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Cannot require CUDNN in Torch! Please help! #26

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Hidden-dreamz opened this issue Apr 4, 2017 · 5 comments
Open

Cannot require CUDNN in Torch! Please help! #26

Hidden-dreamz opened this issue Apr 4, 2017 · 5 comments

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@Hidden-dreamz
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Hidden-dreamz commented Apr 4, 2017

When i require 'cudnn' i get this error on ubuntu 16.04, nvidia driver 378.13, Cuda 8.0 (full newest release), Cudnn 6 (same problem with 5.1) using torch-cl and installed all cutorch cunn cudnn with laurocks. Torch works with my gpu i just cant get CUDNN to work. Please help! thanks! (and im using 1070 gpu)

/home/josh/torch-cl/install/share/lua/5.1/cudnn/init.lua:98: attempt to call field 'hasFastHalfInstructions' (a nil value)
stack traceback:
/home/josh/torch-cl/install/share/lua/5.1/cudnn/init.lua:98: in function 'fasterHalfMathTypeForCurrentDevice'
/home/josh/torch-cl/install/share/lua/5.1/cudnn/init.lua:112: in function 'configureMath'
/home/josh/torch-cl/install/share/lua/5.1/cudnn/init.lua:131: in main chunk
[C]: in function 'require'
stdin:1: in main chunk
[C]: at 0x00405e90

@hughperkins
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distro-cl is for opencl. cunn, cudnn are the cuda versions. Please use require clnn instead.

@Hidden-dreamz
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i want to use the cudnn version how to go back to using the standard torch distro if everything is linked to the opencl one? thanks for the help

@hughperkins
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You'll wnat to install into two separate folder, one for distro-cl, one for standard torch, eg, you could install distro-cl into ~/torch-cl, and the standard distro into ~/torch

To choose the one you want, simply call activate from the one you want to use, something like:

source ~/torch/bin/torch-activate

@NerminSalem
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Hi
can you help, i m using cpu mode as my laptop doesn't support NIVIDIA and i installed cltorch and clnn and set gpu= -1 but still i m getting libthclnn_searchpath /home/nermin/torch-cl/install/lib/lua/5.1/libTHCLNN.so
terminate called after throwing an instance of 'std::runtime_error'
can u help?

@hughperkins
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Can you check the result of running clinfo please? You need at least one GPU available, visible from clinfo.

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