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new gradient handling way nicer

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Max Zwiessele 2014-01-24 15:07:28 +00:00
parent f0ac290eb3
commit e128059377
6 changed files with 15 additions and 26 deletions
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1
GPy/kern/kern.py
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@ -346,6 +346,7 @@ class kern(Parameterized):
return target
def update_gradients_full(self, dL_dK, X):
[p.update_gradients_full(dL_dK, X) for p in self._parameters_]
pass
def update_gradients_sparse(self, dL_dKmm, dL_dKnm, dL_dKdiag, X, Z):
pass

12
GPy/kern/parts/rbf.py
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@ -80,9 +80,6 @@ class RBF(Kernpart):
self._X, self._X2 = np.empty(shape=(2, 1))
self._Z, self._mu, self._S = np.empty(shape=(3, 1)) # cached versions of Z,mu,S
def K(self, X, X2, target):
self._K_computations(X, X2)
target += self.variance * self._K_dvar
@ -101,11 +98,8 @@ class RBF(Kernpart):
self._psi_computations(Z, mu, S)
target += self._psi2
def update_gradients_full(self, dL_dK, X):
self._K_computations(X, X2)
self._K_computations(X, None)
self.variance.gradient = np.sum(self._K_dvar * dL_dK)
if self.ARD:
self.lengthscale.gradient = self._dL_dlengthscales_via_K(dL_dK, X, None)
@ -123,7 +117,7 @@ class RBF(Kernpart):
self.lengthscales.gradient = self._dL_dlengthscales_via_K(dL_dKnm, X, Z)
else:
self.lengthscale.gradient = (self.variance / self.lengthscale) * np.sum(self._K_dvar * self._K_dist2 * dL_dK)
self.lengthscale.gradient = (self.variance / self.lengthscale) * np.sum(self._K_dvar * self._K_dist2 * dL_dKmm)
#from Kmm
self._K_computations(Z, None)
@ -131,7 +125,7 @@ class RBF(Kernpart):
if self.ARD:
self.lengthscales.gradient += self._dL_dlengthscales_via_K(dL_dKmm, Z, None)
else:
self.lengthscale.gradient += (self.variance / self.lengthscale) * np.sum(self._K_dvar * self._K_dist2 * dL_dK)
self.lengthscale.gradient += (self.variance / self.lengthscale) * np.sum(self._K_dvar * self._K_dist2 * dL_dKmm)
def update_gradients_variational(self, dL_dKmm, dL_dpsi0, dL_dpsi1, dL_dpsi2, mu, S, Z):
self._psi_computations(Z, mu, S)