warnings in running examples/optimizers.jl #51
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Can you indicate the language, package, and library versions?
versioninfo() and Pkg.status() in Julia and the versions for cuda and cudnn.
…On Thu, Dec 15, 2016, 15:00 ngphuoc ***@***.***> wrote:
I tried to run optimizers.jl and got a lot of the following warning:
% julia optimizers.jl
in #conv4x#70(::Ptr{Void}, ::Float32, ::Float32, ::Int64, ::Ptr{Void}, ::Int64, ::Array{Any,1}, ::Function, ::Knet.KnetArray{Float32,4}, ::Knet.KnetArray{Float32,4}, ::Knet.KnetArray{Float32,4}) at /home/phuoc/.julia/v0.5/Knet/src/cuda44.jl:50
in #conv4x#85(::Array{Any,1}, ::Function, ::AutoGrad.Rec{Knet.KnetArray{Float32,4}}, ::AutoGrad.Rec{Knet.KnetArray{Float32,4}}, ::Knet.KnetArray{Float32,4}) at ./<missing>:0
in #conv4#74(::Array{Any,1}, ::Function, ::Type{AutoGrad.Grad{2}}, ::Knet.KnetArray{Float32,4}, ::Knet.KnetArray{Float32,4}, ::AutoGrad.Rec{Knet.KnetArray{Float32,4}}, ::AutoGrad.Rec{Knet.KnetArray{Float32,4}}) at ./<missing>:0
in conv4(::Type{AutoGrad.Grad{2}}, ::Knet.KnetArray{Float32,4}, ::Knet.KnetArray{Float32,4}, ::AutoGrad.Rec{Knet.KnetArray{Float32,4}}, ::AutoGrad.Rec{Knet.KnetArray{Float32,4}}) at ./<missing>:0
in backward_pass(::AutoGrad.Rec{Array{Any,1}}, ::AutoGrad.Rec{Float32}, ::Array{AutoGrad.Node,1}) at /home/phuoc/.julia/v0.5/AutoGrad/src/core.jl:212
in (::AutoGrad.##gradfun#1#3{Optimizers.#loss,Int64})(::Array{Any,1}, ::Function, ::Array{Any,1}, ::Vararg{Any,N}) at /home/phuoc/.julia/v0.5/AutoGrad/src/core.jl:47
in (::AutoGrad.#gradfun#2)(::Array{Any,1}, ::Vararg{Any,N}) at /home/phuoc/.julia/v0.5/AutoGrad/src/core.jl:47
in #train#4(::Float64, ::Int64, ::Int64, ::Function, ::Array{Any,1}, ::Array{Any,1}, ::Array{Any,1}) at /home/phuoc/.julia/v0.5/Knet/examples/optimizers.jl:68
in (::Optimizers.#kw##train)(::Array{Any,1}, ::Optimizers.#train, ::Array{Any,1}, ::Array{Any,1}, ::Array{Any,1}) at ./<missing>:0
in macro expansion at /home/phuoc/.julia/v0.5/Knet/examples/optimizers.jl:57 [inlined]
in macro expansion at ./util.jl:184 [inlined]
in main(::Array{String,1}) at /home/phuoc/.julia/v0.5/Knet/examples/optimizers.jl:56
in include_from_node1(::String) at ./loading.jl:488
in process_options(::Base.JLOptions) at ./client.jl:262
in _start() at ./client.jl:318WARNING: cudnn.cudnnConvolutionBackwardData error 3
in #conv4x#70(::Ptr{Void}, ::Float32, ::Float32, ::Int64, ::Ptr{Void}, ::Int64, ::Array{Any,1}, ::Function, ::Knet.KnetArray{Float32,4}, ::Knet.KnetArray{Float32,4}, ::Knet.KnetArray{Float32,4}) at /home/phuoc/.julia/v0.5/Knet/src/cuda44.jl:50
in #conv4x#85(::Array{Any,1}, ::Function, ::AutoGrad.Rec{Knet.KnetArray{Float32,4}}, ::AutoGrad.Rec{Knet.KnetArray{Float32,4}}, ::Knet.KnetArray{Float32,4}) at ./<missing>:0
in #conv4#74(::Array{Any,1}, ::Function, ::Type{AutoGrad.Grad{2}}, ::Knet.KnetArray{Float32,4}, ::Knet.KnetArray{Float32,4}, ::AutoGrad.Rec{Knet.KnetArray{Float32,4}}, ::AutoGrad.Rec{Knet.KnetArray{Float32,4}}) at ./<missing>:0
in conv4(::Type{AutoGrad.Grad{2}}, ::Knet.KnetArray{Float32,4}, ::Knet.KnetArray{Float32,4}, ::AutoGrad.Rec{Knet.KnetArray{Float32,4}}, ::AutoGrad.Rec{Knet.KnetArray{Float32,4}}) at ./<missing>:0
in backward_pass(::AutoGrad.Rec{Array{Any,1}}, ::AutoGrad.Rec{Float32}, ::Array{AutoGrad.Node,1}) at /home/phuoc/.julia/v0.5/AutoGrad/src/core.jl:212
in (::AutoGrad.##gradfun#1#3{Optimizers.#loss,Int64})(::Array{Any,1}, ::Function, ::Array{Any,1}, ::Vararg{Any,N}) at /home/phuoc/.julia/v0.5/AutoGrad/src/core.jl:47
in (::AutoGrad.#gradfun#2)(::Array{Any,1}, ::Vararg{Any,N}) at /home/phuoc/.julia/v0.5/AutoGrad/src/core.jl:47
in #train#4(::Float64, ::Int64, ::Int64, ::Function, ::Array{Any,1}, ::Array{Any,1}, ::Array{Any,1}) at /home/phuoc/.julia/v0.5/Knet/examples/optimizers.jl:68
in (::Optimizers.#kw##train)(::Array{Any,1}, ::Optimizers.#train, ::Array{Any,1}, ::Array{Any,1}, ::Array{Any,1}) at ./<missing>:0
in macro expansion at /home/phuoc/.julia/v0.5/Knet/examples/optimizers.jl:57 [inlined]
in macro expansion at ./util.jl:184 [inlined]
in main(::Array{String,1}) at /home/phuoc/.julia/v0.5/Knet/examples/optimizers.jl:56
in include_from_node1(::String) at ./loading.jl:488
in process_options(::Base.JLOptions) at ./client.jl:262
in _start() at ./client.jl:318. 77.394763 seconds (26.57 M allocations: 1.085 GB, 1.71% gc time)
...
It finally ran but the result seems wrong:
(:epoch,0,:trn,(0.091516666f0,2.3076072f0),:tst,(0.086f0,2.3085766f0))
(:epoch,1,:trn,(0.11236667f0,2.3013859f0),:tst,(0.1135f0,2.3013237f0))
(:epoch,2,:trn,(0.11236667f0,2.301366f0),:tst,(0.1135f0,2.3012974f0))
(:epoch,3,:trn,(0.11236667f0,2.301365f0),:tst,(0.1135f0,2.301296f0))
(:epoch,4,:trn,(0.11236667f0,2.301363f0),:tst,(0.1135f0,2.301292f0))
(:epoch,5,:trn,(0.11236667f0,2.301363f0),:tst,(0.1135f0,2.3012917f0))
(:epoch,6,:trn,(0.11236667f0,2.301362f0),:tst,(0.1135f0,2.3012917f0))
(:epoch,7,:trn,(0.11236667f0,2.3013616f0),:tst,(0.1135f0,2.301291f0))
(:epoch,8,:trn,(0.11236667f0,2.301362f0),:tst,(0.1135f0,2.301291f0))
(:epoch,9,:trn,(0.11236667f0,2.3013618f0),:tst,(0.1135f0,2.3012905f0))
(:epoch,10,:trn,(0.11236667f0,2.3013618f0),:tst,(0.1135f0,2.301291f0))
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Sure, here they are: |
Merged
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Ozan pushed a fix. Can you recheck?
…On Thu, Dec 15, 2016, 15:26 ngphuoc ***@***.***> wrote:
Sure, here they are:
julia> versioninfo()
Julia Version 0.5.1-pre+31
Commit 6a1e339 (2016-11-17 17:50 UTC)
Platform Info:
System: Linux (x86_64-linux-gnu)
CPU: Intel(R) Xeon(R) CPU E5-1660 v3 @ 3.00GHz
WORD_SIZE: 64
BLAS: libopenblas (USE64BITINT DYNAMIC_ARCH NO_AFFINITY Haswell)
LAPACK: libopenblas64_
LIBM: libopenlibm
LLVM: libLLVM-3.7.1 (ORCJIT, haswell)
julia> Pkg.status()
27 required packages:
- ArgParse 0.4.0
- AutoGrad 0.0.4
- CUDArt 0.2.3
- Convex 0.4.0
- DataFrames 0.8.5
- Distributions 0.11.1
- FileIO 0.2.0
- GR 0.18.0
- Glob 1.0.2
- HDF5 0.7.0
- ImageMagick 0.1.8
- JLD 0.6.6
- JSON 0.8.0
- Knet 0.8.1
- LegacyStrings 0.1.1
- LinearLeastSquares 0.1.0
- MAT 0.3.1
- MLBase 0.6.0
- MXNet 0.1.0
- Memcache 0.1.0
- Optim 0.7.1
- Plots 0.10.2
- PyPlot 2.2.4
- RDatasets 0.2.0
- SparseVectors 0.4.2
- StatsBase 0.11.1
- StatsFuns 0.3.1
49 additional packages:
- ArrayViews 0.6.4
- BinDeps 0.4.5
- Blosc 0.1.7
- BufferedStreams 0.2.0
- Calculus 0.1.15
- ColorTypes 0.2.12
- ColorVectorSpace 0.1.11
- Colors 0.6.9
- Compat 0.9.5
- Conda 0.4.0
- DataArrays 0.3.10
- DataStructures 0.4.6
- DiffBase 0.0.2
- FixedPointNumbers 0.2.1
- FixedSizeArrays 0.2.5
- Formatting 0.2.0
- ForwardDiff 0.3.3
- GZip 0.2.20
- Graphics 0.1.3
- Hiccup 0.0.3
- Images 0.5.14
- Iterators 0.2.0
- Juno 0.2.5
- LaTeXStrings 0.2.0
- Lazy 0.11.4
- Libz 0.2.0
- LineSearches 0.1.2
- MacroTools 0.3.2
- MathProgBase 0.5.8
- Measures 0.0.3
- Media 0.2.4
- NaNMath 0.2.2
- PDMats 0.5.2
- PlotThemes 0.1.0
- PlotUtils 0.2.0
- PositiveFactorizations 0.0.3
- PyCall 1.7.2
- RData 0.0.4
- RecipesBase 0.1.0
- Reexport 0.0.3
- Rmath 0.1.5
- SHA 0.3.0
- SIUnits 0.1.0
- Showoff 0.0.7
- SortingAlgorithms 0.1.0
- TexExtensions 0.0.3
- TextWrap 0.1.6
- URIParser 0.1.6
- Zlib 0.1.12
% nvcc --version
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2015 NVIDIA Corporation
Built on Tue_Aug_11_14:27:32_CDT_2015
Cuda compilation tools, release 7.5, V7.5.17
% cat /usr/local/cuda/include/cudnn.h | grep CUDNN_MAJOR -A 2#define CUDNN_MAJOR 5#define CUDNN_MINOR 1#define CUDNN_PATCHLEVEL 3
--#define CUDNN_VERSION (CUDNN_MAJOR * 1000 + CUDNN_MINOR * 100 + CUDNN_PATCHLEVEL)
#include "driver_types.h"
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I have checked. It works. Thanks a lot. |
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I tried to run optimizers.jl and got a lot of the following warnings:
It finally ran but the result seems wrong:
The other examples ran correctly without warning.
The text was updated successfully, but these errors were encountered: