CompatHelper: bump compat for OrderedCollections to 2 for package test, (keep existing compat)

[github-actions]

This pull request changes the compat entry for the OrderedCollections package from 1 to 1, 2 for package test.
This keeps the compat entries for earlier versions.

Note: I have not tested your package with this new compat entry.
It is your responsibility to make sure that your package tests pass before you merge this pull request.

[codecov]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 27.02%. Comparing base (9347d11) to head (9d1c75f).

❗ There is a different number of reports uploaded between BASE (9347d11) and HEAD (9d1c75f). Click for more details.

HEAD has 12 uploads less than BASE

Flag	BASE (9347d11)	HEAD (9d1c75f)
	15	3

Additional details and impacted files

@@             Coverage Diff             @@
##             main    #1419       +/-   ##
===========================================
- Coverage   81.58%   27.02%   -54.56%     
===========================================
  Files          50       49        -1     
  Lines        3578     3534       -44     
===========================================
- Hits         2919      955     -1964     
- Misses        659     2579     +1920     

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[github-actions]

DynamicPPL.jl documentation for PR #1419 is available at:
https://TuringLang.github.io/DynamicPPL.jl/previews/PR1419/

[github-actions]

Benchmarks @ 9d1c75f

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     4.63 ns       12.51    1469.63       39.46     12.41
Simple assume observe*         1      true     4.63 ns       12.50    1668.13       35.43     12.29
Smorgasbord                  201     false     5.93 μs       71.27     133.62        6.75      9.61
Smorgasbord                  201      true     7.57 μs       77.26     140.80        6.22      6.97
Loop univariate 1k          1000     false     17.9 μs      930.19     304.95        8.02      6.54
Loop univariate 1k          1000      true     19.1 μs     1338.78     289.32        7.48      6.07
Multivariate 1k             1000     false     23.2 μs      316.51      71.33        9.45      3.07
Multivariate 1k             1000      true     21.8 μs      293.33      62.00       10.43      2.96
Loop univariate 10k        10000     false    174.0 μs    11771.32     333.66        8.27      6.67
Loop univariate 10k        10000      true    187.0 μs    12371.89     312.18        7.68      6.23
Multivariate 10k           10000     false    198.0 μs     5778.17      86.43       11.38      2.30
Multivariate 10k           10000      true    197.0 μs     5670.92      88.19       11.31      2.33
Dynamic                       15     false     1.39 μs         err      44.97       16.00     11.05
Dynamic                       10      true     1.91 μs        2.00      57.69       12.79     20.88
Submodel*                      1     false     4.63 ns       12.51    1757.48       40.93     12.30
Submodel*                      1      true     4.63 ns       12.76    1852.32       35.52     12.48
LDA                           12      true     23.0 μs        0.58       2.04       33.79       err
===================================================================================================

Main @ 9347d11

===================================================================================================
                                               eval                       gradient                 
                                            ----------  -------------------------------------------
Model                        dim    linked      primal     FwdDiff    RvsDiff    Mooncake    Enzyme
---------------------------------------------------------------------------------------------------
Simple assume observe*         1     false     2.12 ns       23.33    1527.70       53.31     15.69
Simple assume observe*         1      true     2.12 ns       24.41    1725.32       53.65     15.33
Smorgasbord                  201     false     9.19 μs       39.26      45.54        3.53      2.78
Smorgasbord                  201      true     9.75 μs       45.91      56.19        3.66      2.46
Loop univariate 1k          1000     false     17.5 μs      802.45     158.47        5.87      4.03
Loop univariate 1k          1000      true     18.9 μs      962.11     144.75        5.34      3.75
Multivariate 1k             1000     false     31.4 μs      212.31      26.83        4.44      0.85
Multivariate 1k             1000      true     30.8 μs      229.93      27.45        4.80      0.84
Loop univariate 10k        10000     false    173.0 μs    10176.45     170.90        5.95      3.94
Loop univariate 10k        10000      true    186.0 μs    10297.88     158.94        5.52      3.65
Multivariate 10k           10000     false    296.0 μs     3742.89      30.51        5.02      0.64
Multivariate 10k           10000      true    295.0 μs     3921.40      30.65        5.02      0.65
Dynamic                       15     false    947.0 ns         err      39.16        9.22      9.37
Dynamic                       10      true     1.28 μs        1.83      49.29        6.99     16.32
Submodel*                      1     false     2.12 ns       24.34    1741.05       54.00     15.92
Submodel*                      1      true     2.12 ns       24.47    1895.00       53.37     15.93
LDA                           12      true     11.6 μs        0.52       2.46       34.89       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)