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[GPU] psi1 after debug

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This commit is contained in:
Zhenwen Dai 2014-03-26 17:09:01 +00:00
parent e4d19120cd
commit bc59cb8b22
5 changed files with 157 additions and 40 deletions
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28
GPy/inference/latent_function_inference/var_dtc_gpu.py
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@ -52,17 +52,17 @@ class VarDTC_GPU(object):
def _initGPUCache(self, num_inducing, output_dim):
if self.gpuCache == None:
self.gpuCache = {# inference_likelihood
'Kmm_gpu' :gpuarray.empty((num_inducing,num_inducing),np.float64),
'Lm_gpu' :gpuarray.empty((num_inducing,num_inducing),np.float64),
'ones_gpu' :gpuarray.empty(num_inducing, np.float64),
'LL_gpu' :gpuarray.empty((num_inducing,num_inducing),np.float64),
'b_gpu' :gpuarray.empty((num_inducing,output_dim),np.float64),
'v_gpu' :gpuarray.empty((num_inducing,output_dim),np.float64),
'vvt_gpu' :gpuarray.empty((num_inducing,num_inducing),np.float64),
'KmmInvPsi2LLInvT_gpu' :gpuarray.empty((num_inducing,num_inducing),np.float64),
'KmmInvPsi2P_gpu' :gpuarray.empty((num_inducing,num_inducing),np.float64),
'dL_dpsi2R_gpu' :gpuarray.empty((num_inducing,num_inducing),np.float64),
'dL_dKmm_gpu' :gpuarray.empty((num_inducing,num_inducing),np.float64),
'Kmm_gpu' :gpuarray.empty((num_inducing,num_inducing),np.float64,order='F'),
'Lm_gpu' :gpuarray.empty((num_inducing,num_inducing),np.float64,order='F'),
'ones_gpu' :gpuarray.empty(num_inducing, np.float64,order='F'),
'LL_gpu' :gpuarray.empty((num_inducing,num_inducing),np.float64,order='F'),
'b_gpu' :gpuarray.empty((num_inducing,output_dim),np.float64,order='F'),
'v_gpu' :gpuarray.empty((num_inducing,output_dim),np.float64,order='F'),
'vvt_gpu' :gpuarray.empty((num_inducing,num_inducing),np.float64,order='F'),
'KmmInvPsi2LLInvT_gpu' :gpuarray.empty((num_inducing,num_inducing),np.float64,order='F'),
'KmmInvPsi2P_gpu' :gpuarray.empty((num_inducing,num_inducing),np.float64,order='F'),
'dL_dpsi2R_gpu' :gpuarray.empty((num_inducing,num_inducing),np.float64,order='F'),
'dL_dKmm_gpu' :gpuarray.empty((num_inducing,num_inducing),np.float64,order='F'),
# inference_minibatch
}
self.gpuCache['ones_gpu'].fill(1.0)
@ -134,11 +134,11 @@ class VarDTC_GPU(object):
if het_noise:
beta_slice = beta[n_start:n_end]
psi0_full += (beta_slice*psi0).sum()
psi1Y_full += np.dot(psi1,beta_slice[:,None]*Y_slice) # DxM
psi1Y_full += np.dot(psi1.T,beta_slice[:,None]*Y_slice) # MxD
YRY_full += (beta_slice*np.square(Y_slice).sum(axis=-1)).sum()
else:
psi0_full += psi0.sum()
psi1Y_full += np.dot(psi1,Y_slice) # DxM
psi1Y_full += np.dot(psi1.T,Y_slice) # MxD
if uncertain_inputs:
@ -275,7 +275,7 @@ class VarDTC_GPU(object):
# Compute the Posterior distribution of inducing points p(u|Y)
#======================================================================
post = Posterior(woodbury_inv=KmmInvPsi2P_gpu.get(), woodbury_vector=v_gpu.get(), K=Kmm_gpu.get(), mean=None, cov=None, K_chol=Lm.get())
post = Posterior(woodbury_inv=KmmInvPsi2P_gpu.get(), woodbury_vector=v_gpu.get(), K=Kmm_gpu.get(), mean=None, cov=None, K_chol=Lm_gpu.get())
return logL, dL_dKmm, post