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derivatives working in DTC

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This commit is contained in:
James Hensman 2014-02-12 11:13:24 +00:00
parent 32deb2085d
commit 34dec0ade3
1 changed files with 7 additions and 14 deletions
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21
GPy/inference/latent_function_inference/dtc.py
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@ -40,9 +40,9 @@ class DTC(object):
Kmmi, L, Li, _ = pdinv(Kmm)
# Compute A
LiUT, _ = dtrtrs(L, U.T*np.sqrt(beta), lower=1)
A_I = tdot(LiUT)
A = A_I + np.eye(num_inducing)
#LiUT, _ = dtrtrs(L, U.T*np.sqrt(beta), lower=1)
LiUT = np.dot(Li, U.T)*np.sqrt(beta)
A = tdot(LiUT) + np.eye(num_inducing)
# factor A
LA = jitchol(A)
@ -63,24 +63,17 @@ class DTC(object):
0.5*np.sum(np.square(b))
# Compute dL_dKmm
tmp, _ = dtrtrs(L, A_I, lower=1, trans=1)
dL_dK, _ = dtrtrs(L, tmp.T, lower=1, trans=0)
tmp, _ = dtrtrs(LA, tmp.T, lower=1, trans=1)
dL_dK -= tdot(tmp.T)
dL_dK *= output_dim
dL_dK -= tdot(v)
dL_dK /=2.
vvT_P = tdot(v.reshape(-1,1)) + P
dL_dK = 0.5*(Kmmi - vvT_P)
# Compute dL_dU
vvT_P = tdot(v.reshape(-1,1)) + P
vY = np.dot(v.reshape(-1,1),Y.T)
dL_dU = vY + np.dot(vvT_P, U.T)
dL_dU = vY - np.dot(vvT_P, U.T)
dL_dU *= beta
#compute dL_dR
Uv = np.dot(U, v)
dL_dR = 0.5*(np.sum(U*np.dot(U,P), 1) - beta * np.sum(np.square(Y), 1) - 2.*np.sum(Uv*Y, 1) + np.sum(np.square(Uv), 1)
)*beta**2
dL_dR = 0.5*(np.sum(U*np.dot(U,P), 1) - 1./beta + np.sum(np.square(Y), 1) - 2.*np.sum(Uv*Y, 1) + np.sum(np.square(Uv), 1))*beta**2
grad_dict = {'dL_dKmm': dL_dK, 'dL_dKdiag':np.zeros_like(Knn), 'dL_dKnm':dL_dU.T}