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non-working grads in linear

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James Hensman 2014-02-21 11:25:33 +00:00
parent 81e0861a60
commit 0dc9a32ba3
3 changed files with 14 additions and 11 deletions
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21
GPy/kern/_src/linear.py
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@ -47,7 +47,7 @@ class Linear(Kern):
self.variances = Param('variances', variances, Logexp())
self.add_parameter(self.variances)
self.variances.add_observer(self._on_changed)
self.variances.add_observer(self, self._on_changed)
def _on_changed(self, obj):
#TODO: move this to base class? isnt it jst for the caching?
@ -82,9 +82,9 @@ class Linear(Kern):
self._collect_gradient(target)
self.update_gradients_full(dL_dKmm, Z, None)
self._collect_gradient(target)
return target
self._set_gradient(target)
def update_gradients_full(self, dL_dK, X):
def update_gradients_full(self, dL_dK, X, X2=None):
if self.ARD:
if X2 is None:
self.variances.gradient = np.array([np.sum(dL_dK * tdot(X[:, i:i + 1])) for i in range(self.input_dim)])
@ -130,16 +130,19 @@ class Linear(Kern):
def update_gradients_variational(self, dL_dKmm, dL_dpsi0, dL_dpsi1, dL_dpsi2, mu, S, Z):
# psi0:
tmp = dL_dpsi0[:, None] * self._mu2S(mu, S)
if self.ARD: self.variances.gradient[:] = tmp.sum(0)
else: self.variances.gradient[:] = tmp.sum()
if self.ARD: grad = tmp.sum(0)
else: grad = np.atleast_1d(tmp.sum())
#psi1
self.variances.gradient += self._param_grad_helper(dL_dpsi1, mu, Z)
self.update_gradients_full(dL_dpsi1, mu, Z)
grad += self.variances.gradient
#psi2
tmp = dL_dpsi2[:, :, :, None] * (self._ZAinner(mu, S, Z)[:, :, None, :] * (2. * Z)[None, None, :, :])
if self.ARD: self.variances.gradient += tmp.sum(0).sum(0).sum(0)
else: self.variances.gradient += tmp.sum()
if self.ARD: grad += tmp.sum(0).sum(0).sum(0)
else: grad += tmp.sum()
#from Kmm
self.variances.gradient += self._param_grad_helper(dL_dKmm, Z, None)
self.update_gradients_full(dL_dpsi1, mu, Z)
grad += self.variances.gradient
self._set_gradient(grad)
def gradients_Z_variational(self, dL_dKmm, dL_dpsi0, dL_dpsi1, dL_dpsi2, mu, S, Z):
# Kmm