sudo nvidia-docker run -it -v /home/hzh:/var/workspace --name caffe nvidia/cuda:9.0-cudnn7-devel-ubuntu16.04 /bin/bash 1. 2. 3. 2.配置cuda echo 'add for cuda' >> ~/.bashrc echo 'export PATH="/usr/local/cuda-9.0/bin:$PATH"' >> ~/.bashrc echo 'export LD_LIBRARY_PATH="/...
Description Add a few arguments CUDA_VERSION, CUDNN_VERSION, OS, GIT_COMMIT, GIT_BRANCH and ONNXRUNTIME_VERSION to the Dockerfile.cuda to allow for more flexibility in the build process. Update RE...
| 22.04 | NVIDIA GeForce RTX 3060 | 10.6.0.26 | CUDA 11.3.r11.3 | cuDNN 8.8.0 | :heavy_check_mark: | > [!note] > > According to your hardware, you must choose the appropriate version of CUDA | GPU Hardware Architecture | Relevant GPUs | Minimum CUDA Version | |:---:|:---:...
ENV CUDNN_VERSION=7.4.1.5 1. 2. 通过设定这两行,来指定ubuntu、cuda、cudnn版本。 FROM跟着基础镜像名,通过英伟达的镜像可以指定cuda9.0,ubuntu16.04。对于cudnn,英伟达的9.0-cudnn7-devel-ubuntu16.04镜像cudnn版本是7.0,如果想用别的版本cudnn,就用这个例子的方法即可。 ENV CUDNN_VERSION=7.4.1.5就是设定...
ARGGOLANG_VERSION=1.22.1ARGCMAKE_VERSION=3.22.1#此CUDA_VERSION与docs/gpu.md中指定的对应ARGCUDA_VERSION=11.3.1ARGROCM_VERSION=6.0.2# 复制运行生成脚本所需的最小上下文FROMscratch AS llm-codeCOPY.git .gitCOPY.gitmodules .gitmodulesCOPYllm llmFROM--platform=linux/amd64 nvidia/cuda:$CUDA_VERSION...
version="${CUDNN_VERSION}" RUN apt-get update && apt-get install -y\ libcudnn7=$CUDNN_VERSION-1+cuda9.0 && \ apt-mark hold libcudnn7 && \ rm -rf /var/lib/apt/lists/* RUN apt-get update \ && apt-get install -y tar git curl nano wget dialog net-tools build-essential \ ...
cat /proc/version cd /usr/local/ ls -ln Ubuntu 18.06 Cuda 11.6 在docker hub 上寻找...
# See https://pytorch.org/ for other options if you use a different version of CUDA RUN pip install torch==1.8.0+cu111 torchvision==0.9.0+cu111 torchaudio==0.8.0 -f https://download.pytorch.org/whl/torch_stable.html WORKDIR /root ...
bump: CUDA Version (#1769) 12345678910111213141516171819202122232425262728293031323334353637383940414243444546 FROM nvidia/cuda:12.2.0-base-ubuntu22.04 ENV DEBIAN_FRONTEND=noninteractive ENV LANG=C.UTF-8 ENV PYTHONUNBUFFERED=1 ENV PYTHONDONTWRITEBYTECODE=1 RUN apt-get update && apt-get install -y -...
poetry install --no-interaction -vv# Provide a known path for the virtual environment by creating a symlinkRUN ln -s $(poetry env info --path) /root/cuda_manager_env# Clean up project files. You can add them with a Docker mount later.RUN rm pyproject.toml poetry.lock...