SciML / SciML/ExponentialUtilities.jl
Avoid generated function in generic_exp
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- Dominant language
- Julia
- Stars
- 107
- Forks
- 35
- Avg merge
- 22h 52m
- Merged PRs (30d)
- 11
Description
The current implementation relies on methods being defined for special number types before https://github.com/SciML/ExponentialUtilities.jl/blob/fce7ae64e8507baf7ce98d268e46478c7a1540ab/src/exp.jl#L127-L135 is being called, see item 4 in https://docs.julialang.org/en/v1/manual/metaprogramming/#Generated-functions-1. If not then you'll hit a world age error. E.g.
julia> using ExponentialUtilities
julia> f = t -> exp_generic(t)
#1 (generic function with 1 method)
julia> f(0.3)
1.3498588075760032
julia> using ForwardDiff
julia> ForwardDiff.derivative(f, 0.2)
ERROR: MethodError: no method matching ForwardDiff.Dual{ForwardDiff.Tag{var"#1#2",Float64},Float64,1}(::Int64)
The applicable method may be too new: running in world age 27795, while current world is 27806.
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start in src/exp.jl at lines 127-135 and reproduce the reported generic_exp call followed by ForwardDiff.derivative. Trace how the generated function handles special number types and verify that the completed change no longer produces the reported world age or constructor MethodError.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- julia
- Domain
- backend
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 45/100