tf.contrib.bayesflow.stochastic_tensor.GammaWithSoftplusAlphaBetaTensor.distribution

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

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

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

tf.contrib.bayesflow.stochastic_tensor.MultivariateNormalFullTensor.name

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

tf.contrib.bayesflow.stochastic_tensor.GammaTensor.__init__(name=None, dist_value_type=None, loss_fn=score_function, **dist_args)

tf.contrib.distributions.DirichletMultinomial.is_reparameterized

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

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