I am building a Docker image, for deep learning: cuda:11.2.0-cudnn8-devel-ubuntu20.04 PYTHON_VERSION=3.7.9 For this task I need 3 dependencies to install, but I can’t find the right version. The error I get, when building the Docker image: E: Version ‘18.104.22.168-1+cuda11.2’ for ‘libnvinfer8’ was not found E: Version ‘22.214.171.124-1+cuda11.2’ for ‘libnvinfer-dev’ was not found E: Version ‘126.96.36.199-1+cuda11.2’ ..
I am currently trying to run an old pytorch code that only support pytorch version 1.4 and cuda version 10.1 My goto solution is to use pytorch/pytorch:1.4-cuda10.1-cudnn7-devel docker image that has the right requirements for my project. But when I run a python interpreter and start using the GPU with pytorch, the process hangs for ..
I’m trying to write a usable Dockerfile for linux GPU prediction with python (I’m new in docker). Config: os (Ubuntu or other linux distribution) cuda (9-10) (I have gtx 1080 ti) python 3.6 tensorflow-gpu==1.9 I tried to use nvidia/cuda images from docker hub like: 9.2-cudnn7-devel-ubuntu18.04 It runs, with –gpus=all parameter, but the python code doesn’t ..
I am trying to run my model training on GPU server but i am getting below error saying libcusolver.so.11 is not present. Error: tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library ‘libcusolver.so.11’; dlerror: libcusolver.so.11: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /azureml-envs/azureml_0223502b9e9fa00eac9eae53b2b1cdcd/lib:/usr/local/nvidia/lib:/usr/local/nvidia/lib64:/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64 Looking into the various resolution posted on the below link we ..
I have installed Ubuntu 20.04 on WSL2 on a Windows 10 (Dev Channel, Build 21390) In order to work with GPU-optimized containerized images for a Machine Learning project, I followed this guide . As stated in the guide: "NVIDIA Container Toolkit does not yet support Docker Desktop WSL 2 backend. Note: For this release, install ..
I am trying to create an environment for using ZED SDK in a Docker image with ROS. For that, I need to install its CUDA dependency, which as far as I know it is CUDA Toolkit 11.3, and ROS Melodic Morenia. I have created a DockerFile and I tried to install CUDA from a ROS ..
I am trying to use the base images provided by NVIDIA that let us use their GPUs via Docker containers. Because I am using docker, there is no need for me to have CUDA Toolkit or CuDNN on my system. All I need to have is the right driver – which I have. I can ..
So my workflow is gonna be a bit wonky, but I’m not permitted to use Docker, so I have Singularity instead. I’m running some code that is giving me this error: RuntimeError: nvrtc: error: failed to open libnvrtc-builtins.so.11.1. Make sure that libnvrtc-builtins.so.11.1 is installed correctly. nvrtc compilation failed: If more details are needed, I can ..
I am trying to use the docker image with new drivers >460 for CUDA 11 but my host machine has cuda-10. According to the image below (https://github.com/NVIDIA/nvidia-docker) docker uses the drivers present in the host hence I am getting error as kernel mismatch required 450+ kernel version 418. I have installed the drivers on my ..
I am using base container from https://gitlab.com/nvidia/container-images/cuda/blob/master/doc/supported-tags.md My definition file starts with Bootstrap: docker From: nvidia/cuda:10.0-cudnn7-devel-ubuntu18.04 My Host OS has CUDA version 11.0. I am using the following commands to build my container singularity build –sandbox mycontainer/ new.def singularity shell –nv –writable mycontainer/ The –nv flag leads to using drivers from the host OS(cuda 11.0), ..