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interim svgp commit

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This commit is contained in:
James Hensman 2015-05-15 08:10:34 +01:00
parent 1c294cad40
commit 2249ec06a5
2 changed files with 29 additions and 8 deletions
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19
GPy/inference/latent_function_inference/svgp.py
View file

@ -3,7 +3,7 @@ from ...util import linalg
from ...util import choleskies
import numpy as np
from .posterior import Posterior
from scipy.linalg.blas import dgemm
from scipy.linalg.blas import dgemm, dsymm, dtrmm
class SVGP(LatentFunctionInference):
@ -46,6 +46,13 @@ class SVGP(LatentFunctionInference):
A = np.dot(Kmmi, Kmn)
mu = prior_mean_f + np.dot(A.T, q_u_mean - prior_mean_u)
LA = L.reshape(-1, num_inducing).dot(A).reshape(num_outputs, num_inducing, num_data)
#LA = np.empty((num_outputs, num_inducing, num_data))
#Af = np.asfortranarray(A)
#for Li, LAi in zip(L, LA):
#LAi[:,:] = dtrmm(1., Li.T, Af, side=0, lower=0, trans_a=1, overwrite_b=0)
#stop
#assert np.allclose(LA, LA_)
v = (Knn_diag - np.sum(A*Kmn,0))[:,None] + np.sum(np.square(LA),1).T
@ -83,22 +90,18 @@ class SVGP(LatentFunctionInference):
#derivatives of expected likelihood, assuming zero mean function
Adv = A[None,:,:]*dF_dv.T[:,None,:] # As if dF_Dv is diagonal, D, M, N
Admu = A.dot(dF_dmu)
#AdvA_ = np.dot(Adv, A) # D, M, M
Adv = np.ascontiguousarray(Adv) # makes for faster operations later...
AdvA = np.dot(Adv.reshape(-1, num_data),A.T).reshape(num_outputs, num_inducing, num_inducing )
#assert np.allclose(AdvA, AdvA_, 1e-9)
tmp = np.sum([np.dot(a,s) for a, s in zip(AdvA, S)],0).dot(Kmmi)
dF_dKmm = -Admu.dot(Kmmim.T) + AdvA.sum(0) - tmp - tmp.T
dF_dKmm = 0.5*(dF_dKmm + dF_dKmm.T) # necessary? GPy bug?
tmp = S.reshape(-1, num_inducing).dot(Kmmi).reshape(num_outputs, num_inducing , num_inducing )
#tmp_ = S.dot(Kmmi).swapaxes(1,2)
tmp = 2.*(tmp - np.eye(num_inducing)[None, :,:])
#dF_dKmn_ = np.sum([np.dot(a,b) for a,b in zip(tmp, Adv)],0) + Kmmim.dot(dF_dmu.T)
dF_dKnm = Kmmim.dot(dF_dmu.T).T
assert dF_dKnm.flags['F_CONTIGUOUS'] # needed for dgemm in place call:
assert dF_dKnm.flags['F_CONTIGUOUS'] # needed for dsymm in place call:
for a,b in zip(tmp, Adv):
dgemm(1.0, b.T, a.T, beta=1., c=dF_dKnm, overwrite_c=True)
dsymm(1.0, a.T, b.T, beta=1., side=1, c=dF_dKnm, overwrite_c=True)
dF_dKmn = dF_dKnm.T
dF_dm = Admu

18
GPy/kern/_src/stationary_utils.c
View file

@ -14,6 +14,22 @@ for(nd=0;nd<(D*N);nd++){
} //grad_X
void _lengthscale_grads_unsafe(int N, int M, int Q, double* tmp, double* X, double* X2, double* grad){
int n,m,nm,q,nQ,mQ;
double dist;
#pragma omp parallel for private(n,m,nm,q,nQ,mQ,dist)
for(nm=0; nm<(N*M); nm++){
n = nm/M;
m = nm%M;
nQ = n*Q;
mQ = m*Q;
for(q=0; q<Q; q++){
dist = X[nQ+q]-X2[mQ+q];
grad[q] += tmp[nm]*dist*dist;
}
}
} //lengthscale_grads
void _lengthscale_grads(int N, int M, int Q, double* tmp, double* X, double* X2, double* grad){
int n,m,q;
@ -34,3 +50,5 @@ for(q=0; q<Q; q++){