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Reindented, did some profiling which looks promising

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This commit is contained in:
Alan Saul 2015-09-02 10:46:30 +03:00
parent 6ea3310c74
commit 81ef734908
2 changed files with 9 additions and 12 deletions
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2
GPy/kern/_src/psi_comp/rbf_psi_comp.py
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@ -68,7 +68,6 @@ def __psi2computations(variance, lengthscale, Z, mu, S):
_psi2 = variance*variance*np.exp(_psi2_logdenom[:,None,None]+_psi2_exp1[None,:,:]+_psi2_exp2) _psi2 = variance*variance*np.exp(_psi2_logdenom[:,None,None]+_psi2_exp1[None,:,:]+_psi2_exp2)
return _psi2 return _psi2
@profile
def psiDerivativecomputations(dL_dpsi0, dL_dpsi1, dL_dpsi2, variance, lengthscale, Z, variational_posterior, def psiDerivativecomputations(dL_dpsi0, dL_dpsi1, dL_dpsi2, variance, lengthscale, Z, variational_posterior,
psi0=None, psi1=None, psi2=None, Lpsi0=None, Lpsi1=None, Lpsi2=None): psi0=None, psi1=None, psi2=None, Lpsi0=None, Lpsi1=None, Lpsi2=None):
ARD = (len(lengthscale)!=1) ARD = (len(lengthscale)!=1)
@ -122,7 +121,6 @@ def __psi1compDer(dL_dpsi1, variance, lengthscale, Z, mu, S, psi1=None, Lpsi1=No
return _dL_dvar, _dL_dl, _dL_dZ, _dL_dmu, _dL_dS return _dL_dvar, _dL_dl, _dL_dZ, _dL_dmu, _dL_dS
@profile
def __psi2compDer(dL_dpsi2, variance, lengthscale, Z, mu, S, psi2=None, Lpsi2=None): def __psi2compDer(dL_dpsi2, variance, lengthscale, Z, mu, S, psi2=None, Lpsi2=None):
""" """
Z - MxQ Z - MxQ

1
GPy/models/bayesian_gplvm_minibatch.py
View file

@ -146,7 +146,6 @@ class BayesianGPLVMMiniBatch(SparseGPMiniBatch):
full_values['meangrad'] = np.zeros((self.X.shape[0], self.X.shape[1])) full_values['meangrad'] = np.zeros((self.X.shape[0], self.X.shape[1]))
full_values['vargrad'] = np.zeros((self.X.shape[0], self.X.shape[1])) full_values['vargrad'] = np.zeros((self.X.shape[0], self.X.shape[1]))
#FIXME Hack
full_values['dL_dpsi0'] = ObsAr(np.zeros(self.X.shape[0])) full_values['dL_dpsi0'] = ObsAr(np.zeros(self.X.shape[0]))
full_values['dL_dpsi1'] = ObsAr(np.zeros((self.X.shape[0], self.Z.shape[0]))) full_values['dL_dpsi1'] = ObsAr(np.zeros((self.X.shape[0], self.Z.shape[0])))
full_values['dL_dpsi2'] = ObsAr(np.zeros((self.Z.shape[0], self.Z.shape[0]))) full_values['dL_dpsi2'] = ObsAr(np.zeros((self.Z.shape[0], self.Z.shape[0])))