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WIP improve frule inference#202

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kf/genericinferencewip
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WIP improve frule inference#202
aviatesk wants to merge 4 commits into
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kf/genericinferencewip

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Keno and others added 2 commits July 31, 2023 16:21
@aviatesk aviatesk force-pushed the kf/genericinferencewip branch from c39a1ce to 607ba18 Compare July 31, 2023 21:06
Comment thread src/stage2/interpreter.jl Outdated
aviatesk added a commit to JuliaLang/julia that referenced this pull request Jul 31, 2023
Currently, the code that updates `bestguess` using `ReturnNode`
information includes hardcodes that relate to `Conditional` and
`LimitedAccuracy`. These behaviors are actually lattice-dependent and
therefore should be overloadable by `AbstractInterpreter`.

Additionally, particularly in Diffractor, a clever strategy is required
to update return types in a way that it takes into account information
from both the original method and its rule method
(xref: JuliaDiff/Diffractor.jl#202). This also requires such an overload
to exist.
In response to these needs, this commit introduces an implementation of
a hook named `update_bestguess!`.
@codecov

codecov Bot commented Jul 31, 2023

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Codecov Report

❌ Patch coverage is 69.23077% with 4 lines in your changes missing coverage. Please review.
✅ Project coverage is 54.96%. Comparing base (9b2a506) to head (2438a47).
⚠️ Report is 202 commits behind head on main.

Files with missing lines Patch % Lines
src/stage2/interpreter.jl 69.23% 4 Missing ⚠️
Additional details and impacted files
@@            Coverage Diff             @@
##             main     #202      +/-   ##
==========================================
- Coverage   55.01%   54.96%   -0.06%     
==========================================
  Files          28       28              
  Lines        2790     2800      +10     
==========================================
+ Hits         1535     1539       +4     
- Misses       1255     1261       +6     

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aviatesk added a commit to JuliaLang/julia that referenced this pull request Aug 1, 2023
Currently, the code that updates `bestguess` using `ReturnNode`
information includes hardcodes that relate to `Conditional` and
`LimitedAccuracy`. These behaviors are actually lattice-dependent and
therefore should be overloadable by `AbstractInterpreter`.

Additionally, particularly in Diffractor, a clever strategy is required
to update return types in a way that it takes into account information
from both the original method and its rule method
(xref: JuliaDiff/Diffractor.jl#202). This also requires such an overload
to exist.
In response to these needs, this commit introduces an implementation of
a hook named `update_bestguess!`.
aviatesk added a commit to JuliaLang/julia that referenced this pull request Aug 1, 2023
…50744)

Currently, the code that updates `bestguess` using `ReturnNode`
information includes hardcodes that relate to `Conditional` and
`LimitedAccuracy`. These behaviors are actually lattice-dependent and
therefore should be overloadable by `AbstractInterpreter`.

Additionally, particularly in Diffractor, a clever strategy is required
to update return types in a way that it takes into account information
from both the original method and its rule method
(xref: JuliaDiff/Diffractor.jl#202). This also requires such an overload
to exist.
In response to these needs, this commit introduces an implementation of
a hook named `update_bestguess!`.
@aviatesk aviatesk requested a review from Copilot July 3, 2026 01:42

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Pull request overview

Updates ADInterpreter to support an alternate “generic inference” mode intended to work with Julia’s bestguess-overload branch by allowing a converged-inference pathway (current_level === missing) and hooking into Core.Compiler’s bestguess initialization/update points.

Changes:

  • Extend ADInterpreter with a generic cache and widen current_level to Union{Int,Missing}.
  • Add conditional overloads for CC.InferenceState and CC.update_bestguess! (guarded on CC.update_bestguess! existing) to override bestguess behavior when current_level === missing.
  • Remove an older abstract_call_gf_by_type compatibility overload.

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Comment thread src/stage2/interpreter.jl
Comment on lines 61 to 63
native_interpreter::NativeInterpreter
current_level::Int
current_level::Union{Int, Missing}
remarks::OffsetVector{RemarksCache}
Comment thread src/stage2/interpreter.jl
Comment on lines 73 to 75
#=native_interpreter::NativeInterpreter=#NativeInterpreter(),
#=current_level::Int=#0,
#=remarks::OffsetVector{RemarksCache}=#OffsetVector([RemarksCache()], 0:0))
Comment thread src/stage2/interpreter.jl
Comment on lines +58 to +60
# Cache results for forward inference over a converged inference (current_level == missing)
generic::OptCache

Comment thread src/stage2/interpreter.jl
Comment on lines +101 to +120
function CC.InferenceState(result::InferenceResult, cache::Symbol, interp::ADInterpreter)
sv = @invoke CC.InferenceState(result::InferenceResult, cache::Symbol, interp::AbstractInterpreter)
sv === nothing && return sv
if interp.current_level === missing
# override initial bestguess
arginfo = ArgInfo(nothing, result.argtypes)
si = StmtInfo(false)
sv.bestguess = CC.abstract_call(interp.native_interpreter, arginfo, si, sv).rt
end
return sv
end

function CC.update_bestguess!(interp::ADInterpreter, frame::InferenceState,
currstate::CC.VarTable, @nospecialize(rt))
if interp.current_level === missing
rt = CC.getfield_tfunc(rt, Const(1))
end
return @invoke CC.update_bestguess!(interp::AbstractInterpreter, frame::InferenceState,
currstate::CC.VarTable, rt::Any)
end
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3 participants