JuliaDiff / JuliaDiff/ForwardDiff.jl
missing method big(::Dual)
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- Dominant language
- Julia
- Stars
- 1k
- Forks
- 160
- PR merge metrics
- No merged PRs in 30d
Description
It seems like this should work. All that is needed is:
Base.big(x::Dual{T}) where {T} = Dual{T}(big(x.value), big(x.partials))
Base.big(p::Partials) = Partials(big.(p.values))
(Mentioned on discourse.)
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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
Locate the Dual and Partials definitions in ForwardDiff.jl and check how their value and partial fields are represented. Review the linked Discourse discussion and current Base.big behavior, then verify the proposed methods for both types. Done means big(::Dual) and big(::Partials) support the reported BigFloat optimization case without regressions.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- julia
- Domain
- backend-api-design
- Issue type
- Feature
- Difficulty
- 2/5
- Estimated time
- 1-3 hours
- Activity status
- Stale
- Clarity
- Clearly specified
- Newbie friendliness
- 45/100