[英]Use GPU on python docker image
我正在使用python:3.7.4-slim-buster
docker 圖像,我無法更改它。 我想知道如何在上面使用我的nvidia gpus 。
我通常使用tensorflow/tensorflow:1.14.0-gpu-py3
和一個簡單的--runtime=nvidia
int docker run
命令一切正常,但現在我有這個約束。
我認為這種類型的圖像沒有捷徑,所以我按照本指南https://towardsdatascience.com/how-to-properly-use-the-gpu-within-a-docker-container-4c699c78c6d1構建 Z3254677A7917C6C01FBF55212FZF6它建議:
FROM python:3.7.4-slim-buster
RUN apt-get update && apt-get install -y build-essential
RUN apt-get --purge remove -y nvidia*
ADD ./Downloads/nvidia_installers /tmp/nvidia > Get the install files you used to install CUDA and the NVIDIA drivers on your host
RUN /tmp/nvidia/NVIDIA-Linux-x86_64-331.62.run -s -N --no-kernel-module > Install the driver.
RUN rm -rf /tmp/selfgz7 > For some reason the driver installer left temp files when used during a docker build (i dont have any explanation why) and the CUDA installer will fail if there still there so we delete them.
RUN /tmp/nvidia/cuda-linux64-rel-6.0.37-18176142.run -noprompt > CUDA driver installer.
RUN /tmp/nvidia/cuda-samples-linux-6.0.37-18176142.run -noprompt -cudaprefix=/usr/local/cuda-6.0 > CUDA samples comment if you dont want them.
RUN export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/cuda/lib64 > Add CUDA library into your PATH
RUN touch /etc/ld.so.conf.d/cuda.conf > Update the ld.so.conf.d directory
RUN rm -rf /temp/* > Delete installer files.
但它引發了一個錯誤:
ADD failed: stat /var/lib/docker/tmp/docker-builder080208872/Downloads/nvidia_installers: no such file or directory
我可以更改什么以輕松讓 docker 圖像看到我的 GPU?
TensorFlow 映像拆分為幾個“部分”Dockerfile。 其中之一包含 TensorFlow 需要在 GPU 上運行的所有依賴項。 使用它您可以輕松創建自定義圖像,您只需將默認 python 更改為您需要的任何版本。 在我看來,這比將 NVIDIA 的東西帶入 Debian 映像(CUDA 和/或 cuDNN 未正式支持 AFAIK)要容易得多。
這是 Dockerfile:
# TensorFlow image base written by TensorFlow authors.
# Source: https://github.com/tensorflow/tensorflow/blob/v2.3.0/tensorflow/tools/dockerfiles/partials/ubuntu/nvidia.partial.Dockerfile
# -------------------------------------------------------------------------
ARG ARCH=
ARG CUDA=10.1
FROM nvidia/cuda${ARCH:+-$ARCH}:${CUDA}-base-ubuntu${UBUNTU_VERSION} as base
# ARCH and CUDA are specified again because the FROM directive resets ARGs
# (but their default value is retained if set previously)
ARG ARCH
ARG CUDA
ARG CUDNN=7.6.4.38-1
ARG CUDNN_MAJOR_VERSION=7
ARG LIB_DIR_PREFIX=x86_64
ARG LIBNVINFER=6.0.1-1
ARG LIBNVINFER_MAJOR_VERSION=6
# Needed for string substitution
SHELL ["/bin/bash", "-c"]
# Pick up some TF dependencies
RUN apt-get update && apt-get install -y --no-install-recommends \
build-essential \
cuda-command-line-tools-${CUDA/./-} \
# There appears to be a regression in libcublas10=10.2.2.89-1 which
# prevents cublas from initializing in TF. See
# https://github.com/tensorflow/tensorflow/issues/9489#issuecomment-562394257
libcublas10=10.2.1.243-1 \
cuda-nvrtc-${CUDA/./-} \
cuda-cufft-${CUDA/./-} \
cuda-curand-${CUDA/./-} \
cuda-cusolver-${CUDA/./-} \
cuda-cusparse-${CUDA/./-} \
curl \
libcudnn7=${CUDNN}+cuda${CUDA} \
libfreetype6-dev \
libhdf5-serial-dev \
libzmq3-dev \
pkg-config \
software-properties-common \
unzip
# Install TensorRT if not building for PowerPC
RUN [[ "${ARCH}" = "ppc64le" ]] || { apt-get update && \
apt-get install -y --no-install-recommends libnvinfer${LIBNVINFER_MAJOR_VERSION}=${LIBNVINFER}+cuda${CUDA} \
libnvinfer-plugin${LIBNVINFER_MAJOR_VERSION}=${LIBNVINFER}+cuda${CUDA} \
&& apt-get clean \
&& rm -rf /var/lib/apt/lists/*; }
# For CUDA profiling, TensorFlow requires CUPTI.
ENV LD_LIBRARY_PATH /usr/local/cuda/extras/CUPTI/lib64:/usr/local/cuda/lib64:$LD_LIBRARY_PATH
# Link the libcuda stub to the location where tensorflow is searching for it and reconfigure
# dynamic linker run-time bindings
RUN ln -s /usr/local/cuda/lib64/stubs/libcuda.so /usr/local/cuda/lib64/stubs/libcuda.so.1 \
&& echo "/usr/local/cuda/lib64/stubs" > /etc/ld.so.conf.d/z-cuda-stubs.conf \
&& ldconfig
# -------------------------------------------------------------------------
#
# Custom part
FROM base
ARG PYTHON_VERSION=3.7
RUN apt-get update && apt-get install -y --no-install-recommends --no-install-suggests \
python${PYTHON_VERSION} \
python3-pip \
python${PYTHON_VERSION}-dev \
# Change default python
&& cd /usr/bin \
&& ln -sf python${PYTHON_VERSION} python3 \
&& ln -sf python${PYTHON_VERSION}m python3m \
&& ln -sf python${PYTHON_VERSION}-config python3-config \
&& ln -sf python${PYTHON_VERSION}m-config python3m-config \
&& ln -sf python3 /usr/bin/python \
# Update pip and add common packages
&& python -m pip install --upgrade pip \
&& python -m pip install --upgrade \
setuptools \
wheel \
six \
# Cleanup
&& apt-get clean \
&& rm -rf $HOME/.cache/pip
您可以從這里獲取:將 python 版本更改為您需要的版本(在 Ubuntu 存儲庫中可用),添加包、代碼等。
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