InitContext, part 5 - Remove SamplingContext, SampleFrom{Prior,Uniform}, {tilde_,}assume

[penelopeysm]

Part 1: Adding hasvalue and getvalue to AbstractPPL
Part 2: Removing hasvalue and getvalue from DynamicPPL
Part 3: Introducing InitContext and init!!
Part 4: Using ParamsInit to implement predict, returned, and initialize_values

This is part 5/N of #967.

This PR removes everything that is no longer needed. SamplingContext, SampleFromPrior, SampleFromUniform, now have direct one-to-one replacements (albeit with slightly different behaviour since they now always overwrite variables in the varinfo).

It also removes assume and tilde_assume.

Prior to this PR we had two different kinds of assume, one with a sampler and one without. Now we only have the one without, so we can just move that definition into tilde_assume!!(::DefaultContext, ...).

Finally, tilde_assume has been subsumed into tilde_assume!! as we can just dispatch on the type of right. (Previously this wasn't possible because there was a lot of stuff about is_rhs_model, etc. etc. which was removed in #960.)

Closes #859
Closes #955

[github-actions]

Benchmark Report for Commit 7aae613

Computer Information

Julia Version 1.11.6
Commit 9615af0f269 (2025-07-09 12:58 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 | Dimension |  AD Backend |      VarInfo Type | Linked | Eval Time / Ref Time | AD Time / Eval Time |
|-----------------------|-----------|-------------|-------------------|--------|----------------------|---------------------|
| Simple assume observe |         1 | forwarddiff |             typed |  false |                 13.6 |                 1.4 |
|           Smorgasbord |       201 | forwarddiff |             typed |  false |                772.3 |                37.5 |
|           Smorgasbord |       201 | forwarddiff | simple_namedtuple |   true |                422.1 |                57.3 |
|           Smorgasbord |       201 | forwarddiff |           untyped |   true |               1106.4 |                32.9 |
|           Smorgasbord |       201 | forwarddiff |       simple_dict |   true |               7728.7 |                26.6 |
|           Smorgasbord |       201 | reversediff |             typed |   true |               1148.7 |                36.4 |
|           Smorgasbord |       201 |    mooncake |             typed |   true |               1119.6 |                12.4 |
|    Loop univariate 1k |      1000 |    mooncake |             typed |   true |               6996.7 |                52.1 |
|       Multivariate 1k |      1000 |    mooncake |             typed |   true |               1015.3 |                 8.9 |
|   Loop univariate 10k |     10000 |    mooncake |             typed |   true |              83355.2 |                47.9 |
|      Multivariate 10k |     10000 |    mooncake |             typed |   true |               8411.9 |                10.0 |
|               Dynamic |        10 |    mooncake |             typed |   true |                140.8 |                23.9 |
|              Submodel |         1 |    mooncake |             typed |   true |                 18.1 |                26.6 |
|                   LDA |        12 | reversediff |             typed |   true |               1212.8 |                 1.9 |

[codecov]

Codecov Report

❌ Patch coverage is 89.47368% with 2 lines in your changes missing coverage. Please review.
⚠️ Please upload report for BASE (py/actually-use-init@4c96020). Learn more about missing BASE report.

Files with missing lines	Patch %	Lines
src/context_implementations.jl	86.66%	2 Missing ⚠️

Additional details and impacted files

@@                   Coverage Diff                   @@
##             py/actually-use-init     #985   +/-   ##
=======================================================
  Coverage                        ?   79.89%           
=======================================================
  Files                           ?       39           
  Lines                           ?     3914           
  Branches                        ?        0           
=======================================================
  Hits                            ?     3127           
  Misses                          ?      787           
  Partials                        ?        0           

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

🚀 New features to boost your workflow:

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

[github-actions]

DynamicPPL.jl documentation for PR #985 is available at:
https://TuringLang.github.io/DynamicPPL.jl/previews/PR985/

[penelopeysm]

It's maybe a bit opinionated to delete this file. I personally don't see the point of it. It's essentially testing that rand(::LKJ) or rand(::LKJCholesky) works (which is a Distributions problem) and/or testing that LKJ / LKJCholesky linking works correctly (which is a Bijectors problem).

The direct replacement for these tests would be something like this:

for init_strategy in [PriorInit(), UniformInit()]
    lkjchol_samples = [DynamicPPL.init(Random.default_rng, @varname(x), LKJCholesky(...), init_strategy) for _ in 1:1000]
    @test isapprox(mean(lkjchol_samples), expected_mean)
end

However, I don't quite see why we should perform this test for LKJ/LKJCholesky and not for any other distributions. DynamicPPL.init only uses Bijectors functionality, and the only reason why we would test LKJ specifically is if we were concerned about Bijectors' reliability on LKJ. But that should be tested in Bijectors, not here.

[penelopeysm]

I couldn't find a way to reproduce this test without SamplingContext and the whole tilde-pipeline machinery that this PR removes, so I think that this is no longer relevant.