tf.contrib.distributions.MultivariateNormalCholesky.mu

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

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

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

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

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

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

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

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

class tf.contrib.distributions.WishartFull The matrix Wishart distribution on positive definite matrices. This