v0.31.4

Turing v0.31.4

Diff since v0.31.3

Features

• It is now possible to use := to track deterministic quantities in the model.

Merged pull requests:

• Use values_as_in_model to extract the parameters from a Transition (#2202) (@torfjelde)

Closed issues:

• Problems with deterministic distribution (#1335)
• Zygote's compilation scales badly with the number of ~ statements (#1754)
• New Gibbs sampler based on SimpleVarInfo. (#1904)
• LKJCholesky returns a Union (#2102)
• ADVI is not up-to-date on the AD side (#2186)
• Model fails with an autograd error (#2189)
• Why are we passing chunksize=0 to AutoForwardDiff rather than using default? (#2203)

v0.31.3

Turing v0.31.3

Diff since v0.31.2

Merged pull requests:

• Bump ADTypes compat entry to include version 1 (#2209) (@torfjelde)

v0.31.2

Turing v0.31.2

Diff since v0.31.1

Merged pull requests:

• CompatHelper: bump compat for ADTypes to 1, (keep existing compat) (#2200) (@github-actions[bot])
• Improvements to externalsampler (#2204) (@torfjelde)
• Revert "CompatHelper: bump compat for ADTypes to 1, (keep existing compat)" (#2207) (@torfjelde)
• Bump AdvancedPS version to 0.6.0 (#2210) (@THargreaves)

v0.31.1

Turing v0.31.1

Diff since v0.31.0

Merged pull requests:

• Fix for #2205 (#2206) (@torfjelde)

Closed issues:

• ADVI errors for conditioned problems (#2205)

v0.31.0

Turing v0.31.0

Diff since v0.30.9

Merged pull requests:

• Bump DynamicPPL to v0.25 (#2197) (@torfjelde)

v0.30.9

Turing v0.30.9

Diff since v0.30.8

New features

• Turing.Experimental module where more experimental features will go, with the aim of eventually making its way into Turing proper.
• Turing.Experimental.Gibbs is a new implementation of the Gibbs sampler which provides much greater flexibility specifying which variables should use which sampler. Note that this is in the Turing.Experimental module, and thus will be prone to changes.

Merged pull requests:

• New Gibbs sampler using condition (#2099) (@torfjelde)

v0.30.8

Turing v0.30.8

Diff since v0.30.7

Merged pull requests:

• Bugfix for Optim.jl on models with different linked dimensionality (#2196) (@torfjelde)

Closed issues:

• Feature request: allow user to pass gradient tape into sample() function (#1419)
• Should we support Tracker.jl? (#2000)
• Transfer essential/ad.jl to DynamicPPL (#2141)
• init_params doesn't work since v0.30.0 (#2150)
• ADVI does not work with new DynamicPPL.jl Conditioning Syntax (#2178)
• Proposal for MH only works correctly with subtypes of MvNormal (#2180)
• Question: I tried this tutorial. I added the package "DynamicPPL". However, when running "using DynamicPPL: settrans!", I get the error "UndefVarError: settrans! not defined" (#2183)
• filldist on distributions requiring SimplexBijector (#2190)
• init_params in v.0.30.1 (#2192)

v0.30.7

Turing v0.30.7

Diff since v0.30.6

v0.30.6

Turing v0.30.6

Diff since v0.30.5

Merged pull requests:

• Partial fix for #2095 (#2096) (@torfjelde)
• Fix error TuringOptimExt.jl with information matrix/vcov (#2167) (@smith-garrett)
• Disable CI sampling progress logging (#2176) (@sunxd3)

Closed issues:

• method definition warning when trying tutorial no.2 'Unsupervised Learning using Bayesian Mixture Models' (#2173)
• autodiff documentation outdated (#2177)

v0.30.5

Turing v0.30.5

Diff since v0.30.4

• essential/ad.jl is removed, ForwardDiff and ReverseDiff integrations via LogDensityProblemsAD are moved to DynamicPPL and live in corresponding package extensions.
• LogDensityProblemsAD.ADgradient(ℓ::DynamicPPL.LogDensityFunction) (i.e. the single argument method) is moved to Inference module. It will create ADgradient using the adtype information stored in context field of ℓ.
• getADbackend function is renamed to getADType, the interface is preserved, but packages that previously used getADbackend should be updated to use getADType.
• TuringTag for ForwardDiff is also removed, now DynamicPPLTag is defined in DynamicPPL package and should serve the same purpose.

Merged pull requests:

• Move ad.jl to DynamicPPL (#2158) (@sunxd3)
• Change Optimization kwarg autoad to adtype (#2168) (@ElOceanografo)
• Add accepted arg to AdvancedMH.Transition calls (#2172) (@sunxd3)