API and Documentation

There are four modules in Edward: ed.criticisms, ed.inferences, ed.models, and ed.util.

Criticism

ed.criticisms is comprised of functions. They operate on random variables in a model or they operate on NumPy arrays representing values drawn from the random variables.

• ed.criticisms.evaluate
• ed.criticisms.ppc
• ed.criticisms.ppc_density_plot
• ed.criticisms.ppc_stat_hist_plot

Inference

ed.inferences is mostly comprised of classes. They are organized in a class hierarchy, where methods are shared via parent classes and Inference is the top-most base class.

• ed.inferences.Inference
• ed.inferences.VariationalInference
  • ed.inferences.KLqp
    • ed.inferences.ReparameterizationKLqp
    • ed.inferences.ReparameterizationKLKLqp
    • ed.inferences.ReparameterizationEntropyKLqp
    • ed.inferences.ScoreKLqp
    • ed.inferences.ScoreKLKLqp
    • ed.inferences.ScoreEntropyKLqp
  • ed.inferences.KLpq
  • ed.inferences.GANInference
    • ed.inferences.BiGANInference
    • ed.inferences.ImplicitKLqp
    • ed.inferences.WGANInference
  • ed.inferences.MAP
    • ed.inferences.Laplace
• ed.inferences.MonteCarlo
  • ed.inferences.Gibbs
  • ed.inferences.MetropolisHastings
  • ed.inferences.HMC
  • ed.inferences.SGLD
  • ed.inferences.SGHMC
• ed.inferences.complete_conditional

Models

ed.models is comprised of random variables. The list of available random variables depends on the TensorFlow version installed. For TensorFlow 1.6.0, the following are available:

• ed.models.RandomVariable
• ed.models.Autoregressive
• ed.models.Bernoulli
• ed.models.BernoulliWithSigmoidProbs
• ed.models.Beta
• ed.models.BetaWithSoftplusConcentration
• ed.models.Binomial
• ed.models.Categorical
• ed.models.Cauchy
• ed.models.Chi2
• ed.models.Chi2WithAbsDf
• ed.models.ConditionalDistribution
• ed.models.ConditionalTransformedDistribution
• ed.models.Deterministic
• ed.models.Dirichlet
• ed.models.DirichletMultinomial
• ed.models.DirichletProcess
• ed.models.Empirical
• ed.models.ExpRelaxedOneHotCategorical
• ed.models.Exponential
• ed.models.ExponentialWithSoftplusRate
• ed.models.Gamma
• ed.models.GammaWithSoftplusConcentrationRate
• ed.models.Geometric
• ed.models.HalfNormal
• ed.models.Independent
• ed.models.InverseGamma
• ed.models.InverseGammaWithSoftplusConcentrationRate
• ed.models.Laplace
• ed.models.LaplaceWithSoftplusScale
• ed.models.Logistic
• ed.models.Mixture
• ed.models.MixtureSameFamily
• ed.models.Multinomial
• ed.models.MultivariateNormalDiag
• ed.models.MultivariateNormalDiagPlusLowRank
• ed.models.MultivariateNormalDiagWithSoftplusScale
• ed.models.MultivariateNormalFullCovariance
• ed.models.MultivariateNormalTriL
• ed.models.NegativeBinomial
• ed.models.Normal
• ed.models.NormalWithSoftplusScale
• ed.models.OneHotCategorical
• ed.models.ParamMixture
• ed.models.PointMass
• ed.models.Poisson
• ed.models.PoissonLogNormalQuadratureCompound
• ed.models.QuantizedDistribution
• ed.models.RelaxedBernoulli
• ed.models.RelaxedOneHotCategorical
• ed.models.SinhArcsinh
• ed.models.StudentT
• ed.models.StudentTWithAbsDfSoftplusScale
• ed.models.TransformedDistribution
• ed.models.Uniform
• ed.models.VectorDeterministic
• ed.models.VectorDiffeomixture
• ed.models.VectorExponentialDiag
• ed.models.VectorLaplaceDiag
• ed.models.VectorSinhArcsinhDiag
• ed.models.WishartCholesky
• ed.models.WishartFull

Utilities

ed.util is comprised of functions for miscellaneous usage.

• ed.util.Progbar
• ed.util.check_data
• ed.util.check_latent_vars
• ed.util.compute_multinomial_mode
• ed.util.copy
• ed.util.dot
• ed.util.get_ancestors
• ed.util.get_blanket
• ed.util.get_children
• ed.util.get_control_variate_coef
• ed.util.get_descendants
• ed.util.get_parents
• ed.util.get_session
• ed.util.get_siblings
• ed.util.get_variables
• ed.util.is_independent
• ed.util.random_variables
• ed.util.rbf
• ed.util.set_seed
• ed.util.to_simplex
• ed.util.transform
• ed.util.with_binary_averaging
• ed.VERSION
• ed.__version__