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Add support for external method tables (JuliaLang/julia#39697)
This PR implements a way to keep tables of methods that are not part of the internal method table, but still participate in the special support we have for keeping tables of methods, in particular unification through precompilation and efficient lookup. The intended design use case is to allow for method overlay tables for various non-CPU backends (e.g. GPU and TPU). These backends would like to modify basic function like `sin` to perform better on the device in question (or in the case of TPU to define them over non-LLVM intrinsics). It is worth noting that this PR only gives the ability to keep these tables of methods. It assigns no particular meaning to them and the runtime (and regular inference) do not look at them. They are designed as an implementation detail for external compilers and similar tools. # Demo ```julia julia> using Base.Experimental: @overlay, @MethodTable julia> @MethodTable(mt) # 0 methods: julia> @overlay mt function sin(x::Float64) 1 end julia> @overlay mt function cos(x::Float64) 1 end julia> mt # 2 methods: [1] cos(x::Float64) in Main at REPL[5]:1 [2] sin(x::Float64) in Main at REPL[4]:1 julia> Base._methods_by_ftype(Tuple{typeof(sin), Float64}, mt, 1, typemax(UInt)) 1-element Vector{Any}: Core.MethodMatch(Tuple{typeof(sin), Float64}, svec(), sin(x::Float64) in Main at REPL[4]:1, true) julia> Base._methods_by_ftype(Tuple{typeof(sin), Float64}, 1, typemax(UInt)) 1-element Vector{Any}: Core.MethodMatch(Tuple{typeof(sin), Float64}, svec(Float64), sin(x::T) where T<:Union{Float32, Float64} in Base.Math at special/trig.jl:29, true) ``` Co-authored-by: Tim Besard <tim.besard@gmail.com> Co-authored-by: Julian P Samaroo <jpsamaroo@jpsamaroo.me> Co-authored-by: Keno Fischer <keno@juliacomputing.com>
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