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

tf.contrib.bayesflow.stochastic_tensor.BinomialTensor.clone(name=None, **dist_args)

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

tf.contrib.bayesflow.stochastic_tensor.WishartCholeskyTensor.graph

tf.contrib.distributions.Poisson.is_reparameterized

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

tf.contrib.distributions.StudentTWithAbsDfSoftplusSigma.param_static_shapes(cls, sample_shape) param_shapes with static (i.e.

tf.contrib.distributions.Chi2.mean(name='mean') Mean.

tf.contrib.bayesflow.stochastic_tensor.BernoulliWithSigmoidPTensor.input_dict

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