Le jeudi 21 avril 2016 à 13:24 -0700, Andrew a écrit :
> I don't get it, but it doesn't like something about concatenating the
> number and the array. If you convert the 1 to an array first, it
> works. I thought it was because 1 is an integer and you're joining it
> with an array of float 0's, but using 1. doesn't work either.
>
> function version1(N)
> b = [[1]; zeros(N-1)]
> println(typeof(b))
> for k = 1:N
> for j = 1:N
> b[j] += k
> end
> end
> end
>
> This has no type issues.
This looks like
https://github.com/JuliaLang/julia/issues/13665
Regards
> > Thanks. I figured it was something along these lines. I'd forgotten
> > about the "@code_warntype" macro
> >
> > > It looks like the type inference is failing in version1. If you
> > > do "@code_warntype version1(1000)", it shows that it is inferring
> > > the type of b as Any.
> > >
> > > > In a class I'm teaching the students are using Julia and I
> > > > couldn't for the life of me figure out why one of my students
> > > > codes was allocating a lot of memory.
> > > >
> > > > I finally paired it down the following example that I don't
> > > > understand:
> > > >
> > > > function version1(N)
> > > > b = [1;zeros(N-1)]
> > > > println(typeof(b))
> > > > for k = 1:N
> > > > for j = 1:N
> > > > b[j] += k
> > > > end
> > > > end
> > > > end
> > > >
> > > >
> > > > function version2(N)
> > > > b = zeros(N)
> > > > b[1] = 1
> > > > println(typeof(b))
> > > > for k = 1:N
> > > > for j = 1:N
> > > > b[j] += k
> > > > end
> > > > end
> > > > end
> > > >
> > > > N = 1000
> > > > println("compiling..")
> > > > @time version1(N)
> > > > version2(N)
> > > > println()
> > > > println()
> > > >
> > > > println("Version 1")
> > > > @time version1(N)
> > > > println()
> > > >
> > > > println("Version 2")
> > > > @time version2(N)
> > > >
> > > > The output of this (without the compiling output) in v0.4.5 is:
> > > >
> > > > Version 1
> > > > Array{Float64,1}
> > > > 0.092473 seconds (3.47 M allocations: 52.920 MB, 3.24% gc
> > > > time)
> > > >
> > > > Version 2
> > > > Array{Float64,1}
> > > > 0.001195 seconds (27 allocations: 8.828 KB)
> > > >
> > > > Both version produce the same type for Array b, but in version1
> > > > every time through the loop allocation happens and in the
> > > > version2 the only allocation is of the initial array.
> > > >
> > > > I've not run into this one before (because I would never do
> > > > version1), but as all of us that teach know students will
> > > > always surprise you with their approaches.
> > > >
> > > > Any help understanding what's going on would be appreciated.
> > > >
