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[sparse gp] memory overflow with big data, iterating over dimensions now

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mzwiessele 2015-04-20 16:02:59 +02:00
parent 2d39afd0a5
commit e7650c8a90
1 changed files with 8 additions and 1 deletions
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9
GPy/core/sparse_gp.py
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@ -10,6 +10,7 @@ from .parameterization.variational import VariationalPosterior, NormalPosterior
from ..util.linalg import mdot
import logging
import itertools
logger = logging.getLogger("sparse gp")
class SparseGP(GP):
@ -135,7 +136,13 @@ class SparseGP(GP):
var = var
else:
Kxx = kern.Kdiag(Xnew)
var = (Kxx - np.sum(np.dot(np.atleast_3d(self.posterior.woodbury_inv).T, Kx) * Kx[None,:,:], 1)).T
if self.posterior.woodbury_inv.ndim == 2:
var = Kxx - np.sum(np.dot(self.posterior.woodbury_inv.T, Kx) * Kx, 0)
elif self.posterior.woodbury_inv.ndim == 3:
var = np.empty((Kxx.shape[0],self.posterior.woodbury_inv.shape[2]))
for i in range(var.shape[1]):
var[:, i] = (Kxx - (np.sum(np.dot(self.posterior.woodbury_inv[:, :, i].T, Kx) * Kx, 0)))
var = var
#add in the mean function
if self.mean_function is not None:
mu += self.mean_function.f(Xnew)