tf.contrib.distributions.GammaWithSoftplusAlphaBeta.get_event_shape() Shape of a single sample from a single batch as a TensorShape

tf.contrib.distributions.DirichletMultinomial.sample(sample_shape=(), seed=None, name='sample') Generate samples of the specified

tf.contrib.distributions.Beta.b Shape parameter.

tf.contrib.distributions.Mixture.__init__(cat, components, validate_args=False, allow_nan_stats=True, name='Mixture') Initialize

tf.contrib.distributions.WishartFull.log_normalizing_constant(name='log_normalizing_constant') Computes the log normalizing constant

tf.contrib.distributions.WishartFull.batch_shape(name='batch_shape') Shape of a single sample from a single event index as a 1-D

tf.contrib.distributions.DirichletMultinomial.pdf(value, name='pdf') Probability density function. Args:

tf.contrib.distributions.DirichletMultinomial.variance(name='variance') Variance. Additional documentation

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

tf.contrib.distributions.Categorical.log_cdf(value, name='log_cdf') Log cumulative distribution function. Given