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Bump patch version to 0.41.8#1397

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bump-0.41.8
May 18, 2026
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Bump patch version to 0.41.8#1397
sunxd3 merged 1 commit into
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bump-0.41.8

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@sunxd3 sunxd3 commented May 18, 2026

Bumps the patch version following #1395

@TuringLang TuringLang deleted a comment from JuliaRegistrator May 18, 2026
@sunxd3 sunxd3 merged commit 9e5ae37 into main May 18, 2026
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@sunxd3 sunxd3 deleted the bump-0.41.8 branch May 18, 2026 17:53
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DynamicPPL.jl documentation for PR #1397 is available at:
https://TuringLang.github.io/DynamicPPL.jl/previews/PR1397/

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codecov Bot commented May 18, 2026

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 82.30%. Comparing base (90a74c3) to head (1d4f703).
⚠️ Report is 1 commits behind head on main.

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@@           Coverage Diff           @@
##             main    #1397   +/-   ##
=======================================
  Coverage   82.30%   82.30%           
=======================================
  Files          50       50           
  Lines        3543     3543           
=======================================
  Hits         2916     2916           
  Misses        627      627           

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Benchmarks @ 1d4f703

=================================================================================================
                                              eval                      gradient                 
                                           ----------  ------------------------------------------
Model                       dim    linked      primal    FwdDiff    RvsDiff    Mooncake    Enzyme
-------------------------------------------------------------------------------------------------
Simple assume observe         1     false     5.88 ns       9.32    1111.21       28.81      6.24
Simple assume observe         1      true     23.9 ns       2.48     328.40        7.08      1.58
Smorgasbord                 201     false     6.43 μs      68.50     123.39        6.30      8.91
Smorgasbord                 201      true     8.92 μs      64.60     119.18        5.09      5.91
Loop univariate 1k         1000     false     19.6 μs     961.02     257.99        7.14      5.87
Loop univariate 1k         1000      true     21.0 μs    1349.73     248.20        6.68      5.60
Multivariate 1k            1000     false     23.4 μs     332.11      71.56        9.13      3.04
Multivariate 1k            1000      true     26.8 μs     267.07      60.42        8.64      3.02
Loop univariate 10k       10000     false    202.0 μs    9853.93     276.52        7.25      5.86
Loop univariate 10k       10000      true    218.0 μs    9986.22     262.31        6.75      5.44
Multivariate 10k          10000     false    219.0 μs    4460.83      79.97       10.43      2.14
Multivariate 10k          10000      true    219.0 μs    4402.55      80.15       10.57      2.14
Dynamic                      15     false      1.4 μs        err      41.05       13.44     10.78
Dynamic                      10      true     1.96 μs       1.95      55.88       11.52     18.21
Submodel                      1     false     5.88 ns      10.25    1314.91       28.21      6.26
Submodel                      1      true     5.88 ns      10.19    1414.61       29.09      6.19
LDA                          12      true     22.5 μs       0.47       1.98       33.70       err
=================================================================================================

Each row times one of DynamicPPL's reference models on this PR's head. Dim is the parameter count; Linked is true when parameters have been mapped to unconstrained space. t(logdensity) is the wall-clock time for one log-density evaluation. The AD (automatic differentiation) backend columns express gradient time as a multiple of t(logdensity) — a value of 10 means computing the gradient takes 10× as long as the log-density. Lower is better throughout; err means the backend errored on that model. Compare against main below to spot regressions.

Main @ 90a74c3
==================================================================================================
                                              eval                       gradient                 
                                           ----------  -------------------------------------------
Model                       dim    linked      primal     FwdDiff    RvsDiff    Mooncake    Enzyme
--------------------------------------------------------------------------------------------------
Simple assume observe         1     false     5.22 ns       10.58    1111.09       27.99      4.90
Simple assume observe         1      true     18.5 ns        3.06     415.80        8.61      3.29
Smorgasbord                 201     false     9.61 μs       54.34      82.83        7.82      5.87
Smorgasbord                 201      true     19.9 μs       28.57      53.41        4.17      2.84
Loop univariate 1k         1000     false     50.8 μs      376.20     101.22        3.83      2.65
Loop univariate 1k         1000      true     51.0 μs      523.33     103.80        4.03      2.87
Multivariate 1k            1000     false     43.0 μs      226.55      38.02        5.00      1.85
Multivariate 1k            1000      true     41.5 μs      244.36      40.27        5.37      1.71
Loop univariate 10k       10000     false    238.0 μs    10720.24     233.84        6.00      5.20
Loop univariate 10k       10000      true    245.0 μs    11804.24     230.75        5.91      4.91
Multivariate 10k          10000     false    245.0 μs     6526.90      70.50        8.54      1.79
Multivariate 10k          10000      true    248.0 μs     6392.60      70.45        8.40      1.77
Dynamic                      15     false      2.4 μs         err      30.78       11.64      8.33
Dynamic                      10      true     3.15 μs        1.96      40.84        9.84     13.55
Submodel                      1     false     5.16 ns       22.09    1399.01       53.46     12.61
Submodel                      1      true     5.21 ns       22.08    1475.45       53.43     12.11
LDA                          12      true     28.7 μs        0.60       2.05       24.37       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)

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