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chg: fixed naming in variational priors

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Max Zwiessele 2016-10-03 12:19:24 +01:00
parent 59be79e962
commit 543a04dc1b
1 changed files with 10 additions and 7 deletions
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5
GPy/core/parameterization/variational.py
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@ -10,7 +10,7 @@ from .param import Param
from paramz.transformations import Logexp, Logistic,__fixed__ from paramz.transformations import Logexp, Logistic,__fixed__
class VariationalPrior(Parameterized): class VariationalPrior(Parameterized):
def __init__(self, name='latent space', **kw): def __init__(self, name='latent prior', **kw):
super(VariationalPrior, self).__init__(name=name, **kw) super(VariationalPrior, self).__init__(name=name, **kw)
def KL_divergence(self, variational_posterior): def KL_divergence(self, variational_posterior):
@ -23,6 +23,9 @@ class VariationalPrior(Parameterized):
raise NotImplementedError("override this for variational inference of latent space") raise NotImplementedError("override this for variational inference of latent space")
class NormalPrior(VariationalPrior): class NormalPrior(VariationalPrior):
def __init__(self, name='normal_prior', **kw):
super(VariationalPrior, self).__init__(name=name, **kw)
def KL_divergence(self, variational_posterior): def KL_divergence(self, variational_posterior):
var_mean = np.square(variational_posterior.mean).sum() var_mean = np.square(variational_posterior.mean).sum()
var_S = (variational_posterior.variance - np.log(variational_posterior.variance)).sum() var_S = (variational_posterior.variance - np.log(variational_posterior.variance)).sum()