Google Colab:本地运行时使用 [英] Google Colab : Local Runtime use

问题描述

我目前正在使用google-colab，在入门页面上，我们看到:

I was currently using google-colab and on the getting started pages, we see:

本地运行时支持Colab支持连接到Jupyter运行时在您的本地计算机上.有关更多信息，请参见我们的文档.

因此，当我看到文档时，我使用连接的选项卡将colab笔记本连接到了本地运行时，安装后等.

So, when I saw the documentation I connected my colab notebook to the local runtime, after the installations,etc by using the connected tab.

当我访问内存信息时:

!cat /proc/meminfo

输出如下:

    MemTotal:        3924628 kB
MemFree:          245948 kB
MemAvailable:    1473096 kB
Buffers:          168560 kB
Cached:          1280300 kB
SwapCached:        20736 kB
Active:          2135932 kB
Inactive:         991300 kB
Active(anon):    1397156 kB
Inactive(anon):   560124 kB
Active(file):     738776 kB
Inactive(file):   431176 kB
Unevictable:         528 kB
Mlocked:             528 kB

哪个是我的PC的内存信息，所以可以肯定地从笔记本电脑访问我的PC?那么它与我的本地Jupyter笔记本有什么不同?现在，我无法使用13 Gig的高内存环境，也无法访问GPU.

Which is the memory info for my pc, so certainly the access from the notebook is to my pc? Then how is it any different from my local jupyter-notebook? Now, I can't use the high memory environment of 13 Gigs, nor can I have GPU access.

如果有人可以解释，那就太好了！

Would be great if someone can explain!

推荐答案

将Colab与本地后端一起使用的主要优点来自基于Drive的笔记本存储:Drive注释，ACL和基于链接的成品笔记本轻松共享

The main advantages to using Colab with a local backend stem from Drive-based notebook storage: Drive commenting, ACLs, and easy link-based sharing of the finished notebook.

使用Jupyter时，共享笔记本需要共享文件.而且，从一台不同的计算机访问笔记本电脑需要安装Jupyter而不是加载网站.

When using Jupyter, sharing notebooks requires sharing files. And, accessing your notebooks from a distinct machine requires installing Jupyter rather than loading a website.

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