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functionismacro(@nospecialize(f::FT)) where {FT<:Function}
isdefined(FT, :name) ||returnfalse
tn = FT.name::Core.TypeNamereturnoccursin('@', string(tn.name))
end
gets rid of the performance regression anyway, so I'm okay with it if the slowness of methods can't be helped in order to circumvent the latency issues.
The text was updated successfully, but these errors were encountered:
aviatesk
added a commit
to JunoLab/Atom.jl
that referenced
this issue
Oct 16, 2020
MRE:
The profiling shows most of the time is spent in
_methods_by_ftype
, and I guess #35983 might be the source of this.Well, I'm not sure the performance for
methods
is critical; I found this problem just because Juno's completions are much slower than before when using Julia built from master, and profiling shows that this line callingmethods
is the source of the performance regression:https://github.com/JunoLab/Atom.jl/blob/c751731bd488db815110ed7771b7f313d8b92116/src/utils.jl#L268
Now I found changing this line into
gets rid of the performance regression anyway, so I'm okay with it if the slowness of
methods
can't be helped in order to circumvent the latency issues.The text was updated successfully, but these errors were encountered: