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 <module> 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 <module> 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 <module> 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
