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a little tidying

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This commit is contained in:
James Hensman 2015-05-28 08:35:55 +01:00
parent dade88ea36
commit 08c45741d5
1 changed files with 4 additions and 4 deletions
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8
GPy/inference/latent_function_inference/svgp.py
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@ -22,8 +22,8 @@ class SVGP(LatentFunctionInference):
Sv = np.zeros((num_outputs, num_inducing, num_inducing))
for i in range(num_outputs):
Sv[i] = Lv[i].dot(Lv[i].T)
logdetS = np.array([2.*np.sum(np.log(np.abs(np.diag(Lv[i,:,:])))) for i in range(Lv.shape[0])])
traceS = np.array([np.sum(np.square(np.diag(Lv[i,:,:]))) for i in range(Lv.shape[0])])
logdetS = np.array([2.*np.sum(np.log(np.abs(np.diag(Lv[i])))) for i in range(num_outputs)])
traceS = np.array([np.sum(np.square(np.diag(Lv[i]))) for i in range(num_outputs)])
#compute kernel related stuff
@ -43,7 +43,7 @@ class SVGP(LatentFunctionInference):
var += (Knn_diag - np.sum(np.square(A),1))[:,None]
#compute the KL term
KL = -0.5*logdetS.sum() + 0.5*np.sum(np.square(q_v_mean)) + 0.5*traceS.sum()
KL = -0.5*logdetS.sum() + 0.5*np.sum(np.square(q_v_mean)) + 0.5*traceS.sum() - 0.5*num_inducing*output_dim
dL_dmv = -q_v_mean*1
dL_dL = np.zeros_like(Lv)
for i in range(num_outputs):
@ -75,7 +75,7 @@ class SVGP(LatentFunctionInference):
#L
for i in range(num_outputs):
dL_dL[i] += 2*np.dot(Lv[i].T, A.T).dot(A*dF_dv[:,i][:,None]).T
dL_dL[i] += 2.*np.dot(Lv[i].T, A.T).dot(A*dF_dv[:,i][:,None]).T
#R
dL_dR,_ = linalg.dtrtrs(R, -dL_dA_via_v.T.dot(A), trans=1, lower=1)