docker中遇到的坑

快来打我* 2024-04-17 05:34 61阅读 0赞

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\------------重点分割线，掉坑是我进步的动力，有时候真的情愿不进步也不想掉坑啊啊啊啊-------------------------------------------

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# 问题1，update终止 #

## 1、在安装vim的时候需要先执行 ##

apt-get update

但是在执行update的时候执行到23步之后无法执行下去，可能是由于第一次在执行到23的时候出现断网，然后使用ctrl+C打断了跟新，反正之后就一直断在这一步。

下载一个新的镜像后在新的镜像里面执行成功

docker pull ufoym/deepo:cpu

推测删除后重新下载可以改变这个状态，删除已有镜像

参考：[https://blog.csdn.net/winy\_lm/article/details/77980529][https_blog.csdn.net_winy_lm_article_details_77980529]

[https://blog.csdn.net/jeikerxiao/article/details/78476925][https_blog.csdn.net_jeikerxiao_article_details_78476925]

![20190730105345646.png][]

删除镜像bvlc/caffe的时候报错，提示有子镜像没有删除，所以先删除子镜像caffe-mnist

![20190730105517994.png][]

删除子镜像的被容器使用

![2019073010574551.png][]

查看后发现caffe-mnist有很多容器，一个一个删除太麻烦了，所以就干脆全部一起删除

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L0RpYW5hX1o_size_16_color_FFFFFF_t_70][]

先停止全部容器，然后删除全部容器，查看确认容器删除

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L0RpYW5hX1o_size_16_color_FFFFFF_t_70 1][]

成功删除两个caffe的镜像

然而，重新下载caffe镜像之后，人就update失败

**emmmmm**

**所以，那就，换一个镜像吧～～～**

**所以，那就，直接复制出来改好了再传回去吧~~~~**

## 2、推荐镜像 ##

地址：[https://github.com/ufoym/deepo][https_github.com_ufoym_deepo]

里面提供了一个叫做deepo的镜像，在镜像里面已经安装了包括caffe，caffe2，tensoflow，torch等等深度学习框架。有cpu和gpu版本。

docker pull ufoym/deepo

gpu版本的下载

## 3、推荐教程 ##

地址：[https://zhuanlan.zhihu.com/p/63426143][https_zhuanlan.zhihu.com_p_63426143]

这是一个使用deepo的cpu镜像实现ssh链接，然后通过ssh将容器编辑器链接Pycharm的教程。

在之前掉过一个坑，如果直接使用镜像链接Pycharm的话，可能只能将镜像中的python包导入到Pycharm里面去，但是比如caffe这种需要在环境中编译得到的就没法加载，所以需要将镜像的容器里面的python解释器导入到Pycharm里面，这个时候就需要使用ssh来链接了。

# 4、错误： #

# docker: Error response from daemon: OCI runtime create failed: container\_linux.go:345: starting container process caused "exec: \\"/bash\\": stat /bash: no such file or directory": unknown. #

解决：

可能是下载过程中出现错误，重新执行docker pull ubuntu，在执行docker run -i -t ubuntu /bin/bash就OK了。

解决方法来源：

[https://blog.csdn.net/weixin\_43201726/article/details/82789002][https_blog.csdn.net_weixin_43201726_article_details_82789002]

# 5、make all 过程中错误，关键字"\_\_shfl\_down" #

NVCC src/caffe/3rdparty/reduce.cu
    nvcc warning : The 'compute_20', 'sm_20', and 'sm_21' architectures are deprecated, and may be removed in a future release (Use -Wno-deprecated-gpu-targets to suppress warning).
    nvcc warning : The 'compute_20', 'sm_20', and 'sm_21' architectures are deprecated, and may be removed in a future release (Use -Wno-deprecated-gpu-targets to suppress warning).
    src/caffe/3rdparty/reduce.cu(44): error: identifier "__shfl_down" is undefined
              detected during:
                instantiation of "T CTAReduce<NT, T, Rop>::reduce(int, T, CTAReduce<NT, T, Rop>::Storage &, int, Rop) [with NT=128, T=float, Rop=ctc_helper::add<float, float>]" 
    (76): here
                instantiation of "void reduce_rows<NT,Iop,Rop,T>(Iop, Rop, const T *, T *, int, int) [with NT=128, Iop=ctc_helper::negate<float, float>, Rop=ctc_helper::add<float, float>, T=float]" 
    (124): here
                instantiation of "void ReduceHelper::impl(Iof, Rof, const T *, T *, int, int, __nv_bool, cudaStream_t) [with T=float, Iof=ctc_helper::negate<float, float>, Rof=ctc_helper::add<float, float>]" 
    (139): here
                instantiation of "ctcStatus_t reduce(Iof, Rof, const T *, T *, int, int, __nv_bool, cudaStream_t) [with T=float, Iof=ctc_helper::negate<float, float>, Rof=ctc_helper::add<float, float>]" 
    (149): here
    
    src/caffe/3rdparty/reduce.cu(44): error: identifier "__shfl_down" is undefined
              detected during:
                instantiation of "T CTAReduce<NT, T, Rop>::reduce(int, T, CTAReduce<NT, T, Rop>::Storage &, int, Rop) [with NT=128, T=float, Rop=ctc_helper::maximum<float, float>]" 
    (76): here
                instantiation of "void reduce_rows<NT,Iop,Rop,T>(Iop, Rop, const T *, T *, int, int) [with NT=128, Iop=ctc_helper::identity<float, float>, Rop=ctc_helper::maximum<float, float>, T=float]" 
    (124): here
                instantiation of "void ReduceHelper::impl(Iof, Rof, const T *, T *, int, int, __nv_bool, cudaStream_t) [with T=float, Iof=ctc_helper::identity<float, float>, Rof=ctc_helper::maximum<float, float>]" 
    (139): here
                instantiation of "ctcStatus_t reduce(Iof, Rof, const T *, T *, int, int, __nv_bool, cudaStream_t) [with T=float, Iof=ctc_helper::identity<float, float>, Rof=ctc_helper::maximum<float, float>]" 
    (157): here
    
    2 errors detected in the compilation of "/tmp/tmpxft_00000e20_00000000-14_reduce.compute_20.cpp1.ii".
    Makefile:594: recipe for target '.build_release/cuda/src/caffe/3rdparty/reduce.o' failed
    make: *** [.build_release/cuda/src/caffe/3rdparty/reduce.o] Error 1ce.o' failí

解决方法参考[https://github.com/xmfbit/warpctc-caffe/issues/1][https_github.com_xmfbit_warpctc-caffe_issues_1]

修改如下，上面被\#注释的是原来的，下面没有注释的是新的，直接删除了sm\_20和sm\_21两行

#CUDA_ARCH := -gencode arch=compute_20,code=sm_20 \
    #		-gencode arch=compute_20,code=sm_21 \
    #		-gencode arch=compute_30,code=sm_30 \
    #		-gencode arch=compute_35,code=sm_35 \
    #		-gencode arch=compute_50,code=sm_50 \
    #		-gencode arch=compute_50,code=compute_50
    
    CUDA_ARCH := -gencode arch=compute_30,code=sm_30 \
    		-gencode arch=compute_35,code=sm_35 \
    		-gencode arch=compute_50,code=sm_50 \
    		-gencode arch=compute_50,code=compute_50Z×ÓU?¥

[https_blog.csdn.net_winy_lm_article_details_77980529]: https://blog.csdn.net/winy_lm/article/details/77980529
[https_blog.csdn.net_jeikerxiao_article_details_78476925]: https://blog.csdn.net/jeikerxiao/article/details/78476925
[20190730105345646.png]: https://image.dandelioncloud.cn/pgy_files/images/2024/04/11/85c1972f52544fbd911cd8b7701d9e16.png
[20190730105517994.png]: https://image.dandelioncloud.cn/pgy_files/images/2024/04/11/1d3d11f7cdb0461699ba3667104e51d3.png
[2019073010574551.png]: https://image.dandelioncloud.cn/pgy_files/images/2024/04/11/df5fe9818cf14e52a82a7aa3b1bd64b6.png
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L0RpYW5hX1o_size_16_color_FFFFFF_t_70]: https://image.dandelioncloud.cn/pgy_files/images/2024/04/11/73234b5e5ba04f52af850f1bb598ec13.png
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L0RpYW5hX1o_size_16_color_FFFFFF_t_70 1]: https://image.dandelioncloud.cn/pgy_files/images/2024/04/11/8d07cf5dd8974f6688f4b66db6f2d013.png
[https_github.com_ufoym_deepo]: https://github.com/ufoym/deepo
[https_zhuanlan.zhihu.com_p_63426143]: https://zhuanlan.zhihu.com/p/63426143
[https_blog.csdn.net_weixin_43201726_article_details_82789002]: https://blog.csdn.net/weixin_43201726/article/details/82789002
[https_github.com_xmfbit_warpctc-caffe_issues_1]: https://github.com/xmfbit/warpctc-caffe/issues/1