What is the best way to do that? Should I use separate conda environments for theano and tensorflow, and create LD_LIBRARY_PATH in each? Does dnn.libary_path in theanorc override LD_LIBRARY_PATH?
On Thursday, May 10, 2018 at 3:09:29 PM UTC-7, nouiz wrote: > > You could have multiple cuda version installed to have TF working. > > Le jeu. 10 mai 2018 16:28, Michael Klachko <[email protected] > <javascript:>> a écrit : > >> After struggling with this error for a day, I decided to upgrade CUDA to >> 9.1 and CuDNN to 7.1. After that I got "your driver might be too old" >> error, which was resolved by updating the driver to 396.24. Also, in the >> process I found out I had older CuDNN files in /usr/lib/x86_64-linux-gnu/ >> directory. Not sure how they got there, perhaps because sometimes I >> installed CuDNN using .deb package, and sometimes by manually copying the >> files. So it's probably not a good idea to mix .deb and .run cuda >> installation methods. >> >> Anyway, now theano works fine now, but unfortunately my Tensorflow is >> broken because it does not support cuda 9.1 yet... Will probably have to >> compile it from source. >> >> >> >> On Thursday, May 10, 2018 at 11:30:38 AM UTC-7, Arnaud Bergeron wrote: >> >>> This is a new one. It is also very weird since gemm doesn't involve >>> cuLinkAddData. This may be an error message from something else. >>> >>> First things first, since you are on cuda 9.0, I would recommend that >>> you update your driver to 384.111 or 390.*. If that doesn't help, then >>> I'll need some help reproducing the problem since I don't get that in any >>> of my environments. >>> >> Le 8 mai 2018 à 18:15, Michael Klachko <[email protected]> a écrit : >>> >>> I have CUDA 9.0 and CuDNN 7.0.5 on my Ubuntu 16.04, and Tensorflow works >>> fine. In order to install theano, I first installed miniconda, then ran >>> "conda >>> install theano pygpu" and it seemed to have installed fine. >>> >>> >>> >>> However, here's what I get: >>> >>> >>> $ python >>> Python 3.6.5 |Anaconda, Inc.| (default, Apr 29 2018, 16:14:56) >>> [GCC 7.2.0] on linux >>> Type "help", "copyright", "credits" or "license" for more information. >>> >>> import theano >>> Using cuDNN version 7005 on context None >>> ERROR (theano.gpuarray): Could not initialize pygpu, support disabled >>> Traceback (most recent call last): >>> File >>> "/home/michael/miniconda2/envs/las/lib/python3.6/site-packages/theano/gpuarray/__init__.py", >>> line 227, in <module> >>> use(config.device) >>> File >>> "/home/michael/miniconda2/envs/las/lib/python3.6/site-packages/theano/gpuarray/__init__.py", >>> line 214, in use >>> init_dev(device, preallocate=preallocate) >>> File >>> "/home/michael/miniconda2/envs/las/lib/python3.6/site-packages/theano/gpuarray/__init__.py", >>> line 159, in init_dev >>> pygpu.blas.gemm(0, tmp, tmp, 0, tmp, overwrite_c=True) >>> File "pygpu/blas.pyx", line 149, in pygpu.blas.gemm >>> File "pygpu/blas.pyx", line 47, in pygpu.blas.pygpu_blas_rgemm >>> pygpu.gpuarray.GpuArrayException: (b'cuLinkAddData: CUDA_ERROR_UNKNOWN: >>> unknown error', 3) >>> >>> >>> >>> Here's the packages I have installed in this environment: >>> >>> >>> $ conda list >>> # packages in environment at /home/michael/miniconda2/envs/las: >>> # >>> # Name Version Build Channel >>> binutils_impl_linux-64 2.28.1 had2808c_3 >>> binutils_linux-64 7.2.0 26 >>> ca-certificates 2018.03.07 0 >>> certifi 2018.4.16 py36_0 >>> gcc_impl_linux-64 7.2.0 habb00fd_3 >>> gcc_linux-64 7.2.0 26 >>> gxx_impl_linux-64 7.2.0 hdf63c60_3 >>> gxx_linux-64 7.2.0 26 >>> intel-openmp 2018.0.0 8 >>> libedit 3.1 heed3624_0 >>> libffi 3.2.1 hd88cf55_4 >>> libgcc-ng 7.2.0 hdf63c60_3 >>> libgfortran-ng 7.2.0 hdf63c60_3 >>> libgpuarray 0.7.5 h14c3975_0 >>> libstdcxx-ng 7.2.0 hdf63c60_3 >>> mako 1.0.7 py36h0727276_0 >>> markupsafe 1.0 py36hd9260cd_1 >>> mkl 2018.0.2 1 >>> mkl-service 1.1.2 py36h17a0993_4 >>> mkl_fft 1.0.1 py36h3010b51_0 >>> mkl_random 1.0.1 py36h629b387_0 >>> ncurses 6.0 h9df7e31_2 >>> nose 1.3.7 py36hcdf7029_2 >>> numpy 1.14.2 py36hdbf6ddf_1 >>> openssl 1.0.2o h20670df_0 >>> pip 10.0.1 py36_0 >>> pygpu 0.7.5 py36h14c3975_0 >>> python 3.6.5 hc3d631a_2 >>> readline 7.0 ha6073c6_4 >>> scipy 1.0.1 py36hfc37229_0 >>> setuptools 39.1.0 py36_0 >>> six 1.11.0 py36h372c433_1 >>> sqlite 3.23.1 he433501_0 >>> theano 1.0.1 py36h6bb024c_0 >>> tk 8.6.7 hc745277_3 >>> wheel 0.31.0 py36_0 >>> xz 5.2.3 h5e939de_4 >>> zlib 1.2.11 ha838bed_2 >>> >>> >>> >>> Here's my .theanorc file: >>> >>> >>> [global] >>> device = cuda0 >>> optimizer_including = cudnn >>> floatX = float32 >>> >>> [dnn] >>> include_path = /usr/local/cuda/include >>> library_path = /usr/local/cuda/lib64 >>> >>> [lib] >>> cnmem = 0.7 >>> >>> [nvcc] >>> fastmath = True >>> >>> [blas] >>> # Only used for device = cpu >>> ldflags = -lopenblas >>> >>> [cuda] >>> root = /usr/local/cuda/bin >>> >>> >>> >>> Nvidia driver: Driver Version: 384.81 >>> >>> -- >>> >>> --- >>> You received this message because you are subscribed to the Google >>> Groups "theano-users" group. >>> >>> To unsubscribe from this group and stop receiving emails from it, send >>> an email to [email protected]. >>> >>> >>> For more options, visit https://groups.google.com/d/optout. >>> >>> -- >> >> --- >> You received this message because you are subscribed to the Google Groups >> "theano-users" group. >> To unsubscribe from this group and stop receiving emails from it, send an >> email to [email protected] <javascript:>. >> For more options, visit https://groups.google.com/d/optout. >> > -- --- You received this message because you are subscribed to the Google Groups "theano-users" group. 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