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

tf.contrib.distributions.MultivariateNormalDiagPlusVDVT.log_sigma_det(name='log_sigma_det') Log of determinant of covariance matrix

tf.contrib.distributions.Chi2.beta Inverse scale parameter.

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

tf.contrib.distributions.Gamma.validate_args Python boolean indicated possibly expensive checks are enabled.

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

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

tf.contrib.distributions.Mixture.event_shape(name='event_shape') Shape of a single sample from a single batch as a 1-D int32 Tensor

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

tf.contrib.distributions.Beta.validate_args Python boolean indicated possibly expensive checks are enabled.