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@mhauru mhauru commented Sep 29, 2025

Now that the "del" flag is gone (#1058), the only flag that is ever used is "trans". Hence, no need to bother with having the Dict{String, BitVector} for Metadata.flags, and can instead have a single BitVector for Metadata.trans. EDIT: Renamed to Metadata.is_transformed.

You may wonder, given that Metadata is presumably on its way out, why bother? Two reasons:

  • I tried running the benchmark suite locally with VectorVarInfo, and there were some horrendous performance regressions there compared to using Metadata. Hence, we might not be about to switch over the VarNamedVector imminently.
  • The above experience made me wonder why there was such a performance difference, and whether the Metadata.flags field might actually be a significant cost compared to a BitVector.

My local benchmarking suggests that indeed, this makes a difference:

Before

┌───────────────────────┬───────┬─────────────┬───────────────────┬────────┬────────────────┬─────────────────┐
│                 Model │   Dim │  AD Backend │           VarInfo │ Linked │ t(eval)/t(ref) │ t(grad)/t(eval) │
├───────────────────────┼───────┼─────────────┼───────────────────┼────────┼────────────────┼─────────────────┤
│ Simple assume observe │     1 │ forwarddiff │             typed │  false │           16.0 │             1.7 │
│           Smorgasbord │   201 │ forwarddiff │             typed │  false │          790.6 │            46.1 │
│           Smorgasbord │   201 │ forwarddiff │ simple_namedtuple │   true │          382.0 │            84.3 │
│           Smorgasbord │   201 │ forwarddiff │           untyped │   true │         1431.7 │            36.0 │
│           Smorgasbord │   201 │ forwarddiff │       simple_dict │   true │        10511.1 │            21.6 │
│           Smorgasbord │   201 │ reversediff │             typed │   true │         1495.9 │            42.4 │
│           Smorgasbord │   201 │    mooncake │             typed │   true │         1637.4 │             3.4 │
│    Loop univariate 1k │  1000 │    mooncake │             typed │   true │         8635.9 │             3.2 │
│       Multivariate 1k │  1000 │    mooncake │             typed │   true │         1266.1 │             8.5 │
│   Loop univariate 10k │ 10000 │    mooncake │             typed │   true │        90116.3 │             3.2 │
│      Multivariate 10k │ 10000 │    mooncake │             typed │   true │        10364.2 │             9.7 │
│               Dynamic │    10 │    mooncake │             typed │   true │          235.0 │             5.7 │
│              Submodel │     1 │    mooncake │             typed │   true │           24.0 │             4.2 │
│                   LDA │    12 │ reversediff │             typed │   true │         1391.7 │             2.0 │
└───────────────────────┴───────┴─────────────┴───────────────────┴────────┴────────────────┴─────────────────┘

After

┌───────────────────────┬───────┬─────────────┬───────────────────┬────────┬────────────────┬─────────────────┐
│                 Model │   Dim │  AD Backend │           VarInfo │ Linked │ t(eval)/t(ref) │ t(grad)/t(eval) │
├───────────────────────┼───────┼─────────────┼───────────────────┼────────┼────────────────┼─────────────────┤
│ Simple assume observe │     1 │ forwarddiff │             typed │  false │           10.8 │             2.5 │
│           Smorgasbord │   201 │ forwarddiff │             typed │  false │          695.1 │            53.0 │
│           Smorgasbord │   201 │ forwarddiff │ simple_namedtuple │   true │          319.1 │           104.9 │
│           Smorgasbord │   201 │ forwarddiff │           untyped │   true │         1114.3 │            45.0 │
│           Smorgasbord │   201 │ forwarddiff │       simple_dict │   true │        10323.5 │            22.3 │
│           Smorgasbord │   201 │ reversediff │             typed │   true │         1190.0 │            52.4 │
│           Smorgasbord │   201 │    mooncake │             typed │   true │         1263.0 │             3.8 │
│    Loop univariate 1k │  1000 │    mooncake │             typed │   true │         5606.7 │             4.4 │
│       Multivariate 1k │  1000 │    mooncake │             typed │   true │         1236.0 │             8.7 │
│   Loop univariate 10k │ 10000 │    mooncake │             typed │   true │        63260.7 │             4.2 │
│      Multivariate 10k │ 10000 │    mooncake │             typed │   true │        11029.4 │             9.4 │
│               Dynamic │    10 │    mooncake │             typed │   true │          216.4 │             6.4 │
│              Submodel │     1 │    mooncake │             typed │   true │           19.0 │             4.6 │
│                   LDA │    12 │ reversediff │             typed │   true │         1341.4 │             2.0 │
└───────────────────────┴───────┴─────────────┴───────────────────┴────────┴────────────────┴─────────────────┘

Curious to see whether GHA benchmarks come out looking similar.

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github-actions bot commented Sep 29, 2025

Benchmark Report for Commit a011dd6

Computer Information

Julia Version 1.11.7
Commit f2b3dbda30a (2025-09-08 12:10 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)

Benchmark Results

┌───────────────────────┬───────┬─────────────┬───────────────────┬────────┬────────────────┬─────────────────┐
│                 Model │   Dim │  AD Backend │           VarInfo │ Linked │ t(eval)/t(ref) │ t(grad)/t(eval) │
├───────────────────────┼───────┼─────────────┼───────────────────┼────────┼────────────────┼─────────────────┤
│ Simple assume observe │     1 │ forwarddiff │             typed │  false │            7.4 │             1.6 │
│           Smorgasbord │   201 │ forwarddiff │             typed │  false │          598.5 │            49.3 │
│           Smorgasbord │   201 │ forwarddiff │ simple_namedtuple │   true │          423.2 │            57.6 │
│           Smorgasbord │   201 │ forwarddiff │           untyped │   true │         1063.4 │            32.1 │
│           Smorgasbord │   201 │ forwarddiff │       simple_dict │   true │         6740.1 │            29.0 │
│           Smorgasbord │   201 │ reversediff │             typed │   true │          914.1 │            46.1 │
│           Smorgasbord │   201 │    mooncake │             typed │   true │          875.0 │             5.8 │
│    Loop univariate 1k │  1000 │    mooncake │             typed │   true │         4455.6 │             5.6 │
│       Multivariate 1k │  1000 │    mooncake │             typed │   true │         1020.9 │             9.3 │
│   Loop univariate 10k │ 10000 │    mooncake │             typed │   true │        51734.7 │             4.9 │
│      Multivariate 10k │ 10000 │    mooncake │             typed │   true │         8677.5 │            10.3 │
│               Dynamic │    10 │    mooncake │             typed │   true │          132.2 │            10.9 │
│              Submodel │     1 │    mooncake │             typed │   true │           10.4 │             5.6 │
│                   LDA │    12 │ reversediff │             typed │   true │          992.7 │             2.1 │
└───────────────────────┴───────┴─────────────┴───────────────────┴────────┴────────────────┴─────────────────┘

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codecov bot commented Sep 29, 2025

Codecov Report

❌ Patch coverage is 88.50575% with 10 lines in your changes missing coverage. Please review.
✅ Project coverage is 82.36%. Comparing base (ec65b4f) to head (db64645).
⚠️ Report is 2 commits behind head on breaking.

Files with missing lines Patch % Lines
src/abstract_varinfo.jl 66.66% 3 Missing ⚠️
src/simple_varinfo.jl 78.57% 3 Missing ⚠️
src/threadsafe.jl 75.00% 2 Missing ⚠️
ext/DynamicPPLEnzymeCoreExt.jl 0.00% 1 Missing ⚠️
src/varinfo.jl 97.67% 1 Missing ⚠️
Additional details and impacted files
@@             Coverage Diff              @@
##           breaking    #1060      +/-   ##
============================================
- Coverage     82.38%   82.36%   -0.03%     
============================================
  Files            42       42              
  Lines          3820     3787      -33     
============================================
- Hits           3147     3119      -28     
+ Misses          673      668       -5     

☔ View full report in Codecov by Sentry.
📢 Have feedback on the report? Share it here.

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  • ❄️ Test Analytics: Detect flaky tests, report on failures, and find test suite problems.

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DynamicPPL.jl documentation for PR #1060 is available at:
https://TuringLang.github.io/DynamicPPL.jl/previews/PR1060/

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mhauru commented Sep 30, 2025

CI benchmarks. Target branch:

┌───────────────────────┬───────┬─────────────┬───────────────────┬────────┬────────────────┬─────────────────┐
│                 Model │   Dim │  AD Backend │           VarInfo │ Linked │ t(eval)/t(ref) │ t(grad)/t(eval) │
├───────────────────────┼───────┼─────────────┼───────────────────┼────────┼────────────────┼─────────────────┤
│ Simple assume observe │     1 │ forwarddiff │             typed │  false │            8.5 │             1.6 │
│           Smorgasbord │   201 │ forwarddiff │             typed │  false │          635.2 │            43.6 │
│           Smorgasbord │   201 │ forwarddiff │ simple_namedtuple │   true │          411.8 │            52.7 │
│           Smorgasbord │   201 │ forwarddiff │           untyped │   true │         1163.6 │            29.7 │
│           Smorgasbord │   201 │ forwarddiff │       simple_dict │   true │         6444.2 │            28.6 │
│           Smorgasbord │   201 │ reversediff │             typed │   true │         1022.9 │            40.9 │
│           Smorgasbord │   201 │    mooncake │             typed │   true │          980.1 │             4.5 │
│    Loop univariate 1k │  1000 │    mooncake │             typed │   true │         5750.3 │             4.3 │
│       Multivariate 1k │  1000 │    mooncake │             typed │   true │          964.6 │             9.1 │
│   Loop univariate 10k │ 10000 │    mooncake │             typed │   true │        64679.1 │             3.9 │
│      Multivariate 10k │ 10000 │    mooncake │             typed │   true │         8179.8 │            10.3 │
│               Dynamic │    10 │    mooncake │             typed │   true │          129.7 │            11.3 │
│              Submodel │     1 │    mooncake │             typed │   true │           12.2 │             5.1 │
│                   LDA │    12 │ reversediff │             typed │   true │         1006.2 │             2.0 │
└───────────────────────┴───────┴─────────────┴───────────────────┴────────┴────────────────┴─────────────────┘

This branch:

┌───────────────────────┬───────┬─────────────┬───────────────────┬────────┬────────────────┬─────────────────┐
│                 Model │   Dim │  AD Backend │           VarInfo │ Linked │ t(eval)/t(ref) │ t(grad)/t(eval) │
├───────────────────────┼───────┼─────────────┼───────────────────┼────────┼────────────────┼─────────────────┤
│ Simple assume observe │     1 │ forwarddiff │             typed │  false │            7.4 │             1.7 │
│           Smorgasbord │   201 │ forwarddiff │             typed │  false │          597.3 │            49.0 │
│           Smorgasbord │   201 │ forwarddiff │ simple_namedtuple │   true │          422.1 │            57.4 │
│           Smorgasbord │   201 │ forwarddiff │           untyped │   true │          969.2 │            35.2 │
│           Smorgasbord │   201 │ forwarddiff │       simple_dict │   true │         6575.6 │            31.0 │
│           Smorgasbord │   201 │ reversediff │             typed │   true │          883.4 │            47.6 │
│           Smorgasbord │   201 │    mooncake │             typed │   true │          854.6 │             5.1 │
│    Loop univariate 1k │  1000 │    mooncake │             typed │   true │         4305.0 │             5.6 │
│       Multivariate 1k │  1000 │    mooncake │             typed │   true │          991.4 │             9.5 │
│   Loop univariate 10k │ 10000 │    mooncake │             typed │   true │        50138.4 │             5.1 │
│      Multivariate 10k │ 10000 │    mooncake │             typed │   true │         9003.3 │            10.1 │
│               Dynamic │    10 │    mooncake │             typed │   true │          128.2 │            11.4 │
│              Submodel │     1 │    mooncake │             typed │   true │            9.9 │             5.9 │
│                   LDA │    12 │ reversediff │             typed │   true │          989.8 │             2.1 │
└───────────────────────┴───────┴─────────────┴───────────────────┴────────┴────────────────┴─────────────────┘

Roughly in line with what I saw locally. Seems worth it to me, especially if you look at the Loop univariate 1k and 10k models.

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yebai commented Sep 30, 2025

I suggest we take this chance to rename Metadata.trans to a more readable term, e.g., Metadata.is_unconstrained / Metadata.is_transformed.

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mhauru commented Sep 30, 2025

Good idea, done.

@mhauru mhauru requested a review from penelopeysm September 30, 2025 16:19
Comment on lines 494 to 496
islinked(vi::SimpleVarInfo) = istrans(vi)
islinked(vi::SimpleVarInfo) = is_transformed(vi)
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like this line is just the same function but duplicated. so it feels like to me we could just pick one and roll with it!

@mhauru mhauru requested a review from penelopeysm October 9, 2025 15:18
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Happy to merge after this! Very pleased with the improved performance

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@mhauru I'll leave you to click the green button :)

@mhauru mhauru merged commit 01bf0bc into breaking Oct 10, 2025
18 of 19 checks passed
@mhauru mhauru deleted the mhauru/delete-flags branch October 10, 2025 08:55
penelopeysm added a commit that referenced this pull request Oct 21, 2025
* Bump minor version

* bump benchmarks compat

* add a skeletal changelog

* `InitContext`, part 3 - Introduce `InitContext` (#981)

* Implement InitContext

* Fix loading order of modules; move `prefix(::Model)` to model.jl

* Add tests for InitContext behaviour

* inline `rand(::Distributions.Uniform)`

Note that, apart from being simpler code, Distributions.Uniform also
doesn't allow the lower and upper bounds to be exactly equal (but we
might like to keep that option open in DynamicPPL, e.g. if the user
wants to initialise all values to the same value in linked space).

* Document

* Add a test to check that `init!!` doesn't change linking

* Fix `push!` for VarNamedVector

This should have been changed in #940, but slipped through as the file
wasn't listed as one of the changed files.

* Add some line breaks

Co-authored-by: Markus Hauru <markus@mhauru.org>

* Add the option of no fallback for ParamsInit

* Improve docstrings

* typo

* `p.default` -> `p.fallback`

* Rename `{Prior,Uniform,Params}Init` -> `InitFrom{Prior,Uniform,Params}`

---------

Co-authored-by: Markus Hauru <markus@mhauru.org>

* use `varname_leaves` from AbstractPPL instead (#1030)

* use `varname_leaves` from AbstractPPL instead

* add changelog entry

* fix import

* tidy occurrences of varname_leaves as well (#1031)

* `InitContext`, part 4 - Use `init!!` to replace `evaluate_and_sample!!`, `predict`, `returned`, and `initialize_values` (#984)

* Replace `evaluate_and_sample!!` -> `init!!`

* Use `ParamsInit` for `predict`; remove `setval_and_resample!` and friends

* Use `init!!` for initialisation

* Paper over the `Sampling->Init` context stack (pending removal of SamplingContext)

* Remove SamplingContext from JETExt to avoid triggering `Sampling->Init` pathway

* Remove `predict` on vector of VarInfo

* Fix some tests

* Remove duplicated test

* Simplify context testing

* Rename FooInit -> InitFromFoo

* Fix JETExt

* Fix JETExt properly

* Fix tests

* Improve comments

* Remove duplicated tests

* Docstring improvements

Co-authored-by: Markus Hauru <markus@mhauru.org>

* Concretise `chain_sample_to_varname_dict` using chain value type

* Clarify testset name

* Re-add comment that shouldn't have vanished

* Fix stale Requires dep

* Fix default_varinfo/initialisation for odd models

* Add comment to src/sampler.jl

Co-authored-by: Markus Hauru <markus@mhauru.org>

---------

Co-authored-by: Markus Hauru <markus@mhauru.org>

* `InitContext`, part 5 - Remove `SamplingContext`, `SampleFrom{Prior,Uniform}`, `{tilde_,}assume` (#985)

* Remove `SamplingContext` for good

* Remove `tilde_assume` as well

* Split up tilde_observe!! for Distribution / Submodel

* Tidy up tilde-pipeline methods and docstrings

* Fix tests

* fix ambiguity

* Add changelog

* Update HISTORY.md

Co-authored-by: Markus Hauru <markus@mhauru.org>

---------

Co-authored-by: Markus Hauru <markus@mhauru.org>

* fix missing import

* Shuffle context code around and remove dead code (#1050)

* Delete the `"del"` flag (#1058)

* Delete del

* Fix a typo

* Add HISTORY entry about del

* Fixes for Turing 0.41 (#1057)

* setleafcontext(model, ctx) and various other fixes

* fix a bug

* Add warning for `initial_parameters=...`

* Remove `resume_from` and `default_chain_type` (#1061)

* Remove resume_from

* Format

* Fix test

* remove initial_params warning

* Allow more flexible `initial_params` (#1064)

* Enable NamedTuple/Dict initialisation

* Add more tests

* fix include_all kwarg for predict, improve perf (#1068)

* Fix `include_all` for predict

* Fix include_all for predict, some perf improvements

* Replace `Metadata.flags` with `Metadata.trans` (#1060)

* Replace Medata.flags with Metadata.trans

* Fix a bug

* Fix a typo

* Fix two bugs

* Rename trans to is_transformed

* Rename islinked to is_transformed, remove duplication

* Change pointwise_logdensities default key type to VarName (#1071)

* Change pointwise_logdensities default key type to VarName

* Fix a doctest

* Fix DynamicPPL / MCMCChains methods (#1076)

* Reimplement pointwise_logdensities (almost completely)

* Move logjoint, logprior, ... as well

* Fix imports, etc

* Remove tests that are failing (yes I learnt this from Claude)

* Changelog

* logpdf

* fix docstrings

* allow dict output

* changelog

* fix some comments

* fix tests

* Fix more imports

* Remove stray n

Co-authored-by: Markus Hauru <markus@mhauru.org>

* Expand `logprior`, `loglikelihood`, and `logjoint` docstrings

---------

Co-authored-by: Markus Hauru <markus@mhauru.org>

* Remove `Sampler` and its interface (#1037)

* Remove `Sampler` and `initialstep`

* Actually just remove the entire file

* forgot one function

* Move sampling test utils to Turing as well

* Update changelog to correctly reflect changes

* [skip ci] Make changelog headings more consistent

---------

Co-authored-by: Markus Hauru <markus@mhauru.org>
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