, mu, S)
@ -104,11 +101,9 @@ class RBF(Stationary):
dZ = self._psi2[:, :, :, None] * (term1[None] + term2)
grad += 2*(dL_dpsi2[:, :, :, None] * dZ).sum(0).sum(0)
grad += self.gradients_X(dL_dKmm, Z, None)
return grad
def gradients_q_variational(self, dL_dKmm, dL_dpsi0, dL_dpsi1, dL_dpsi2, Z, variational_posterior):
def gradients_qX_expectations(self, dL_dpsi0, dL_dpsi1, dL_dpsi2, Z, variational_posterior):
mu = variational_posterior.mean
S = variational_posterior.variance
self._psi_computations(Z, mu, S)