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improve the stability of parallel inference code

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This commit is contained in:
Zhenwen Dai 2015-08-17 17:49:37 +01:00
parent 5c35d70a56
commit 097b048100
1 changed files with 13 additions and 8 deletions
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21
GPy/inference/latent_function_inference/var_dtc_parallel.py
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@ -172,18 +172,23 @@ class VarDTC_minibatch(LatentFunctionInference):
if not np.isfinite(Kmm).all(): if not np.isfinite(Kmm).all():
print(Kmm) print(Kmm)
Lm = jitchol(Kmm) Lm = jitchol(Kmm)
LmInv = dtrtri(Lm)
LmInvPsi2LmInvT = backsub_both_sides(Lm,psi2_full,transpose='right') LmInvPsi2LmInvT = LmInv.dot(psi2_full.dot(LmInv.T))
Lambda = np.eye(Kmm.shape[0])+LmInvPsi2LmInvT Lambda = np.eye(Kmm.shape[0])+LmInvPsi2LmInvT
LL = jitchol(Lambda) LL = jitchol(Lambda)
LLInv = dtrtri(LL)
logdet_L = 2.*np.sum(np.log(np.diag(LL))) logdet_L = 2.*np.sum(np.log(np.diag(LL)))
b = dtrtrs(LL,dtrtrs(Lm,psi1Y_full.T)[0])[0] LmLLInv = LLInv.dot(LmInv)
b = psi1Y_full.dot(LmLLInv.T)
bbt = np.square(b).sum() bbt = np.square(b).sum()
v = dtrtrs(Lm,dtrtrs(LL,b,trans=1)[0],trans=1)[0] v = b.dot(LmLLInv).T
LLinvPsi1TYYTPsi1LLinvT = tdot(b.T)
tmp = -backsub_both_sides(LL, tdot(b)+output_dim*np.eye(input_dim), transpose='left')
dL_dpsi2R = backsub_both_sides(Lm, tmp+output_dim*np.eye(input_dim), transpose='left')/2. tmp = -LLInv.T.dot(LLinvPsi1TYYTPsi1LLinvT+output_dim*np.eye(input_dim)).dot(LLInv)
dL_dpsi2R = LmInv.T.dot(tmp+output_dim*np.eye(input_dim)).dot(LmInv)/2.
# Cache intermediate results # Cache intermediate results
self.midRes['dL_dpsi2R'] = dL_dpsi2R self.midRes['dL_dpsi2R'] = dL_dpsi2R
self.midRes['v'] = v self.midRes['v'] = v
@ -201,7 +206,7 @@ class VarDTC_minibatch(LatentFunctionInference):
# Compute dL_dKmm # Compute dL_dKmm
#====================================================================== #======================================================================
dL_dKmm = dL_dpsi2R - output_dim*backsub_both_sides(Lm, LmInvPsi2LmInvT, transpose='left')/2. dL_dKmm = dL_dpsi2R - output_dim*LmInv.T.dot(LmInvPsi2LmInvT).dot(LmInv)/2.
#====================================================================== #======================================================================
# Compute the Posterior distribution of inducing points p(u|Y) # Compute the Posterior distribution of inducing points p(u|Y)