開發平臺: Ubuntu 16.04 安裝docker-ce, docker, nvidia-docker 1.1, docker-compose

預處理:

製作資料卷 nvidia_driver_384.111

製作映象

mkdir -p /your_path
cd /your_path
## 
git clone https://github.com/NVIDIA/FastPhotoStyle.git
cd FastPhotoStyle

## 製作docker映象, 映象操作耗時長, 耐心等待
docker build -t photo_style:1.0 .

編寫docker-compose.yml

docker-compose.yml檔案

version: "2"
services:    
    photo_style:
        container_name: photo_style
        devices:
            - /dev/nvidia0
            - /dev/nvidia1
            - /dev/nvidiactl
            - /dev/nvidia-uvm
            - /dev/nvidia-uvm-tools
        ports:
         - "22222:22222"         
        image
 
: photo_style:1.0
        volumes:
         - nvidia_driver_384.111:/usr/local/nvidia:ro
         - /your_path/FastPhotoStyle:/FastPhotoStyle
        restart: on-failure
        tty: true
volumes:  
  nvidia_driver_384.111:
    external: true

啟動容器

## 建立容器
docker-compose -f docker-compose.yml up -d

## 啟動容器
 

docker exec -it photo_style /bin/bash

錯誤記錄

cupy.cuda.runtime.CUDARuntimeError: cudaErrorInsufficientDriver: CUDA driver version is insufficient for CUDA runtime version


驅動不支援cuda版本, 換比較低的cuda版本.
不同版本Cuda 對顯示卡驅動要求是不一樣的，如果你的顯示卡驅動版本低於CUDA tookit 要求的版本，程式可能出現計算錯誤或其它未知名的錯誤。

用的是cuda91的版本, 換為cuda90版本.

修改dockerfile檔案

FROM nvidia/cuda:9.0-cudnn7-devel-ubuntu16.04
ENV ANACONDA /opt/anaconda3
ENV CUDA_PATH /usr/local/cuda
ENV PATH ${ANACONDA}/bin:${CUDA_PATH}/bin:$PATH
ENV LD_LIBRARY_PATH ${ANACONDA}/lib:${CUDA_PATH}/bin64:$LD_LIBRARY_PATH
ENV C_INCLUDE_PATH ${CUDA_PATH}/include
RUN apt-get update && apt-get install -y --no-install-recommends \
         wget \	 
         imagemagick \
         libopencv-dev \
         python-opencv \
         build-essential \
         cmake \
         git \
         curl \
         ca-certificates \
         libjpeg-dev \
         libpng-dev \
         axel \
         zip \
         unzip
RUN wget https://repo.continuum.io/archive/Anaconda3-5.0.1-Linux-x86_64.sh -P /tmp
RUN bash /tmp/Anaconda3-5.0.1-Linux-x86_64.sh -b -p $ANACONDA
RUN rm /tmp/Anaconda3-5.0.1-Linux-x86_64.sh -rf
RUN conda install -y pytorch=0.4.1 torchvision cuda90 -c pytorch
RUN conda install -y -c anaconda pip 
RUN conda install -y -c menpo opencv3
RUN pip install scikit-umfpack
RUN pip install cupy-cuda90
RUN pip install pynvrtc

重新制作docker映象

## 製作docker映象, 映象操作耗時長, 耐心等待
docker build -t photo_style:1.1 .

啟動容器

docker exec -it photo_style /bin/bash

執行命令

cd /your_path
./demo_example1.sh

如有疑問, 請留言