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Added svgp in partially broken state ready for multiouputs

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Alan Saul 2014-12-22 12:00:16 +00:00
parent 935f2016db
commit 7ba2e2ed08
1 changed files with 8 additions and 7 deletions
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15
GPy/inference/latent_function_inference/svgp.py
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@ -10,15 +10,16 @@ class SVGP(LatentFunctionInference):
num_inducing = Z.shape[0]
#expand cholesky representation
L = choleskies.flat_to_triang(q_u_chol[:,None]).squeeze()
S = L.dot(L.T)
Si,_ = linalg.dpotri(np.asfortranarray(L), lower=1)
logdetS = 2.*np.sum(np.log(np.abs(np.diag(L))))
L = choleskies.flat_to_triang(q_u_chol)
S = np.einsum('ijk,ljk->ilk', L, L) #L.dot(L.T)
#Si,_ = linalg.dpotri(np.asfortranarray(L), lower=1)
Si = choleskies.multiple_dpotri(L)
logdetS = np.array([2.*np.sum(np.log(np.abs(np.diag(L[:,:,i])))) for i in range(L.shape[-1])])
if np.any(np.isinf(Si)):
print "warning:Cholesky representation unstable"
S = S + np.eye(S.shape[0])*1e-5*np.max(np.max(S))
Si, Lnew, _,_ = linalg.pdinv(S)
raise ValueError("Cholesky representation unstable")
#S = S + np.eye(S.shape[0])*1e-5*np.max(np.max(S))
#Si, Lnew, _,_ = linalg.pdinv(S)
#compute kernel related stuff
Kmm = kern.K(Z)