compilerhelp wantedperformance
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Descrizione
I was experimenting with alternatives to https://github.com/FluxML/Optimisers.jl/pull/57 when I encountered the following weird issue.
Look at the number of allocations when computing the gradient of loss1
function loss1(m)
ls = 0f0
for l in Functors.fleaves(m)
if l isa AbstractArray{<:Number}
ls += sum(l)
end
end
return ls
end
function loss2(m)
sum(sum(l) for l in Functors.fleaves(m) if l isa AbstractArray{<:Number})
end
function loss3(m)
sum([sum(l) for l in Functors.fleaves(m) if l isa AbstractArray{<:Number}])
end
function perf()
m = Chain(Dense(128 => 128, relu), BatchNorm(3), Dense(128 => 10))
@btime gradient(loss1, $m)[1]
@btime gradient(loss2, $m)[1]
@btime gradient(loss3, $m)[1]
println()
end
perf(); #1st call
perf(); #2nd call
perf(); #3rd call
# OUTPUT
154.795 ms (1022652 allocations: 39.16 MiB)
1.734 ms (7605 allocations: 352.62 KiB)
1.314 ms (5948 allocations: 288.08 KiB)
258.556 ms (1658450 allocations: 63.37 MiB)
1.735 ms (7605 allocations: 352.62 KiB)
1.316 ms (5948 allocations: 288.08 KiB)
336.418 ms (2154374 allocations: 82.29 MiB)
1.739 ms (7605 allocations: 352.62 KiB)
1.319 ms (5948 allocations: 288.08 KiB)
What's going on?