apunkt/GPy
1
0
Fork 0
mirror of https://github.com/SheffieldML/GPy.git synced 2026-05-10 12:32:40 +02:00
Code Issues Projects Releases Packages Wiki Activity Actions

merge with current GPy devel

Browse source
This commit is contained in:
Zhenwen Dai 2015-12-09 17:27:06 +00:00
commit c0e6978054
164 changed files with 733 additions and 5931 deletions
Download patch file Download diff file Expand all files Collapse all files

8
GPy/models/ss_gplvm.py
View file

@ -7,7 +7,7 @@ from ..core.sparse_gp_mpi import SparseGP_MPI
from .. import kern
from ..core.parameterization import Param
from ..likelihoods import Gaussian
from ..core.parameterization.variational import SpikeAndSlabPrior, SpikeAndSlabPosterior,VariationalPrior
from GPy.core.parameterization.variational import SpikeAndSlabPrior, SpikeAndSlabPosterior,VariationalPrior
from ..inference.latent_function_inference.var_dtc_parallel import update_gradients, VarDTC_minibatch
from ..kern.src.psi_comp.ssrbf_psi_gpucomp import PSICOMP_SSRBF_GPU
@ -19,7 +19,7 @@ class IBPPosterior(SpikeAndSlabPosterior):
"""
binary_prob : the probability of the distribution on the slab part.
"""
from ..core.parameterization.transformations import Logexp
from paramz.transformations import Logexp
super(IBPPosterior, self).__init__(means, variances, binary_prob, group_spike=True, name=name)
self.sharedX = sharedX
if sharedX:
@ -60,7 +60,7 @@ class IBPPosterior(SpikeAndSlabPosterior):
class IBPPrior(VariationalPrior):
def __init__(self, input_dim, alpha =2., name='IBPPrior', **kw):
super(IBPPrior, self).__init__(name=name, **kw)
from ..core.parameterization.transformations import Logexp, __fixed__
from paramz.transformations import Logexp, __fixed__
self.input_dim = input_dim
self.variance = 1.
self.alpha = Param('alpha', alpha, __fixed__)
@ -224,4 +224,4 @@ class SSGPLVM(SparseGP_MPI):