tf.contrib.distributions.Laplace.mean(name='mean') Mean.

tf.contrib.distributions.MultivariateNormalDiag.allow_nan_stats Python boolean describing behavior when a stat is undefined. Stats return +/- infinity when it makes sense. E.g., the variance of a Cauchy distribution is infinity. However, sometimes the statistic is undefined, e.g., if a distribution's pdf does not achieve a maximum within the support of the distribution, the mode is undefined. If the mean is undefined, then by definition the variance is undefined. E.g. the mean for Student's T

class tf.contrib.bayesflow.stochastic_tensor.WishartFullTensor WishartFullTensor is a StochasticTensor backed by the distribution WishartFull.

tf.contrib.bayesflow.stochastic_tensor.InverseGammaWithSoftplusAlphaBetaTensor.dtype

tf.contrib.bayesflow.stochastic_tensor.BetaTensor.mean(name='mean')

tf.contrib.bayesflow.stochastic_tensor.TransformedDistributionTensor.mean(name='mean')

tf.contrib.bayesflow.stochastic_tensor.BetaWithSoftplusABTensor.name

tf.contrib.learn.monitors.LoggingTrainable.every_n_step_begin(step)

Static helper routines for PartialTensorShape. Includes a few common predicates on a partially known tensor shape. Member Details string tensorflow::PartialTensorShapeUtils::PartialShapeListString(const gtl::ArraySlice< PartialTensorShape > &shapes) bool tensorflow::PartialTensorShapeUtils::AreCompatible(const gtl::ArraySlice< PartialTensorShape > &shapes0, const gtl::ArraySlice< PartialTensorShape > &shapes1)

class tf.contrib.bayesflow.stochastic_tensor.GammaWithSoftplusAlphaBetaTensor GammaWithSoftplusAlphaBetaTensor is a StochasticTensor backed by the distribution GammaWithSoftplusAlphaBeta.