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slicing now returns the right shape, when computing derivative wrt X or Z

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This commit is contained in:
Max Zwiessele 2014-03-17 15:43:09 +00:00
parent f88b4c92e8
commit 62d594d977
3 changed files with 50 additions and 18 deletions
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14
GPy/kern/_src/add.py
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@ -58,7 +58,13 @@ class Add(CombinationKernel):
:type X2: np.ndarray (num_inducing x input_dim)"""
target = np.zeros(X.shape)
[target.__setitem__([Ellipsis, p.active_dims], target[:, p.active_dims]+p.gradients_X(dL_dK, X, X2)) for p in self.parts]
[target.__iadd__(p.gradients_X(dL_dK, X, X2)) for p in self.parts]
return target
def gradients_X_diag(self, dL_dKdiag, X):
target = np.zeros(X.shape)
[target.__iadd__(p.gradients_X_diag(dL_dKdiag, X)) for p in self.parts]
#[target.__setitem__([Ellipsis, p.active_dims], target[:, p.active_dims]+p.gradients_X(dL_dK, X, X2)) for p in self.parts]
return target
def psi0(self, Z, variational_posterior):
@ -131,7 +137,7 @@ class Add(CombinationKernel):
eff_dL_dpsi1 += dL_dpsi2.sum(1) * p2.variance * 2.
else:
eff_dL_dpsi1 += dL_dpsi2.sum(1) * p2.psi1(Z, variational_posterior) * 2.
target[:, p1.active_dims] += p1.gradients_Z_expectations(eff_dL_dpsi1, dL_dpsi2, Z, variational_posterior)
target += p1.gradients_Z_expectations(eff_dL_dpsi1, dL_dpsi2, Z, variational_posterior)
return target
def gradients_qX_expectations(self, dL_dpsi0, dL_dpsi1, dL_dpsi2, Z, variational_posterior):
@ -151,8 +157,8 @@ class Add(CombinationKernel):
else:
eff_dL_dpsi1 += dL_dpsi2.sum(1) * p2.psi1(Z, variational_posterior) * 2.
a, b = p1.gradients_qX_expectations(dL_dpsi0, eff_dL_dpsi1, dL_dpsi2, Z, variational_posterior)
target_mu[:, p1.active_dims] += a
target_S[:, p1.active_dims] += b
target_mu += a
target_S += b
return target_mu, target_S
def _getstate(self):