apunkt/GPy
1
0
Fork 0
mirror of https://github.com/SheffieldML/GPy.git synced 2026-05-09 20:12:38 +02:00
Code Issues Projects Releases Packages Wiki Activity Actions

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

Browse source
This commit is contained in:
mzwiessele 2015-04-20 16:02:59 +02:00
parent 2d39afd0a5
commit e7650c8a90
1 changed files with 8 additions and 1 deletions
Download patch file Download diff file Expand all files Collapse all files

9
GPy/core/sparse_gp.py
View file

@ -10,6 +10,7 @@ from .parameterization.variational import VariationalPosterior, NormalPosterior
from ..util.linalg import mdot from ..util.linalg import mdot
import logging import logging
import itertools
logger = logging.getLogger("sparse gp") logger = logging.getLogger("sparse gp")
class SparseGP(GP): class SparseGP(GP):
@ -135,7 +136,13 @@ class SparseGP(GP):
var = var var = var
else: else:
Kxx = kern.Kdiag(Xnew) 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 #add in the mean function
if self.mean_function is not None: if self.mean_function is not None:
mu += self.mean_function.f(Xnew) mu += self.mean_function.f(Xnew)