Serious regression of warp! about imagetransformations.jl HOT 7 CLOSED

Profiling points to getindex, which we hoped was fixed by JuliaLang/julia#28707. But the OP's example is even worse on a recent nightly of Julia (after that PR).
Is @timholy's overhaul of Interpolations.jl likely to make compiler optimization any more effective for interpolation objects, or do we need to pray for more magic from Keno?

from imagetransformations.jl.

Returning out is not a problem. It doesn't allocate any additional memory, and allows the result to be used pipelines. (Unlike, e.g., pandas, there's no convention that functions which modify their parameters in place return nothing.)

from imagetransformations.jl.

Yes. Returning is not a problem. The question here is what the problem is.

from imagetransformations.jl.

Thanks for the report. I'll investigate soon when I find some time

from imagetransformations.jl.

The real issue is inferring length, which is special-cased for Tuples. Relevant: JuliaLang/julia#27434 (comment)

from imagetransformations.jl.

I'm glad that @Evizero caught my mistake. The sad thing is that I knew better last year.

Is it the case that splatting (almost?) anything other than a Tuple leads to dynamic dispatch, which can foul up inference in various (hard-to-predict) ways?

from imagetransformations.jl.

No worries, these things happen to us all. If anything I should have caught it in the review. Your contributions are a clear net positive and we are lucky to have you. The occasional regression is to be expected and nothing we can't fix

from imagetransformations.jl.