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bug fix for inferenceX

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This commit is contained in:
Zhenwen Dai 2014-11-03 14:11:46 +00:00
parent 78b50db138
commit 24ad425a1b
1 changed files with 3 additions and 2 deletions
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5
GPy/inference/latent_function_inference/inferenceX.py
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@ -95,11 +95,11 @@ class InferenceX(Model):
output_dim = self.valid_dim.sum() output_dim = self.valid_dim.sum()
self.dL_dpsi2 = beta*(output_dim*self.posterior.woodbury_inv - np.einsum('md,od->mo',wv, wv))/2. self.dL_dpsi2 = beta*(output_dim*self.posterior.woodbury_inv - np.einsum('md,od->mo',wv, wv))/2.
self.dL_dpsi1 = beta*np.dot(self.Y[:,self.valid_dim], wv.T) self.dL_dpsi1 = beta*np.dot(self.Y[:,self.valid_dim], wv.T)
self.dL_dpsi0 = -output_dim * beta/2.* np.ones(self.Y.shape[0]) self.dL_dpsi0 = - beta/2.* np.ones(self.Y.shape[0])
else: else:
self.dL_dpsi2 = beta*(output_dim*self.posterior.woodbury_inv - np.einsum('md,od->mo',wv, wv))/2. self.dL_dpsi2 = beta*(output_dim*self.posterior.woodbury_inv - np.einsum('md,od->mo',wv, wv))/2.
self.dL_dpsi1 = beta*np.dot(self.Y, wv.T) self.dL_dpsi1 = beta*np.dot(self.Y, wv.T)
self.dL_dpsi0 = -output_dim * beta/2.* np.ones(self.Y.shape[0]) self.dL_dpsi0 = -beta/2.* np.ones(self.Y.shape[0]) #self.dL_dpsi0[:] = 0
def parameters_changed(self): def parameters_changed(self):
psi0 = self.kern.psi0(self.Z, self.X) psi0 = self.kern.psi0(self.Z, self.X)
@ -121,6 +121,7 @@ class InferenceX(Model):
KL_div = self.variational_prior.KL_divergence(self.X) KL_div = self.variational_prior.KL_divergence(self.X)
# update for the KL divergence # update for the KL divergence
self.variational_prior.update_gradients_KL(self.X) self.variational_prior.update_gradients_KL(self.X)
self._log_marginal_likelihood += -KL_div
def log_likelihood(self): def log_likelihood(self):
return self._log_marginal_likelihood return self._log_marginal_likelihood