tf.contrib.distributions.DirichletMultinomial.sample_n(n, seed=None, name='sample_n') Generate n samples.

tf.contrib.distributions.InverseGammaWithSoftplusAlphaBeta.std(name='std') Standard deviation.

tf.contrib.distributions.LaplaceWithSoftplusScale.batch_shape(name='batch_shape') Shape of a single sample from a single event

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

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

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

tf.contrib.distributions.Chi2.mode(name='mode') Mode. Additional documentation from Gamma:

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

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

tf.contrib.distributions.TransformedDistribution.cdf(value, name='cdf') Cumulative distribution function. Given