You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
sysbox run tensorflow/tensorflow:2.9.1-gpu as follows:
docker run --gpus all --mount type=bind,source=/usr/bin/nvidia-smi,target=/usr/bin/nvidia-smi -v /usr/lib/x86_64-linux-gnu:/usr/lib/x86_64-linux-gnu --device=/dev/nvidiactl --device=/dev/nvidia-uvm --device=/dev/nvidia0 --name test10 tensorflow/tensorflow:2.9.1-gpu python -c "import tensorflow as tf; print(tf.config.list_physical_devices('GPU'))"
error message:
E tensorflow/stream_executor/cuda/cuda_driver.cc:271] failed call to cuInit: UNKNOWN ERROR (34)
I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:169] retrieving CUDA diagnostic information for host: aaf4ecde1157
I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:176] hostname: aaf4ecde1157
I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:200] libcuda reported version is: NOT_FOUND: was unable to find libcuda.so DSO loaded into this program
I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:204] kernel reported version is: 525.85.12
The text was updated successfully, but these errors were encountered:
--mount type=tmpfs,destination=/proc/driver/nvidia
--mount type=bind,source=/usr/bin/nvidia-smi,target=/usr/bin/nvidia-smi
--mount type=bind,source=/usr/bin/nvidia-debugdump,target=/usr/bin/nvidia-debugdump
--mount type=bind,source=/usr/bin/nvidia-persistenced,target=/usr/bin/nvidia-persistenced
--mount type=bind,source=/usr/bin/nvidia-cuda-mps-control,target=/usr/bin/nvidia-cuda-mps-control
--mount type=bind,source=/usr/bin/nvidia-cuda-mps-server,target=/usr/bin/nvidia-cuda-mps-server
-v /usr/lib/x86_64-linux-gnu:/usr/lib/x86_64-linux-gnu
--mount type=bind,source=/run/nvidia-persistenced/socket,target=/run/nvidia-persistenced/socket
--device /dev/nvidiactl:/dev/nvidiactl --device /dev/nvidia-uvm:/dev/nvidia-uvm
--device /dev/nvidia-uvm-tools:/dev/nvidia-uvm-tools
--device /dev/nvidia0:/dev/nvidia0
nestybox/k8s-node:v1.20.2
docker run --gpus all --mount type=bind,source=/usr/bin/nvidia-smi,target=/usr/bin/nvidia-smi -v /usr/lib/x86_64-linux-gnu:/usr/lib/x86_64-linux-gnu --device=/dev/nvidiactl --device=/dev/nvidia-uvm --device=/dev/nvidia0 --name test10 tensorflow/tensorflow:2.9.1-gpu python -c "import tensorflow as tf; print(tf.config.list_physical_devices('GPU'))"
error message:
E tensorflow/stream_executor/cuda/cuda_driver.cc:271] failed call to cuInit: UNKNOWN ERROR (34)
I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:169] retrieving CUDA diagnostic information for host: aaf4ecde1157
I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:176] hostname: aaf4ecde1157
I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:200] libcuda reported version is: NOT_FOUND: was unable to find libcuda.so DSO loaded into this program
I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:204] kernel reported version is: 525.85.12
The text was updated successfully, but these errors were encountered: