Docker部署yolact中编译DCNv2的问题
yolact部署到Docker中，需要单独编译DCNv2
cd external/DCNv2
python setup.py build develop但是这个DCNv2的编译需要依赖GPU，总是编不过。
失败1：使用python:3.6镜像
FROM python:3.6
...
WORKDIR ***/external/DCNv2
RUN python setup.py build develop
...执行后编译报错，通过docker run进入到docker里面依然编译报错：
No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda'
Traceback (most recent call last):
File "setup.py", line 64, in
ext_modules=get_extensions(),
File "setup.py", line 41, in get_extensions
raise NotImplementedError('Cuda is not availabel')
NotImplementedError: Cuda is not availabel 原因分析：python:3.6镜像未安装cuda驱动
失败2：改用pytorch/pytorch:1.2-cuda10.0-cudnn7-runtime镜像
FROM pytorch/pytorch:1.2-cuda10.0-cudnn7-runtime
...
WORKDIR ***/external/DCNv2
RUN python setup.py build develop
...无论是Dockerfile编译，还是docker run进入到docker里面编译，依然报错：
No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda'
Traceback (most recent call last):
File "setup.py", line 64, in
ext_modules=get_extensions(),
File "setup.py", line 41, in get_extensions
raise NotImplementedError('Cuda is not availabel')
NotImplementedError: Cuda is not availabel 原因分析：torch.cuda.is_available() 显示为True，但是from torch.utils.cpp_extension import CUDA_HOME，CUDA_HOME为NULL，看了一下/usr/local目录下确实没有cuda相关的目录。
失败3：改用pytorch/pytorch:1.2-cuda10.0-cudnn7-devel镜像
FROM pytorch/pytorch:1.2-cuda10.0-cudnn7-devel
...
WORKDIR ***/external/DCNv2
RUN python setup.py build develop
...中间出现过一个apt-get update失败的问题：Failed to fetch https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/Packages.gz Hash Sum mismatch
解决方法：
...
# Update source
RUN sed -i s:/archive.ubuntu.com:/mirrors.tuna.tsinghua.edu.cn/ubuntu:g /etc/apt/sources.list
RUN cat /etc/apt/sources.list
RUN apt-get clean
RUN apt-get -y update --fix-missing --allow-unauthenticated
...docker build跑起来，结果编译依然报错（吐血）：
No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda'
Traceback (most recent call last):
File "setup.py", line 64, in
ext_modules=get_extensions(),
File "setup.py", line 41, in get_extensions
raise NotImplementedError('Cuda is not availabel')
NotImplementedError: Cuda is not availabel 但是通过docker run --gpus all -it ... /bin/bash进入到docker里面，居然编译成功了。
running build
running build_ext
running develop
running egg_info
writing DCNv2.egg-info/PKG-INFO
writing dependency_links to DCNv2.egg-info/dependency_links.txt
writing top-level names to DCNv2.egg-info/top_level.txt
reading manifest file 'DCNv2.egg-info/SOURCES.txt'
writing manifest file 'DCNv2.egg-info/SOURCES.txt'
running build_ext
copying build/lib.linux-x86_64-3.6/_ext.cpython-36m-x86_64-linux-gnu.so ->
Creating /opt/conda/lib/python3.6/site-packages/DCNv2.egg-link (link to .)
Adding DCNv2 0.1 to easy-install.pth file
Installed ***/external/DCNv2
Processing dependencies for DCNv2==0.1
Finished processing dependencies for DCNv2==0.1原因分析：通过docker run进入到docker里面编译时，已通过--gpus选项为docker指定了GPU，所以可以使用GPU并编译成功。但在docker build执行Dockerfile时并未为docker指定GPU，所以依然无法使用GPU。
终极方案：不在docker build时通过Dockerfile编译，而是在ENDPOINT中执行编译：
FROM pytorch/pytorch:1.2-cuda10.0-cudnn7-devel
...
ENTRYPOINT ["sh", "run.sh"]在run.sh中编译DCNv2：
cd external/DCNv2
python setup.py build develop
cd ../..
python ***.py