tf.contrib.distributions.InverseGammaWithSoftplusAlphaBeta.log_pdf(value, name='log_pdf') Log probability density function.

tf.contrib.distributions.BetaWithSoftplusAB.prob(value, name='prob') Probability density/mass function (depending on is_continuous)

tf.contrib.distributions.QuantizedDistribution.param_shapes(cls, sample_shape, name='DistributionParamShapes') Shapes of parameters

tf.contrib.distributions.DirichletMultinomial.validate_args Python boolean indicated possibly expensive checks are enabled.

tf.contrib.distributions.Binomial.logits Log-odds.

tf.contrib.distributions.NormalWithSoftplusSigma.is_reparameterized

tf.contrib.distributions.StudentTWithAbsDfSoftplusSigma.dtype The DType of Tensors handled by this

tf.contrib.distributions.Binomial.get_batch_shape() Shape of a single sample from a single event index as a TensorShape

tf.contrib.distributions.WishartFull.survival_function(value, name='survival_function') Survival function. Given

tf.contrib.distributions.QuantizedDistribution.event_shape(name='event_shape') Shape of a single sample from a single batch as