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

tf.contrib.bayesflow.stochastic_tensor.MultivariateNormalFullTensor.loss(final_loss, name='Loss')

tf.contrib.bayesflow.stochastic_tensor.ExponentialTensor.value(name='value')

tf.contrib.distributions.Exponential.is_continuous

tf.contrib.bayesflow.stochastic_tensor.WishartCholeskyTensor.value_type

tf.contrib.distributions.MultivariateNormalFull.pmf(value, name='pmf') Probability mass function. Args:

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

tf.contrib.distributions.StudentTWithAbsDfSoftplusSigma.__init__(df, mu, sigma, validate_args=False, allow_nan_stats=True, name='StudentTWithAbsDfSoftplusSigma')

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

tf.contrib.distributions.StudentT.parameters Dictionary of parameters used by this Distribution.