@fastmath does not work in @tullio and exp

General Usage
,
14

Ok, now I can reproduce it. It looks like @turbo is confused by a name with two module qualifiers, Base.FastMath.exp_fast.

julia> using Tullio, LoopVectorization

julia> let rt=rand(100)
         a = @inbounds @fastmath @tullio et[n] := exp(rt[n])  avx=false
         @show sum(a)
         b = @inbounds @fastmath @tullio et[n] := exp(rt[n])
         @show sum(b)
       end;
sum(a) = 165.47486910574332
ERROR: UndefVarError: `exp_fast` not defined
Stacktrace:
 [1] #239#π’œπ’Έπ“‰!
   @ ~/.julia/packages/Tullio/NGyNM/src/macro.jl:1093 [inlined]

Reproducer without @tullio:

julia> let rt = collect(1:0.1:10.0)
         s = 0.0
         for i in eachindex(rt)
           s += exp(rt[i])
         end
         s
       end
231435.5678161179

julia> let rt = collect(1:0.1:10.0)
         s = 0.0
         @turbo for i in eachindex(rt)
           s += exp(rt[i])
         end
         s
       end
231435.56781611795

julia> let rt = collect(1:0.1:10.0)
         s = 0.0
         @turbo for i in eachindex(rt)
           s += Base.FastMath.exp_fast(rt[i])
         end
         s
       end
ERROR: UndefVarError: `exp_fast` not defined
Stacktrace:
 [1] top-level scope
   @ ./REPL[44]:3

julia> let rt = collect(1:0.1:10.0), e_f = Base.FastMath.exp_fast
         s = 0.0
         @turbo for i in eachindex(rt)
           s += e_f(rt[i])
         end
         s
       end
231435.56781611795

While this is a bug, I stress that @fastmath @tullio is not a good idea. You can turn the mode on or off with a keyword, but letting the @fastmath macro change things is liable to cause problems (e.g. here it defeats the calculation of gradients).

I suspect that @fastmath @turbo is also uniformly a bad idea, since that macro also replaces many functions it knows about with faster ones.

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