I still get the same result on Version 0.6.0-dev.57.
On Saturday, 6 August 2016 19:43:49 UTC+1, Kristoffer Carlsson wrote:
>
> The above was a known bug that has now been fixed and is not related to
> the actual package.
>
> On Saturday, August 6, 2016 at 6:02:29 PM UTC+2, Andrei Zh wrote:
>>
>> Just tried it on my Ubuntu 16.04. The last thing I could see was julia
>> process eating all 16Gb or RAM in ~1 second and hanging on my laptop so
>> that I had to do hard reboot. So this package seems to be a good tool for
>> testing stability of Julia 0.5 release candidates :)
>>
>> On Thursday, August 4, 2016 at 11:40:24 PM UTC+3, Christoph Ortner wrote:
>>>
>>> On Version 0.5.0-rc1+0
>>>
>>> using ReverseDiffSource; rdiff(:(x^3), x=2.0)
>>> ERROR: error in type inference due to #265
>>> in error(::String) at ./error.jl:21
>>> in typed_vcat(::Type{Any}, ::Array{ReverseDiffSource.ExNode,1}, ::Array
>>> {Any,1}) at ./abstractarray.jl:894
>>> in vcat(::Array{ReverseDiffSource.ExNode,1}, ::Array{Any,1}) at ./array
>>> .jl:653
>>> in prune!(::ReverseDiffSource.ExGraph, ::Array{ReverseDiffSource.ExNode
>>> ,1}) at /Users/ortner/.julia/v0.5/ReverseDiffSource/src/graph.jl:268
>>> in #rdiff#126(::Void, ::Int64, ::Module, ::Bool, ::Bool,
>>> ::Array{Symbol,1}, ::Array{Any,1}, ::Function, ::Expr) at
>>> /Users/ortner/.julia/v0.5/ReverseDiffSource/src/rdiff.jl:100
>>> in (::ReverseDiffSource.#kw##rdiff)(::Array{Any,1},
>>> ::ReverseDiffSource.#rdiff, ::Expr) at ./<missing>:0
>>>
>>> I am posting this here in the hope that others have tried to use
>>> ReverseDiffSource on v0.5 and can confirm that they have the same problem,
>>> or whether there is a fix?
>>>
>>>
