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

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

tf.contrib.distributions.Binomial.n Number of trials.

tf.contrib.distributions.Beta.is_reparameterized

tf.contrib.distributions.MultivariateNormalDiagWithSoftplusStDev.mode(name='mode') Mode.

tf.contrib.distributions.ExponentialWithSoftplusLam.name Name prepended to all ops created by this Distribution.

tf.contrib.distributions.Exponential.mode(name='mode') Mode. Additional documentation from

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

tf.contrib.distributions.MultivariateNormalFull.log_prob(value, name='log_prob') Log probability density/mass function (depending

tf.contrib.distributions.TransformedDistribution.log_det_jacobian Function computing the log determinant of the Jacobian of transform