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

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

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

tf.contrib.distributions.Categorical.num_classes Scalar int32 tensor: the number of classes.

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

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

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

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

tf.contrib.distributions.Beta.allow_nan_stats Python boolean describing behavior when a stat is undefined. Stats

tf.contrib.distributions.ExponentialWithSoftplusLam.variance(name='variance') Variance.