model train the fit
转:pytorch并行训练时报错 one of the variables needed for gradient computation has been modified by an inplace operation
【PyTorch踩坑】一个排查了一下午的坑 - 知乎 (zhihu.com) ......
The CATALINA_HOME environment variable is not defined correctly
出现原因:在系统变量中,没有找到CATALINA_HOME 这个变量 解决办法:在系统中加上CATALINA_HOME 这个变量。值为Tomcat 的根目录 ......
Hack The Box 闭坑指南---Starting Point---Meow(第0层)
0x00 实验环境 靶场:windows笔记本、kali虚拟机 0x01 实验前提 (1)注册Hack The Box (自行注册) 注册htb:https://www.hackthebox.com/ (2)连接htb靶场环境: 登录htb: https://app.hackthebox.com/m ......
How to print a web page without breaking the table content in JavaScript All In One
How to print a web page without breaking the table content in JavaScript All In One
使用 JavaScript 如何在不破坏表格内容的情况下打印一个网页
......
python tk编程出现: Tcl_AsyncDelete: async handler deleted by the wrong thread
问题现象 我有一个主TK界面, 同时又创建了一个新的独立的TK窗口. 这个新的TK窗口设置为topmost, 用于超时提醒的. 这个窗口虽然是topmost的, 但是可能没有输入焦点. 我想设置一个快捷键, 用于关闭此窗口. 也就是说, 在另外的线程中关闭tk窗口. 采用的方法是在另外线程中调用ro ......
[题解] CF29D Ant on the Tree
CF29D Ant on the Tree 题目知识点:LCA。 题目传送门 题意 给定一棵以 \(1\) 为节点的树,再给定树的所有叶子节点的一个序列。 现在执行一个操作:从 \(1\) 开始遍历每个节点,并返回根,要求每条边经过的次数一定为 \(2\) 。 问是否能够使得访问节点序列中叶子节点的 ......
Model关联模型,一对一,一对多,多对多
一、一对一关系 1、我们在models中创建一个新的模型,叫做StudentInfo 点击查看代码 ``` class StudentInfo(BaseModel): """学生信息附加表""" address = models.CharField(max_length=255,verbose_na ......
打包发布版时报错 Error: The apk for your currently selected variant cannot be signed. Please specify a signing configuration for this variant (release).
当直接运行release版本时,报错 Error: The apk for your currently selected variant cannot be signed. Please specify a signing configuration for this variant (relea ......
《PROMPT2MODEL: Generating Deployable Models from Natural Language Instructions》论文学习
一、Introduction 传统上,从零开始构建一个自然语言处理(NLP)模型是一项重大任务。一个寻求解决新问题的NLP从业者需要定义他们的任务范围,找到或创建目标任务领域的行为数据,选择合适的模型架构,训练模型,通过评估评估其性能,然后将其部署到实际应用中。 Prompt2Model is a ......
Recommendation as Instruction Following: A Large Language Model Empowered Recommendation Approach
原文地址:https://arxiv.org/abs/2305.07001 本文作者将用户偏好、意图等构建为指令,并用这些指令调优一个LLM(3B Flan-T5-XL),该方法对用户友好,用户可以与系统交流获取更准确的推荐。 ## INTRODUCTION LLM是建立在自然语言文本上的,它不能直 ......
微服务启动失败,报错信息:java.lang.RuntimeException: dynamic-datasource Please check the setting of primary
【问题描述】 Caused by: org.springframework.beans.factory.BeanCreationException: Error creating bean with name 'dataSource' defined in class path resource [ ......
Why Kiki's Delivery Service Is The Perfect Coming of Age Story
# Why Kiki's Delivery Service Is The Perfect Coming of Age Story Studio Ghibli is well known for producing timeless classics that have engaging protag ......
CF1850H The Third Letter
[题目链接](https://codeforces.com/problemset/problem/1850/H) # 题解 **知识点:贪心,图论建模。** 考虑对约束 `a b d` 建边 $a \mathop{\to}\limits^d b$ 与 $b \mathop{\to}\limits^{ ......
CF1872B The Corridor or There and Back Again
## 思路 假设第 $0$ 时刻走进有陷阱的房间,那么必须在第 $t_i$ 时刻前返回到这个房间之前,因为出去还需要回来,假设到达这个房间后的第 $k$ 个房间,那么到达需要 $k$ 的时间,回来需要 $k+1$ 的时间,因为陷阱会困住当前在房间里的人,所以我们需要提前回去。 那么如果走到一个有陷阱 ......
Proj CDeepFuzz Paper Reading: SparseProp: Efficient Sparse Backpropagation for Faster Training of Neural Networks
## Abstract 本文:SparseProp Github: https://github.com/IST-DASLab/sparseprop Task: a back-propagation algo for sparse training data, a fast vectorized i ......
Proj CDeepFuzz Paper Reading: Software Testing with Large Language Model: Survey, Landscape, and Vision
## Abstract 本文: Task: Review on the use of LLMs in software testing Method: 1. analyzes 52 relevant studies ## 1. Intro ![](https://img2023.cnblogs.co ......
The Power of Diagnostic Kits: Unleashing the Potential of John Deere Service Advisor EDL v2,Interface
In the rapidly evolving world of automotive diagnostics, the importance of reliable and efficient diagnostic tools cannot be overstated. These tools s ......
论文解读(CST)《Cycle Self-Training for Domain Adaptation》
Note:[ wechat:Y466551 | 可加勿骚扰,付费咨询 ] 论文信息 论文标题:Cycle Self-Training for Domain Adaptation论文作者:Hong Liu, Jianmin Wang, Mingsheng Long论文来源:2021 论文地址:down ......
Proj CDeepFuzz Paper Reading: PELICAN: Exploiting Backdoors of Naturally Trained Deep Learning Models In Binary Code Analysis
## Abstract 背景: 1. 本文研究的不是被恶意植入的后门,而是products of defects in training 2. 攻击模式: injecting some small fixed input pattern(backdoor) to induce misclassifi ......
The 16-th BIT Campus Programming Contest - Onsite Round
链接:[https://codeforces.com/gym/104025](https://codeforces.com/gym/104025) ## A. Gifts in box ```cpp #include "bits/stdc++.h" using namespace std; usin ......
The 2nd Universal Cup. Stage 1- Qingdao
# A. Live Love 最大值就是把所有的$P$放在一起,最小值是尽可能的均分. ```cpp #include using namespace std; #define int long long void solve() { int n , m , d ; cin >> n >> m , ......
Automate the Boring Stuff with Python(读后感)
这里主要就是记录下这本书的主要内容,自己以后想起来的时候可以直接看这个博客 整本书的内容看目录就很清楚了,所以下面就是目录加自己的一点心得体会 ### Python编程基础 基础中的基础,但有个很重要的轮子 `PrettyPrint`:把输出打印的更漂亮 ### 自动化任务 这是重点,一次性肯定记不 ......
# Codeforces Round 887 E Ina of the Mountain(反悔贪心)
~~被这个题折磨了好久,决定写一篇题解~~ 先考虑没有这个$k$的限制的情况,等价于对原来的$a_i$序列的差分数组$b_i$,每次找到两个位置$1\le x 0$的位置进行$-1$的操作,后面对应的$+1$可以放在$b_ic[i]$,那么$c[i]$减去$k$对答案的贡献就是$0$,因为$d[i] ......
The Road Not Taken
"The Road Not Taken" by Robert Frost Two roads diverged in a yellow wood, And sorry I could not travel both And be one traveler, long I stood And look ......
通过提示大语言模型进行个性化推荐LLM-Rec: Personalized Recommendation via Prompting Large Language Models
论文原文地址:https://arxiv.org/abs/2307.15780 本文提出了一种提示LLM并使用其生成的内容增强推荐系统的输入的方法,提高了个性化推荐的效果。 ## LLM-Rec Prompting ![](https://img2023.cnblogs.com/blog/17994 ......
Four in the Morning
BY Wislawa Szymborska The hour from night to day The hour from side to side The hour for those past thirty The hour swept clean to the crowing of cock ......
Proj CDeepFuzz Paper Reading: Natural attack for pre-trained models of code
## Abstract 背景:目前大多数的adversarial attack method on pre-trained models of code忽略了perturbations should be natural to human judges(naturalness requirement ......
论文解读(MTEM)《Meta-Tsallis-Entropy Minimization: A New Self-Training Approach for Domain Adaptation on Text Classification》
Note:[ wechat:Y466551 | 可加勿骚扰,付费咨询 ] 论文信息 论文标题:Meta-Tsallis-Entropy Minimization: A New Self-Training Approach for Domain Adaptation on Text Classific ......
Proj CDeepFuzz Paper Reading: COMET: Coverage-guided Model Generation For Deep Learning Library Testing
## Abstract 背景:已有的方法(Muffin, Lemon, Cradle) can cover at most 34.1% layer inputs, 25.9% layer parameter values, and 15.6% layer sequences. 本文:COMET Gi ......