{"action":"created","issue":{"url":"https://api.github.com/repos/fchollet/keras/issues/4830","repository_url":"https://api.github.com/repos/fchollet/keras","labels_url":"https://api.github.com/repos/fchollet/keras/issues/4830/labels{/name}","comments_url":"https://api.github.com/repos/fchollet/keras/issues/4830/comments","events_url":"https://api.github.com/repos/fchollet/keras/issues/4830/events","html_url":"https://github.com/fchollet/keras/issues/4830","id":197487724,"number":4830,"title":"Issue when using TensorFlow backend with GPU.","user":{"login":"sixsamuraisoldier","id":13212675,"avatar_url":"https://avatars.githubusercontent.com/u/13212675?v=3","gravatar_id":"","url":"https://api.github.com/users/sixsamuraisoldier","html_url":"https://github.com/sixsamuraisoldier","followers_url":"https://api.github.com/users/sixsamuraisoldier/followers","following_url":"https://api.github.com/users/sixsamuraisoldier/following{/other_user}","gists_url":"https://api.github.com/users/sixsamuraisoldier/gists{/gist_id}","starred_url":"https://api.github.com/users/sixsamuraisoldier/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/sixsamuraisoldier/subscriptions","organizations_url":"https://api.github.com/users/sixsamuraisoldier/orgs","repos_url":"https://api.github.com/users/sixsamuraisoldier/repos","events_url":"https://api.github.com/users/sixsamuraisoldier/events{/privacy}","received_events_url":"https://api.github.com/users/sixsamuraisoldier/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":1,"created_at":"2016-12-25T05:08:55Z","updated_at":"2016-12-25T05:16:14Z","closed_at":null,"body":"Hey there, I am having a problem when using the TensorFlow backend with my GPU.\r\nIt starts to train, but my GPU utilization from nvidia-smi shows that there is almost no utilization yet nvcc-version still gives the correct response.\r\nAnd I've also installed nvidia-modprobe\r\n\r\nOutput of nvidia-smi:\r\nSat Dec 24 21:08:00 2016       \r\n+-----------------------------------------------------------------------------+\r\n| NVIDIA-SMI 375.20                 Driver Version: 375.20                    |\r\n|-------------------------------+----------------------+----------------------+\r\n| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |\r\n| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |\r\n|===============================+======================+======================|\r\n|   0  TITAN X (Pascal)    On   | 0000:03:00.0     Off |                  N/A |\r\n| 23%   33C    P8    10W / 250W |    160MiB / 12221MiB |      0%      Default |\r\n+-------------------------------+----------------------+----------------------+\r\n|   1  TITAN X (Pascal)    On   | 0000:04:00.0      On |                  N/A |\r\n| 23%   41C    P8    11W / 250W |    968MiB / 12218MiB |      3%      Default |\r\n+-------------------------------+----------------------+----------------------+\r\n                                                                               \r\n+-----------------------------------------------------------------------------+\r\n| Processes:                                                       GPU Memory |\r\n|  GPU       PID  Type  Process name                               Usage      |\r\n|=============================================================================|\r\n|    0       991    C   /usr/bin/python                                149MiB |\r\n|    1      1421    G   /usr/bin/X                                     580MiB |\r\n|    1      2336    G   compiz                                         152MiB |\r\n|    1      2746    G   /opt/g                                         189MiB |\r\n|    1     25069    G   ...s-passed-by-fd --v8-snapshot-passed-by-fd    34MiB |\r\n+-----------------------------------------------------------------------------\r\n\r\nOutput of nvcc --version:\r\nnvcc: NVIDIA (R) Cuda compiler driver\r\nCopyright (c) 2005-2016 NVIDIA Corporation\r\nBuilt on Wed_May__4_21:01:56_CDT_2016\r\nCuda compilation tools, release 8.0, V8.0.26\r\n\r\n\r\nWhen I run the keras model, I get this as an output:\r\nI tensorflow/stream_executor/dso_loader.cc:128] successfully opened CUDA library libcublas.so locally\r\nI tensorflow/stream_executor/dso_loader.cc:128] successfully opened CUDA library libcudnn.so locally\r\nI tensorflow/stream_executor/dso_loader.cc:128] successfully opened CUDA library libcufft.so locally\r\nI tensorflow/stream_executor/dso_loader.cc:128] successfully opened CUDA library libcuda.so.1 locally\r\nI tensorflow/stream_executor/dso_loader.cc:128] successfully opened CUDA library libcurand.so locally\r\nCouldn't import dot_parser, loading of dot files will not be possible.\r\nX_train shape: (50000, 32, 32, 3)\r\n50000 train samples\r\n10000 test samples\r\nUsing real-time data augmentation.\r\nEpoch 1/200\r\nE tensorflow/stream_executor/cuda/cuda_driver.cc:509] failed call to cuInit: CUDA_ERROR_UNKNOWN\r\nI tensorflow/stream_executor/cuda/cuda_diagnostics.cc:158] retrieving CUDA diagnostic information for host: Tesseract\r\nI tensorflow/stream_executor/cuda/cuda_diagnostics.cc:165] hostname: Tesseract\r\nI tensorflow/stream_executor/cuda/cuda_diagnostics.cc:189] libcuda reported version is: 375.20.0\r\nI tensorflow/stream_executor/cuda/cuda_diagnostics.cc:363] driver version file contents: \"\"\"NVRM version: NVIDIA UNIX x86_64 Kernel Module  375.20  Tue Nov 15 16:49:10 PST 2016\r\nGCC version:  gcc version 4.8.5 (Ubuntu 4.8.5-2ubuntu1~14.04.1) \r\n\"\"\"\r\nI tensorflow/stream_executor/cuda/cuda_diagnostics.cc:193] kernel reported version is: 375.20.0\r\nI tensorflow/stream_executor/cuda/cuda_diagnostics.cc:300] kernel version seems to match DSO: 375.20.0\r\n\r\nThanks in advance, any help would be much appreciated!\r\n"},"comment":{"url":"https://api.github.com/repos/fchollet/keras/issues/comments/269110615","html_url":"https://github.com/fchollet/keras/issues/4830#issuecomment-269110615","issue_url":"https://api.github.com/repos/fchollet/keras/issues/4830","id":269110615,"user":{"login":"patyork","id":1304633,"avatar_url":"https://avatars.githubusercontent.com/u/1304633?v=3","gravatar_id":"","url":"https://api.github.com/users/patyork","html_url":"https://github.com/patyork","followers_url":"https://api.github.com/users/patyork/followers","following_url":"https://api.github.com/users/patyork/following{/other_user}","gists_url":"https://api.github.com/users/patyork/gists{/gist_id}","starred_url":"https://api.github.com/users/patyork/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/patyork/subscriptions","organizations_url":"https://api.github.com/users/patyork/orgs","repos_url":"https://api.github.com/users/patyork/repos","events_url":"https://api.github.com/users/patyork/events{/privacy}","received_events_url":"https://api.github.com/users/patyork/received_events","type":"User","site_admin":false},"created_at":"2016-12-25T05:16:14Z","updated_at":"2016-12-25T05:16:14Z","body":"This is not a Keras issue. But,\r\n\r\nTry to run `sudo apt-get install nvidia-modprobe` again. Apparently that fixes your issues, according to [google](https://github.com/tensorflow/tensorflow/issues/394)."}}
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