Skip to content

Bump the all-julia-packages group across 7 directories with 11 updates#1422

Closed
dependabot[bot] wants to merge 1 commit into
mainfrom
dependabot/julia/all-julia-packages-3953652f89
Closed

Bump the all-julia-packages group across 7 directories with 11 updates#1422
dependabot[bot] wants to merge 1 commit into
mainfrom
dependabot/julia/all-julia-packages-3953652f89

Conversation

@dependabot

@dependabot dependabot Bot commented on behalf of github Jun 5, 2026 •
edited
Loading

Copy link
Copy Markdown
Contributor

Updates the requirements on OrderedCollections, StatsFuns, DynamicPPL, Bijectors, AbstractPPL, ADTypes, ForwardDiff, DifferentiationInterface, Enzyme, Distributions and LogDensityProblems to permit the latest version.
Updates OrderedCollections to 2.0.0

Release notes

Sourced from OrderedCollections's releases.

v2.0.0

OrderedCollections v2.0.0

Diff since v1.8.2

v2 is only removal of long standing depreactions. If you are using v1.7 or newer already and you can run your code with --depwarn=error then there is nothing to change.

Breaking:

Removed deprecated functionality:

Merged pull requests:

Closed issues:

  • Type piracy? (#25)
Commits
  • d5d76c7 Merge pull request #164 from JuliaCollections/ox/v2
  • 68ab740 Remove depreacations for v2.0 release
  • 7bb0847 Bump version from 1.8.1 to 1.8.2
  • 6af78d8 OrderedDict: improve performance for non-concrete values and keys (#166)
  • 1eaa980 Bump actions/checkout from 5 to 6 (#157)
  • 7be2211 Bump actions/checkout from 4 to 5 (#156)
  • a25bffa Add Integer type annotation to sizehint! overloads (#155)
  • a64f186 issorted(ld; byvalue=true) for LittleDicts (#151)
  • 5ec1764 LittleDict constructor from AbstractDict (#150)
  • 7b3daef CI: workaround TagBot issues
  • Additional commits viewable in compare view

Updates OrderedCollections to 2.0.0

Release notes

Sourced from OrderedCollections's releases.

v2.0.0

OrderedCollections v2.0.0

Diff since v1.8.2

v2 is only removal of long standing depreactions. If you are using v1.7 or newer already and you can run your code with --depwarn=error then there is nothing to change.

Breaking:

Removed deprecated functionality:

Merged pull requests:

Closed issues:

  • Type piracy? (#25)
Commits
  • d5d76c7 Merge pull request #164 from JuliaCollections/ox/v2
  • 68ab740 Remove depreacations for v2.0 release
  • 7bb0847 Bump version from 1.8.1 to 1.8.2
  • 6af78d8 OrderedDict: improve performance for non-concrete values and keys (#166)
  • 1eaa980 Bump actions/checkout from 5 to 6 (#157)
  • 7be2211 Bump actions/checkout from 4 to 5 (#156)
  • a25bffa Add Integer type annotation to sizehint! overloads (#155)
  • a64f186 issorted(ld; byvalue=true) for LittleDicts (#151)
  • 5ec1764 LittleDict constructor from AbstractDict (#150)
  • 7b3daef CI: workaround TagBot issues
  • Additional commits viewable in compare view

Updates StatsFuns to 2.0.1

Release notes

Sourced from StatsFuns's releases.

v2.0.1

StatsFuns v2.0.1

Diff since v2.0.0

Merged pull requests:

Commits

Updates OrderedCollections to 2.0.0

Release notes

Sourced from OrderedCollections's releases.

v2.0.0

OrderedCollections v2.0.0

Diff since v1.8.2

v2 is only removal of long standing depreactions. If you are using v1.7 or newer already and you can run your code with --depwarn=error then there is nothing to change.

Breaking:

Removed deprecated functionality:

Merged pull requests:

Closed issues:

  • Type piracy? (#25)
Commits
  • d5d76c7 Merge pull request #164 from JuliaCollections/ox/v2
  • 68ab740 Remove depreacations for v2.0 release
  • 7bb0847 Bump version from 1.8.1 to 1.8.2
  • 6af78d8 OrderedDict: improve performance for non-concrete values and keys (#166)
  • 1eaa980 Bump actions/checkout from 5 to 6 (#157)
  • 7be2211 Bump actions/checkout from 4 to 5 (#156)
  • a25bffa Add Integer type annotation to sizehint! overloads (#155)
  • a64f186 issorted(ld; byvalue=true) for LittleDicts (#151)
  • 5ec1764 LittleDict constructor from AbstractDict (#150)
  • 7b3daef CI: workaround TagBot issues
  • Additional commits viewable in compare view

Updates DynamicPPL to 0.42.0

Release notes

Sourced from DynamicPPL's releases.

v0.42.0

DynamicPPL v0.42.0

Diff since v0.41.8

LogDensityFunction now performs AD preparation through AbstractPPL's prepare / value_and_gradient!! interface instead of calling DifferentiationInterface directly. Internally this removes the _use_closure heuristic and the explicit DI.Constant plumbing; the choice between closure and constants now lives in AbstractPPL.

logdensity_at has been renamed to logdensity_internal. The old name is kept as a const alias so external callers do not break.

LogDensityAt is now a deprecation shim that emits a warning and returns an AbstractPPL.Evaluators.VectorEvaluator whose call forwards to logdensity_internal. New code should call AbstractPPL.prepare(logdensity_internal, x; context=...) directly.

Breaking changes

DifferentiationInterface is no longer a hard dependency of DynamicPPL. With AbstractPPL 0.15.2, the following backends now have native AbstractPPL extensions and only need the concrete AD package loaded:

  • AutoForwardDiff — load ForwardDiff
  • AutoMooncake, AutoMooncakeForward — load Mooncake

For other DI-routed backends like AutoReverseDiff, users must load DifferentiationInterface together with the concrete AD package:

using DynamicPPL, ADTypes, DifferentiationInterface, ReverseDiff
ldf = LogDensityFunction(model; adtype=AutoReverseDiff())

For distributed sampling the same packages must be loaded on every worker.

Compatibility bounds bumped:

  • AbstractPPL 0.14 → 0.15
  • Bijectors 0.15.17 → 0.16

The integration test suites for MarginalLogDensities, ReverseDiff, and Enzyme now live in their own environments under test/ext/DynamicPPL*Ext/ and run as separate CI jobs.

Merged pull requests:

Closed issues:

  • Improve DynamicPPL benchmarks (#1374)
Changelog

Sourced from DynamicPPL's changelog.

0.42.0

LogDensityFunction now performs AD preparation through AbstractPPL's prepare / value_and_gradient!! interface instead of calling DifferentiationInterface directly. Internally this removes the _use_closure heuristic and the explicit DI.Constant plumbing; the choice between closure and constants now lives in AbstractPPL.

logdensity_at has been renamed to logdensity_internal. The old name is kept as a const alias so external callers do not break.

LogDensityAt is now a deprecation shim that emits a warning and returns an AbstractPPL.Evaluators.VectorEvaluator whose call forwards to logdensity_internal. New code should call AbstractPPL.prepare(logdensity_internal, x; context=...) directly.

Breaking changes

DifferentiationInterface is no longer a hard dependency of DynamicPPL. With AbstractPPL 0.15.2, the following backends now have native AbstractPPL extensions and only need the concrete AD package loaded:

  • AutoForwardDiff — load ForwardDiff
  • AutoMooncake, AutoMooncakeForward — load Mooncake

For other DI-routed backends like AutoReverseDiff, users must load DifferentiationInterface together with the concrete AD package:

using DynamicPPL, ADTypes, DifferentiationInterface, ReverseDiff
ldf = LogDensityFunction(model; adtype=AutoReverseDiff())

For distributed sampling the same packages must be loaded on every worker.

Compatibility bounds bumped:

  • AbstractPPL 0.14 → 0.15
  • Bijectors 0.15.17 → 0.16

The integration test suites for MarginalLogDensities, ReverseDiff, and Enzyme now live in their own environments under test/ext/DynamicPPL*Ext/ and run as separate CI jobs.

0.41.8

Override MarginalLogDensities.optimize_marginal! for LogDensityFunctionWrapper so the underlying OptimizationProblem is rebuilt with the current non-marginalised parameters on each call, rather than reusing a stale problem.

0.41.7

Enable usage of ComponentVectors on the left-hand side of tilde-statements.

Accessing a nonexistent variable in a VarNamedTuple now throws a KeyError with the original VarName, instead of an opaque type NamedTuple has no field ... error.

0.41.6

Add a factorize::Bool keyword argument for pointwise_logdensities(model, values), which controls whether pointwise logdensities for factorisable distributions (e.g. MvNormal, product_distribution, etc.) are returned as a single log-density for the whole distribution, or as an array of log-densities for each factor. The same argument is also added to pointwise_loglikelihoods and pointwise_prior_logdensities.

0.41.5

Make sure that DynamicPPL.TestUtils.AD.run_ad(...; verbose=false) truly silences all messages.

... (truncated)

Commits

Updates Bijectors to 0.16.0

Release notes

Sourced from Bijectors's releases.

v0.16.0

Bijectors v0.16.0

Diff since v0.15.24

Breaking changes

ChainRulesCore and EnzymeCore have been moved from direct dependencies to weak dependencies. Their integration code, including the find_alpha Enzyme rule and the rrules previously defined in src/chainrules.jl, now lives in the new BijectorsChainRulesCoreExt and BijectorsEnzymeCoreExt package extensions. These extensions are only loaded when the user also loads ChainRulesCore or EnzymeCore themselves, so downstream packages that relied on Bijectors to pull in these packages transitively must now load them directly.

DifferentiationInterface has been removed from the package's direct dependencies. It is no longer used at runtime.

Merged pull requests:

Closed issues:

  • LKJCholesky Unconstrained Parameterization is Rather "Stiff" (#468)
Changelog

Sourced from Bijectors's changelog.

0.16.0

Breaking changes

ChainRulesCore and EnzymeCore have been moved from direct dependencies to weak dependencies. Their integration code, including the find_alpha Enzyme rule and the rrules previously defined in src/chainrules.jl, now lives in the new BijectorsChainRulesCoreExt and BijectorsEnzymeCoreExt package extensions. These extensions are only loaded when the user also loads ChainRulesCore or EnzymeCore themselves, so downstream packages that relied on Bijectors to pull in these packages transitively must now load them directly.

DifferentiationInterface has been removed from the package's direct dependencies. It is no longer used at runtime.

0.15.24

Export a few more functions from Bijectors.VectorBijectors, namely scalar_to_scalar_bijector, TypedIdentity, Log, and Untruncate.

0.15.23

Implement vector bijectors for Distributions.MvTDist.

0.15.22

Implement vector bijectors for Bijectors.TransformedDistribution.

0.15.21

Add compatibility with Roots.jl v3.

0.15.20

Export Bijectors.VectorBijectors.has_constant_vec_bijector to allow downstream packages to overload it.

0.15.19

Optimise performance of vector bijectors for products of univariate distributions.

0.15.18

Implemented vector bijectors for Bijectors.OrderedDistribution.

0.15.17

Adds a new module, Bijectors.VectorBijectors. This module implements bijectors that always return vectors as the output of a linking operation. This provides additional guarantees over the existing Bijectors interface, which in general will return some collection of values that are in Euclidean space, but whose shape is not generally a vector (it could be a scalar or a multidimensional array). The intention is to make it easier to implement bijectors that are compatible with libraries that use vector inputs, such as LogDensityProblems.jl (which is in turn heavily used in the Turing ecosystem).

Please see the documentation for further information.

0.15.16

Added compatibility with Mooncake.jl v0.5.

0.15.15

... (truncated)

Commits

Updates AbstractPPL to 0.15.2

Release notes

Sourced from AbstractPPL's releases.

v0.15.2

AbstractPPL v0.15.2

Diff since v0.15.1

Added AbstractPPLForwardDiffExt, a direct ForwardDiff path for AutoForwardDiff (gradient, Jacobian, Hessian, context, chunk size, custom tag).

Merged pull requests:

Closed issues:

  • Add ForwardDiff support (#165)
Changelog

Sourced from AbstractPPL's changelog.

0.15.2

Added AbstractPPLForwardDiffExt, a direct ForwardDiff path for AutoForwardDiff (gradient, Jacobian, Hessian, context, chunk size, custom tag).

0.15.1

Added Hessian support to the AD interface. Pass order=2 to prepare(adtype, problem, x) to build a Hessian-capable evaluator. The new value_gradient_and_hessian!!(prepared, x) then returns (value, gradient, hessian) in a single call. Both the DifferentiationInterface and Mooncake extensions implement this.

order=2 accepts the same context::Tuple and check_dims options as order=1. NamedTuple inputs are not supported with order=2.

The AbstractPPLTestExt conformance harness now provides a :hessian group covering value, gradient and Hessian round-trips, along with an order-mismatch edge case.

0.15.0

Added a new evaluator-preparation interface for AD backends. prepare binds a callable to a sample input, either a vector or a NamedTuple, and returns a Prepared wrapper. value_and_gradient!! and value_and_jacobian!! then compute value-and-derivative pairs from that wrapper. The !! suffix means the returned derivative may alias backend cache storage, so copy it if you need to keep it across calls.

using ADTypes, Mooncake  # or DifferentiationInterface + ForwardDiff
using AbstractPPL: prepare, value_and_gradient!!
prepared = prepare(AutoMooncake(), x -> -0.5 * sum(abs2, x), zeros(3))
val, grad = value_and_gradient!!(prepared, [1.0, 2.0, 3.0])
# val == -7.0; grad == [-1.0, -2.0, -3.0]

Added two AD-backend extensions:

  • AbstractPPLDifferentiationInterfaceExt, supporting DifferentiationInterface backends.
  • AbstractPPLMooncakeExt, supporting AutoMooncake and AutoMooncakeForward.

The new evaluator path supports scalar gradients, vector-output Jacobians, NamedTuple inputs, reusable AD caches, input-shape checks, and constant context arguments via context::Tuple.

AbstractPPLTestExt now provides a small AD conformance harness through generate_testcases and run_testcases, with reserved groups :vector, :namedtuple, :edge, and :cache_reuse.

See https://github.com/TuringLang/AbstractPPL.jl/blob/main/docs/src/evaluators.md for the full interface, the check_dims and context::Tuple options, the NamedTuple input path, and extension-author guidance.

0.14.2

Fix string serialisation of VarNames such that the order of keyword arguments is preserved (this was previously guaranteed, but JSON.jl v1.5.0 introduced a change that caused the keyword arguments to always be sorted.)

Minor performance optimisation for AbstractPPL.append_optic.

0.14.1

Export the concretize_top_level function, which concretizes only the indices contained in an AbstractPPL.Index, and does not recurse into child optics.

0.14.0

This release overhauls the VarName type. Much of the external API for traversing and manipulating VarNames (once they have been constructed) has been preserved, but if you use the VarName type directly, there are significant changes.

... (truncated)

Commits
  • 9ebf18f Add direct ForwardDiff extension (#166)
  • 2d35e51 Update HISTORY.md for 0.15.1 (#164)
  • 4390c43 Add order=2 Hessian preparation via value_gradient_and_hessian!! (#163)
  • 1599516 Revise 0.15.0 HISTORY.md (#162)
  • 451bfa6 Add Mooncake extension; extend AD conformance suite with NamedTuple and cache...
  • 10a4182 Part 1 of autograd backend: DifferentiationInterface extention (#158)
  • 23fc8c5 CompatHelper: add new compat entry for AbstractPPL at version 0.14 for packag...
  • ceec39b Add agent guidance files (#161)
  • ba8d21c Add Evaluators: prepare interface, and vectorisation utilities (#157)
  • 76dc6df Micro-optimise append_optic; fix serialisation for JSON@1.5.0 (#154)
  • Additional commits viewable in compare view

Updates ADTypes to 1.22.0

Release notes

Sourced from ADTypes's releases.

v1.22.0

ADTypes v1.22.0

Diff since v1.21.0

Merged pull requests:

Commits
  • b1759cd Bump version to 1.22.0 (#147)
  • 5f444f7 add HyperHessian definition (#146)
  • 58528c1 Merge pull request #145 from SciML/dependabot/github_actions/julia-actions/se...
  • 8d59cb1 Bump julia-actions/setup-julia from 2 to 3
  • 420fcec Merge pull request #144 from SciML/dependabot/github_actions/codecov/codecov-...
  • b8f651a Bump codecov/codecov-action from 5 to 6
  • 6cc1c9e Merge pull request #143 from SciML/dependabot/github_actions/julia-actions/ca...
  • 59c6ed7 Bump julia-actions/cache from 2 to 3
  • 8d795ca Merge pull request #142 from SciML/dependabot/github_actions/actions/checkout-6
  • 94ee83c Bump actions/checkout from 4 to 6
  • Additional commits viewable in compare view

Updates ForwardDiff to 1.3.3

Release notes

Sourced from ForwardDiff's releases.

v1.3.3

ForwardDiff v1.3.3

Diff since v1.3.2

Merged pull requests:

Commits

Updates DynamicPPL to 0.42.0

Release notes

Sourced from DynamicPPL's releases.

v0.42.0

DynamicPPL v0.42.0

Diff since v0.41.8

LogDensityFunction now performs AD preparation through AbstractPPL's prepare / value_and_gradient!! interface instead of calling DifferentiationInterface directly. Internally this removes the _use_closure heuristic and the explicit DI.Constant plumbing; the choice between closure and constants now lives in AbstractPPL.

logdensity_at has been renamed to logdensity_internal. The old name is kept as a const alias so external callers do not break.

LogDensityAt is now a deprecation shim that emits a warning and returns an AbstractPPL.Evaluators.VectorEvaluator whose call forwards to logdensity_internal. New code should call AbstractPPL.prepare(logdensity_internal, x; context=...) directly.

Breaking changes

DifferentiationInterface is no longer a hard dependency of DynamicPPL. With AbstractPPL 0.15.2, the following backends now have native AbstractPPL extensions and only need the concrete AD package loaded:

  • AutoForwardDiff — load ForwardDiff
  • AutoMooncake, AutoMooncakeForward — load Mooncake

For other DI-routed backends like AutoReverseDiff, users must load DifferentiationInterface together with the concrete AD package:

using DynamicPPL, ADTypes, DifferentiationInterface, ReverseDiff
ldf = LogDensityFunction(model; adtype=AutoReverseDiff())

For distributed sampling the same packages must be loaded on every worker.

Compatibility bounds bumped:

  • AbstractPPL 0.14 → 0.15
  • Bijectors 0.15.17 → 0.16

The integration test suites for MarginalLogDensities, ReverseDiff, and Enzyme now live in their own environments under test/ext/DynamicPPL*Ext/ and run as separate CI jobs.

Merged pull requests:

Closed issues:

  • Improve DynamicPPL benchmarks (#1374)
Changelog

Sourced from DynamicPPL's changelog.

0.42.0

LogDensityFunction now performs AD preparation through AbstractPPL's prepare / value_and_gradient!! interface instead of calling DifferentiationInterface directly. Internally this removes the _use_closure heuristic and the explicit DI.Constant plumbing; the choice between closure and constants now lives in AbstractPPL.

logdensity_at has been renamed to logdensity_internal. The old name is kept as a const alias so external callers do not break.

LogDensityAt is now a deprecation shim that emits a warning and returns an AbstractPPL.Evaluators.VectorEvaluator whose call forwards to logdensity_internal. New code should call AbstractPPL.prepare(logdensity_internal, x; context=...) directly.

Breaking changes

DifferentiationInterface is no longer a hard dependency of DynamicPPL. With AbstractPPL 0.15.2, the following backends now have native AbstractPPL extensions and only need the concrete AD package loaded:

  • AutoForwardDiff — load ForwardDiff
  • AutoMooncake, AutoMooncakeForward — load Mooncake

For other DI-routed backends like AutoReverseDiff, users must load DifferentiationInterface together with the concrete AD package:

using DynamicPPL, ADTypes, DifferentiationInterface, ReverseDiff
ldf = LogDensityFunction(model; adtype=AutoReverseDiff())

For distributed sampling the same packages must be loaded on every worker.

Compatibility bounds bumped:

  • AbstractPPL 0.14 → 0.15
  • Bijectors 0.15.17 → 0.16

The integration test suites for MarginalLogDensities, ReverseDiff, and Enzyme now live in their own environments under test/ext/DynamicPPL*Ext/ and run as separate CI jobs.

0.41.8

Override MarginalLogDensities.optimize_marginal! for LogDensityFunctionWrapper so the underlying OptimizationProblem is rebuilt with the current non-marginalised parameters on each call, rather than reusing a stale problem.

0.41.7

Enable usage of ComponentVectors on the left-hand side of tilde-statements.

Accessing a nonexistent variable in a VarNamedTuple now throws a KeyError with the original VarName, instead of an opaque type NamedTuple has no field ... error.

0.41.6

Add a factorize::Bool keyword argument for pointwise_logdensities(model, values), which controls whether pointwise logdensities for factorisable distributions (e.g. MvNormal, product_distribution, etc.) are returned as a single log-density for the whole distribution, or as an array of log-densities for each factor. The same argument is also added to pointwise_loglikelihoods and pointwise_prior_logdensities.

0.41.5

Make sure that DynamicPPL.TestUtils.AD.run_ad(...; verbose=false) truly silences all messages.

... (truncated)

Commits

Updates DifferentiationInterface to 0.7.18

Release notes

Sourced from DifferentiationInterface's releases.

DifferentiationInterface-v0.7.18

DifferentiationInterface DifferentiationInterface-v0.7.18

Diff since DifferentiationInterface-v0.7.17

Merged pull requests:

Closed issues:

  • FiniteDiff with :central includes junk (#983)
  • Tracking removal from Turing-verse (#992)
Commits
  • f477fa3 fix: proper eltype in wrong-mode pushforward/pullback (#1003)
  • cb6801e feat: add support for HyperHessian backend (#940)
  • d38d905 fix: make DI compatible with latest Mooncake friendly tangents (#1001)
  • 1b5d91c chore: clean up backend testing CI (#1002)
  • 5a3ea38 test: activate Enzyme tests on Julia 1.12 (#966)
  • ee29327 chore(deps): bump julia-actions/setup-julia from 2 to 3 (#994)
  • 508572e chore: upper-bound Mooncake version (coherence with General) (#995)

@dependabot
Bump the all-julia-packages group across 7 directories with 11 updates
b24c6e1 
Updates the requirements on [OrderedCollections](https://github.com/JuliaCollections/OrderedCollections.jl), [StatsFuns](https://github.com/JuliaStats/StatsFuns.jl), [DynamicPPL](https://github.com/TuringLang/DynamicPPL.jl), [Bijectors](https://github.com/TuringLang/Bijectors.jl), [AbstractPPL](https://github.com/TuringLang/AbstractPPL.jl), [ADTypes](https://github.com/SciML/ADTypes.jl), [ForwardDiff](https://github.com/JuliaDiff/ForwardDiff.jl), [DifferentiationInterface](https://github.com/JuliaDiff/DifferentiationInterface.jl), [Enzyme](https://github.com/EnzymeAD/Enzyme.jl), [Distributions](https://github.com/JuliaStats/Distributions.jl) and [LogDensityProblems](https://github.com/tpapp/LogDensityProblems.jl) to permit the latest version.

Updates `OrderedCollections` to 2.0.0
- [Release notes](https://github.com/JuliaCollections/OrderedCollections.jl/releases)
- [Commits](JuliaCollections/OrderedCollections.jl@v1.0.0...v2.0.0)

Updates `OrderedCollections` to 2.0.0
- [Release notes](https://github.com/JuliaCollections/OrderedCollections.jl/releases)
- [Commits](JuliaCollections/OrderedCollections.jl@v1.0.0...v2.0.0)

Updates `StatsFuns` to 2.0.1
- [Release notes](https://github.com/JuliaStats/StatsFuns.jl/releases)
- [Commits](JuliaStats/StatsFuns.jl@v1.0.0...v2.0.1)

Updates `OrderedCollections` to 2.0.0
- [Release notes](https://github.com/JuliaCollections/OrderedCollections.jl/releases)
- [Commits](JuliaCollections/OrderedCollections.jl@v1.0.0...v2.0.0)

Updates `DynamicPPL` to 0.42.0
- [Release notes](https://github.com/TuringLang/DynamicPPL.jl/releases)
- [Changelog](https://github.com/TuringLang/DynamicPPL.jl/blob/main/HISTORY.md)
- [Commits](v0.1.0...v0.42.0)

Updates `Bijectors` to 0.16.0
- [Release notes](https://github.com/TuringLang/Bijectors.jl/releases)
- [Changelog](https://github.com/TuringLang/Bijectors.jl/blob/main/HISTORY.md)
- [Commits](TuringLang/Bijectors.jl@v0.1.0...v0.16.0)

Updates `AbstractPPL` to 0.15.2
- [Release notes](https://github.com/TuringLang/AbstractPPL.jl/releases)
- [Changelog](https://github.com/TuringLang/AbstractPPL.jl/blob/main/HISTORY.md)
- [Commits](TuringLang/AbstractPPL.jl@v0.1.0...v0.15.2)

Updates `ADTypes` to 1.22.0
- [Release notes](https://github.com/SciML/ADTypes.jl/releases)
- [Commits](SciML/ADTypes.jl@v0.1.0...v1.22.0)

Updates `ForwardDiff` to 1.3.3
- [Release notes](https://github.com/JuliaDiff/ForwardDiff.jl/releases)
- [Commits](JuliaDiff/ForwardDiff.jl@v0.0.2...v1.3.3)

Updates `DynamicPPL` to 0.42.0
- [Release notes](https://github.com/TuringLang/DynamicPPL.jl/releases)
- [Changelog](https://github.com/TuringLang/DynamicPPL.jl/blob/main/HISTORY.md)
- [Commits](v0.1.0...v0.42.0)

Updates `DifferentiationInterface` to 0.7.18
- [Release notes](https://github.com/JuliaDiff/DifferentiationInterface.jl/releases)
- [Commits](JuliaDiff/DifferentiationInterface.jl@DifferentiationInterface-v0.1.0...DifferentiationInterface-v0.7.18)

Updates `Enzyme` to 0.13.153
- [Release notes](https://github.com/EnzymeAD/Enzyme.jl/releases)
- [Commits](EnzymeAD/Enzyme.jl@v0.1.0...v0.13.153)

Updates `AbstractPPL` to 0.15.2
- [Release notes](https://github.com/TuringLang/AbstractPPL.jl/releases)
- [Changelog](https://github.com/TuringLang/AbstractPPL.jl/blob/main/HISTORY.md)
- [Commits](TuringLang/AbstractPPL.jl@v0.1.0...v0.15.2)

Updates `DynamicPPL` to 0.42.0
- [Release notes](https://github.com/TuringLang/DynamicPPL.jl/releases)
- [Changelog](https://github.com/TuringLang/DynamicPPL.jl/blob/main/HISTORY.md)
- [Commits](v0.1.0...v0.42.0)

Updates `Distributions` to 0.25.126
- [Release notes](https://github.com/JuliaStats/Distributions.jl/releases)
- [Commits](JuliaStats/Distributions.jl@0.2.2...v0.25.126)

Updates `Bijectors` to 0.16.0
- [Release notes](https://github.com/TuringLang/Bijectors.jl/releases)
- [Changelog](https://github.com/TuringLang/Bijectors.jl/blob/main/HISTORY.md)
- [Commits](TuringLang/Bijectors.jl@v0.1.0...v0.16.0)

Updates `LogDensityProblems` to 2.2.0
- [Release notes](https://github.com/tpapp/LogDensityProblems.jl/releases)
- [Changelog](https://github.com/tpapp/LogDensityProblems.jl/blob/master/CHANGELOG.md)
- [Commits](tpapp/LogDensityProblems.jl@v0.1.0...v2.2.0)

Updates `AbstractPPL` to 0.15.2
- [Release notes](https://github.com/TuringLang/AbstractPPL.jl/releases)
- [Changelog](https://github.com/TuringLang/AbstractPPL.jl/blob/main/HISTORY.md)
- [Commits](TuringLang/AbstractPPL.jl@v0.1.0...v0.15.2)

Updates `ADTypes` to 1.22.0
- [Release notes](https://github.com/SciML/ADTypes.jl/releases)
- [Commits](SciML/ADTypes.jl@v0.1.0...v1.22.0)

Updates `ForwardDiff` to 1.3.3
- [Release notes](https://github.com/JuliaDiff/ForwardDiff.jl/releases)
- [Commits](JuliaDiff/ForwardDiff.jl@v0.0.2...v1.3.3)

Updates `DynamicPPL` to 0.42.0
- [Release notes](https://github.com/TuringLang/DynamicPPL.jl/releases)
- [Changelog](https://github.com/TuringLang/DynamicPPL.jl/blob/main/HISTORY.md)
- [Commits](v0.1.0...v0.42.0)

Updates `Distributions` to 0.25.126
- [Release notes](https://github.com/JuliaStats/Distributions.jl/releases)
- [Commits](JuliaStats/Distributions.jl@0.2.2...v0.25.126)

Updates `Bijectors` to 0.16.0
- [Release notes](https://github.com/TuringLang/Bijectors.jl/releases)
- [Changelog](https://github.com/TuringLang/Bijectors.jl/blob/main/HISTORY.md)
- [Commits](TuringLang/Bijectors.jl@v0.1.0...v0.16.0)

Updates `LogDensityProblems` to 2.2.0
- [Release notes](https://github.com/tpapp/LogDensityProblems.jl/releases)
- [Changelog](https://github.com/tpapp/LogDensityProblems.jl/blob/master/CHANGELOG.md)
- [Commits](tpapp/LogDensityProblems.jl@v0.1.0...v2.2.0)

Updates `AbstractPPL` to 0.15.2
- [Release notes](https://github.com/TuringLang/AbstractPPL.jl/releases)
- [Changelog](https://github.com/TuringLang/AbstractPPL.jl/blob/main/HISTORY.md)
- [Commits](TuringLang/AbstractPPL.jl@v0.1.0...v0.15.2)

Updates `ADTypes` to 1.22.0
- [Release notes](https://github.com/SciML/ADTypes.jl/releases)
- [Commits](SciML/ADTypes.jl@v0.1.0...v1.22.0)

Updates `ForwardDiff` to 1.3.3
- [Release notes](https://github.com/JuliaDiff/ForwardDiff.jl/releases)
- [Commits](JuliaDiff/ForwardDiff.jl@v0.0.2...v1.3.3)

Updates `DynamicPPL` to 0.42.0
- [Release notes](https://github.com/TuringLang/DynamicPPL.jl/releases)
- [Changelog](https://github.com/TuringLang/DynamicPPL.jl/blob/main/HISTORY.md)
- [Commits](v0.1.0...v0.42.0)

Updates `DifferentiationInterface` to 0.7.18
- [Release notes](https://github.com/JuliaDiff/DifferentiationInterface.jl/releases)
- [Commits](JuliaDiff/DifferentiationInterface.jl@DifferentiationInterface-v0.1.0...DifferentiationInterface-v0.7.18)

---
updated-dependencies:
- dependency-name: OrderedCollections
  dependency-version: 2.0.0
  dependency-type: direct:production
  dependency-group: all-julia-packages
- dependency-name: OrderedCollections
  dependency-version: 2.0.0
  dependency-type: direct:production
  dependency-group: all-julia-packages
- dependency-name: StatsFuns
  dependency-version: 2.0.1
  dependency-type: direct:production
  dependency-group: all-julia-packages
- dependency-name: OrderedCollections
  dependency-version: 2.0.0
  dependency-type: direct:production
  dependency-group: all-julia-packages
- dependency-name: DynamicPPL
  dependency-version: 0.42.0
  dependency-type: direct:production
  dependency-group: all-julia-packages
- dependency-name: Bijectors
  dependency-version: 0.16.0
  dependency-type: direct:production
  dependency-group: all-julia-packages
- dependency-name: AbstractPPL
  dependency-version: 0.15.2
  dependency-type: direct:production
  dependency-group: all-julia-packages
- dependency-name: ADTypes
  dependency-version: 1.22.0
  dependency-type: direct:production
  dependency-group: all-julia-packages
- dependency-name: ForwardDiff
  dependency-version: 1.3.3
  dependency-type: direct:production
  dependency-group: all-julia-packages
- dependency-name: DynamicPPL
  dependency-version: 0.42.0
  dependency-type: direct:production
  dependency-group: all-julia-packages
- dependency-name: DifferentiationInterface
  dependency-version: 0.7.18
  dependency-type: direct:production
  dependency-group: all-julia-packages
- dependency-name: Enzyme
  dependency-version: 0.13.153
  dependency-type: direct:production
  dependency-group: all-julia-packages
- dependency-name: AbstractPPL
  dependency-version: 0.15.2
  dependency-type: direct:production
  dependency-group: all-julia-packages
- dependency-name: DynamicPPL
  dependency-version: 0.42.0
  dependency-type: direct:production
  dependency-group: all-julia-packages
- dependency-name: Distributions
  dependency-version: 0.25.126
  dependency-type: direct:production
  dependency-group: all-julia-packages
- dependency-name: Bijectors
  dependency-version: 0.16.0
  dependency-type: direct:production
  dependency-group: all-julia-packages
- dependency-name: LogDensityProblems
  dependency-version: 2.2.0
  dependency-type: direct:production
  dependency-group: all-julia-packages
- dependency-name: AbstractPPL
  dependency-version: 0.15.2
  dependency-type: direct:production
  dependency-group: all-julia-packages
- dependency-name: ADTypes
  dependency-version: 1.22.0
  dependency-type: direct:production
  dependency-group: all-julia-packages
- dependency-name: ForwardDiff
  dependency-version: 1.3.3
  dependency-type: direct:production
  dependency-group: all-julia-packages
- dependency-name: DynamicPPL
  dependency-version: 0.42.0
  dependency-type: direct:production
  dependency-group: all-julia-packages
- dependency-name: Distributions
  dependency-version: 0.25.126
  dependency-type: direct:production
  dependency-group: all-julia-packages
- dependency-name: Bijectors
  dependency-version: 0.16.0
  dependency-type: direct:production
  dependency-group: all-julia-packages
- dependency-name: LogDensityProblems
  dependency-version: 2.2.0
  dependency-type: direct:production
  dependency-group: all-julia-packages
- dependency-name: AbstractPPL
  dependency-version: 0.15.2
  dependency-type: direct:production
  dependency-group: all-julia-packages
- dependency-name: ADTypes
  dependency-version: 1.22.0
  dependency-type: direct:production
  dependency-group: all-julia-packages
- dependency-name: ForwardDiff
  dependency-version: 1.3.3
  dependency-type: direct:production
  dependency-group: all-julia-packages
- dependency-name: DynamicPPL
  dependency-version: 0.42.0
  dependency-type: direct:production
  dependency-group: all-julia-packages
- dependency-name: DifferentiationInterface
  dependency-version: 0.7.18
  dependency-type: direct:production
  dependency-group: all-julia-packages
...

Signed-off-by: dependabot[bot] <support@github.com>
@dependabot dependabot Bot added dependencies Pull requests that update a dependency file julia Pull requests that update julia code labels Jun 5, 2026
@github-actions

github-actions Bot commented Jun 5, 2026

Copy link
Copy Markdown
Contributor

DynamicPPL.jl documentation for PR #1422 is available at:
https://TuringLang.github.io/DynamicPPL.jl/previews/PR1422/

@github-actions

github-actions Bot commented Jun 5, 2026

Copy link
Copy Markdown
Contributor

Benchmarks @ b24c6e1

Performance Ratio: gradient time divided by log-density time.

For very small models these ratios are noisy across runs and machines; raw primal and gradient timings are more reliable. The benchmarks are aimed at DynamicPPL developers and mainly catch obvious allocation or type-stability regressions. See benchmark notes for details.

===================================================================================================
                                               eval                       gradient                 
                                            ----------  -------------------------------------------
Model                        dim    linked      primal     FwdDiff    RvsDiff    Mooncake    Enzyme
---------------------------------------------------------------------------------------------------
Simple assume observe*         1     false     4.64 ns       12.50    1519.75       35.40     12.73
Simple assume observe*         1      true     4.64 ns       12.57    1667.40       35.65     12.45
Smorgasbord                  201     false      6.0 μs       71.54     132.17        6.82      9.69
Smorgasbord                  201      true     7.63 μs       73.98     144.16        6.14      7.08
Loop univariate 1k          1000     false     17.9 μs      938.76     295.70        8.00      6.51
Loop univariate 1k          1000      true     19.3 μs     1419.27     280.15        7.38      6.02
Multivariate 1k             1000     false     23.3 μs      330.60      72.32        9.37      3.00
Multivariate 1k             1000      true     21.8 μs      281.26      62.15       10.16      3.05
Loop univariate 10k        10000     false    174.0 μs    11925.97     335.28        8.27      6.71
Loop univariate 10k        10000      true    188.0 μs    11774.72     308.34        7.58      6.22
Multivariate 10k           10000     false    197.0 μs     5036.34      89.62       12.09      2.36
Multivariate 10k           10000      true    199.0 μs     5035.33      89.64       11.35      2.34
Dynamic                       15     false     1.41 μs         err      44.59       15.41     11.31
Dynamic                       10      true     1.94 μs        1.97      57.09       15.71     20.87
Submodel*                      1     false     4.65 ns       12.54    1726.52       35.51     12.58
Submodel*                      1      true     4.64 ns       12.64    1920.07       35.42     12.45
LDA                           12      true     23.2 μs        0.58       2.13       33.32       err
===================================================================================================
Main @ b887a35 
===================================================================================================
                                               eval                       gradient                 
                                            ----------  -------------------------------------------
Model                        dim    linked      primal     FwdDiff    RvsDiff    Mooncake    Enzyme
---------------------------------------------------------------------------------------------------
Simple assume observe*         1     false     3.28 ns       14.39    1466.54       43.22     19.40
Simple assume observe*         1      true     3.27 ns       14.17    1618.13       43.90     19.15
Smorgasbord                  201     false      4.5 μs       96.48     137.83        7.35      7.53
Smorgasbord                  201      true     5.84 μs      101.28     140.86        6.30      5.68
Loop univariate 1k          1000     false     12.6 μs     1611.50     318.67       10.43      8.21
Loop univariate 1k          1000      true     15.4 μs     2116.04     263.16        8.16      6.65
Multivariate 1k             1000     false     19.0 μs      475.41      59.22        8.28      2.05
Multivariate 1k             1000      true     18.9 μs      443.42      64.41        9.06      2.00
Loop univariate 10k        10000     false    122.0 μs    21345.54     373.54       10.14      8.04
Loop univariate 10k        10000      true    150.0 μs    19539.28     308.15        8.44      6.51
Multivariate 10k           10000     false    171.0 μs     7240.08      78.84        9.89      1.80
Multivariate 10k           10000      true    173.0 μs     6985.23      77.46        9.95      1.84
Dynamic                       15     false     1.08 μs         err      44.62       14.58     12.82
Dynamic                       10      true     1.56 μs        2.18      61.85       13.76     20.30
Submodel*                      1     false     3.28 ns       14.43    1770.12       44.12     19.32
Submodel*                      1      true     3.28 ns       14.44    2039.98       44.54     19.53
LDA                           12      true     16.9 μs        0.63       2.53       37.72       err
===================================================================================================
Environment 
Julia Version 1.11.9
Commit 53a02c0720c (2026-02-06 00:27 UTC)
Build Info:
  Official https://julialang.org/ release
Platform Info:
  OS: Linux (x86_64-linux-gnu)
  CPU: 4 × AMD EPYC 7763 64-Core Processor
  WORD_SIZE: 64
  LLVM: libLLVM-16.0.6 (ORCJIT, znver3)
Threads: 1 default, 0 interactive, 1 GC (on 4 virtual cores)

@dependabot @github

dependabot Bot commented on behalf of github Jun 10, 2026

Copy link
Copy Markdown
Contributor Author

Superseded by #1424.

@dependabot dependabot Bot closed this Jun 10, 2026
@dependabot dependabot Bot deleted the dependabot/julia/all-julia-packages-3953652f89 branch June 10, 2026 03:57
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment

Reviewers

No reviews

Assignees

No one assigned

Labels

dependencies Pull requests that update a dependency file julia Pull requests that update julia code

Projects

None yet

Milestone

No milestone

Development

Successfully merging this pull request may close these issues.

0 participants