对象是一个定值

此时三种方法的作用实际上是相同的。

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import copy

a = "亚丝娜"
b = a
c = copy.copy(a)
d = copy.deepcopy(a)

print("源:id(a)->>>", id(a))
print("赋值:id(b)->>>", id(b))
print("浅拷贝:id(c)->>>", id(c))
print("深拷贝:id(d)->>>", id(d))
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符号变量 syms

在MATLAB中创建或定义一个函数需要用到符号变量。一般情况下,想要绘制函数图像时,往往使用x=[a:0.01:b]的方式先创建一个x的离散定义域,然后再用y=func(x)的方式定义函数本身,最后使用plot(x,y)的方式绘制图像。

然而,当涉及到函数极值、求导、方程求解、连续图像绘制等问题时,这种方法就不够用了。

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Pytorch Release Version Composition

The repository cloned from GitHub pytorch/pytorch is different from the package we download using pip install or conda install. In fact, the former contains many C/C++ based files, which consist of the basic of Pytorch, while the latter is more concise and contains compiled libraries and dll files instead.

Here, let’s discuss the release version, or the installed package at first. The package has a lot of components, Here I only pick out some most important parts to do explanation.

image-20191128191350467

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Overview

Video classification, or in our case, more specifically, action recognition, are studied for a long time. There are many traditional as well as deep learning based method developed to address this problem, and the latest action recognition result trained on a large dataset Kinetics can even reach 98% accuracy. Considering the fact that the action we need to classify is not too much, giving enough data and using the pre-trained model on Kinetics, the result can be quite promising.

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One Line Summary

NOSE: A device which utilize order sensing component and machine learning to detect which kind of cooking method and which kind of foods, oils are used when you are cooking. It can be used to periodically reports to users about their cooking habits.

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Aims

  1. Build a project to visualize the workflow of Tomasulo’s algorithm.
  2. The project should contain at least these parts: Cycle graph, Register info, Pipeline, Data info, Code info and statistics.
  3. We can add some additional components.
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问题背景

由于近期各大免费图床纷纷加入了防盗链机制(如新浪)并停止对个人博客用的图床链接进行访问授权,博客上的图片出现了大面积的无法显示(如本博客),严重影响了博客的浏览体验。然而现在直接使用文中链接尚还可以将图片下载到本地,但这也并无法得到任何官方保障,所以当务之急是把所有图床照片下载到本地,用hexo原生的图片插入格式进行插入。

而在免费图床渐渐不再可用的现在,当务之急其实已经不是再次更换图床,而是把这些图片抢救到本地,并直接将原图部署到服务器上;或是自己搭建图床。为了节省时间和成本,我这里采用了直接将原图部署到服务器上的操作。

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推荐一下新写的Linux系统一键装机脚本(๑´∀`๑)一行命令获得常用命令行软件、zsh、方便好用的诸多zsh插件(如自动补全、一键解压、目录快速跳转、命令行语法高亮等。详见readme和source code)以及一个配置好的spacevim。当前只支持ubuntu。后面将会支持centos。

你将在任何一个新的Linux系统上一键得到一个稳定可靠的使用体验!当然,脚本高度可定制,以上所有内容都可以简单地增减。有问题或需求欢迎提issue~(注意⚠️在已经使用并配置过的电脑上运行可能会出现zshrc配置重复问题)

GitHub链接

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