<?xml version="1.0" encoding="utf-8" ?><rss version="2.0"><channel><title><![CDATA[专心搬砖...]]></title><description><![CDATA[]]></description><link>https://blog.youkuaiyun.com/qq_37508554</link><language>zh-cn</language><generator>https://blog.youkuaiyun.com/</generator><copyright><![CDATA[Copyright &copy; qq_37508554]]></copyright><item><title><![CDATA[Stable diffusion inference 多卡并行]]></title><link>https://blog.youkuaiyun.com/qq_37508554/article/details/143264564</link><guid>https://blog.youkuaiyun.com/qq_37508554/article/details/143264564</guid><author>qq_37508554</author><pubDate>Sun, 27 Oct 2024 09:53:10 +0800</pubDate><description><![CDATA[需要注意的是，diffusers的版本太高时，device_map的参数类型有要求，0.28.0时候，只能输入str，而这个str有几个指定的选项，然而，我在尝试使用"auto“时，提示只能输入”balanced“diffusers版本低于0.28.0时候才支持其他选项，同时支持自定义device_map，如0.27.2是可以的。，上述模型分片要注意不能随意分片，至少同一个模型需要在一个GPU上，否则会报如下错误。stable diffusion 推理过程 多卡并行 注意事项。]]></description><category></category></item><item><title><![CDATA[Stable diffusion的一些参数意义及常规设置]]></title><link>https://blog.youkuaiyun.com/qq_37508554/article/details/133975130</link><guid>https://blog.youkuaiyun.com/qq_37508554/article/details/133975130</guid><author>qq_37508554</author><pubDate>Sun, 22 Oct 2023 19:02:28 +0800</pubDate><description><![CDATA[stable diffusion常用参数解释]]></description><category></category></item><item><title><![CDATA[Stable-diffusion webui AttributeError: module ‘cv2.dnn‘ has no attribute ‘DictValue‘]]></title><link>https://blog.youkuaiyun.com/qq_37508554/article/details/132650604</link><guid>https://blog.youkuaiyun.com/qq_37508554/article/details/132650604</guid><author>qq_37508554</author><pubDate>Sun, 03 Sep 2023 15:29:10 +0800</pubDate><description><![CDATA[stable-diffusion webui AttributeError: module 'cv2.dnn' has no attribute 'DictValue']]></description><category></category></item><item><title><![CDATA[软件设计模式-代理模式(利用java解释）]]></title><link>https://blog.youkuaiyun.com/qq_37508554/article/details/130006753</link><guid>https://blog.youkuaiyun.com/qq_37508554/article/details/130006753</guid><author>qq_37508554</author><pubDate>Fri, 07 Apr 2023 11:27:22 +0800</pubDate><description><![CDATA[代理模式（静态代理，动态代理，cglib代理)]]></description><category></category></item><item><title><![CDATA[Python读取,预处理DICOM文件方式]]></title><link>https://blog.youkuaiyun.com/qq_37508554/article/details/129711579</link><guid>https://blog.youkuaiyun.com/qq_37508554/article/details/129711579</guid><author>qq_37508554</author><pubDate>Wed, 22 Mar 2023 15:53:45 +0800</pubDate><description><![CDATA[python读取，处理dicom文件方式]]></description><category></category></item><item><title><![CDATA[java 常用数据结构及算法tips]]></title><link>https://blog.youkuaiyun.com/qq_37508554/article/details/129506754</link><guid>https://blog.youkuaiyun.com/qq_37508554/article/details/129506754</guid><author>qq_37508554</author><pubDate>Mon, 13 Mar 2023 21:12:23 +0800</pubDate><description><![CDATA[java 
有序的TreeMap
遍历map
并查集及优化
kmp
差分数组]]></description><category></category></item><item><title><![CDATA[基础算法用golang实现(部分用C++)]]></title><link>https://blog.youkuaiyun.com/qq_37508554/article/details/128008319</link><guid>https://blog.youkuaiyun.com/qq_37508554/article/details/128008319</guid><author>qq_37508554</author><pubDate>Wed, 23 Nov 2022 21:40:03 +0800</pubDate><description><![CDATA[基础算法用golang实现，快速排序；递归创建，（递归、迭代）前中后序遍历二叉树]]></description><category></category></item><item><title><![CDATA[python无法识别自有包/方法]]></title><link>https://blog.youkuaiyun.com/qq_37508554/article/details/126948117</link><guid>https://blog.youkuaiyun.com/qq_37508554/article/details/126948117</guid><author>qq_37508554</author><pubDate>Tue, 20 Sep 2022 10:25:27 +0800</pubDate><description><![CDATA[python pytorch常见小bug记录，无法识别自有文件路径]]></description><category></category></item><item><title><![CDATA[pytorch实现在cuda上多进程，能获取处理函数返回值]]></title><link>https://blog.youkuaiyun.com/qq_37508554/article/details/126248137</link><guid>https://blog.youkuaiyun.com/qq_37508554/article/details/126248137</guid><author>qq_37508554</author><pubDate>Tue, 09 Aug 2022 15:31:50 +0800</pubDate><description><![CDATA[multiprocessing python多进程代码实现
pytorch 实现cuda多进程，并获取返回值代码实现]]></description><category></category></item><item><title><![CDATA[vscode python 设置（本地/远程服务器）代码自动提示、错误提示、函数变量跳转]]></title><link>https://blog.youkuaiyun.com/qq_37508554/article/details/125385207</link><guid>https://blog.youkuaiyun.com/qq_37508554/article/details/125385207</guid><author>qq_37508554</author><pubDate>Tue, 21 Jun 2022 09:49:33 +0800</pubDate><description><![CDATA[vscode 设置python代码自动提示，错误提示，函数跳转


重启vscode就有了代码自动提示与错误提示Ctrl + 鼠标左键,跳转到函数定义的位置Alt + ←，跳转回之前的位置]]></description><category></category></item><item><title><![CDATA[Linux kill不掉进程解决方案]]></title><link>https://blog.youkuaiyun.com/qq_37508554/article/details/121783698</link><guid>https://blog.youkuaiyun.com/qq_37508554/article/details/121783698</guid><author>qq_37508554</author><pubDate>Wed, 08 Dec 2021 09:27:27 +0800</pubDate><description><![CDATA[kill不了进程的解决方案
kill它的父进程！
显存被占用但是找不到进程-> fuser -v /dev/nvidia*]]></description><category></category></item><item><title><![CDATA[nvidia-smi报错：NVIDIA-SMI has failed because it couldn‘t communicate with the NVIDIA driver]]></title><link>https://blog.youkuaiyun.com/qq_37508554/article/details/121699332</link><guid>https://blog.youkuaiyun.com/qq_37508554/article/details/121699332</guid><author>qq_37508554</author><pubDate>Fri, 03 Dec 2021 15:29:56 +0800</pubDate><description><![CDATA[输入nvidia-smi显示
NVIDIA-SMI has failed because it couldn‘t communicate with the NVIDIA driver

但是torch.cuda.is_available()还能用，这就有些别扭了
出现这个问题一般是由于kernel mod 的 Nvidia driver 的版本没有更新
（不是人为因素）
解决办法：
1，重启机器（如果有足够权限的话，直接就能解决）
2，如果权限不够，不能重启的话，那就用命令reload kernel mod]]></description><category></category></item><item><title><![CDATA[pytorch实现数值型数据简单预测]]></title><link>https://blog.youkuaiyun.com/qq_37508554/article/details/121663061</link><guid>https://blog.youkuaiyun.com/qq_37508554/article/details/121663061</guid><author>qq_37508554</author><pubDate>Wed, 01 Dec 2021 19:59:20 +0800</pubDate><description><![CDATA[import torch
import pandas as pd
import numpy as np
import torch.utils.data as Data
import os

df = pd.read_csv(r'res.csv',
                 names=['sex', 'age', 'Hb', 'ALB', 'BUN', 'SCr_not', 'Hydronephrosis', 'diabetes', 'HighBlood',
                    ]]></description><category></category></item><item><title><![CDATA[浅谈目标检测RCNN,SPPNET,Fast-RCNN,Faster-RCNN]]></title><link>https://blog.youkuaiyun.com/qq_37508554/article/details/121604594</link><guid>https://blog.youkuaiyun.com/qq_37508554/article/details/121604594</guid><author>qq_37508554</author><pubDate>Mon, 29 Nov 2021 10:55:15 +0800</pubDate><description><![CDATA[RCNN
目标检测-R-CNN模型
●CVPR 2014
●候选区域方法(region proposal method) :提供了额物体检测的一个重要思路
●RCNN步骤:
。1、对于一张图片，找出默认2000个候选区域
。2、2000个候选区域做大小变换(crop+warp)，输入AlexNet当中， 得到特征向量：[2000, 4096]
。3、经过20个类别的SVM分类器，对于2000个候选区域做判断，得到[2000, 20]得分矩阵
。4、2000个候选区域做非极大抑制（NMS），去除不好的，重叠度]]></description><category></category></item><item><title><![CDATA[深度学习与神经网络]]></title><link>https://blog.youkuaiyun.com/qq_37508554/article/details/121548032</link><guid>https://blog.youkuaiyun.com/qq_37508554/article/details/121548032</guid><author>qq_37508554</author><pubDate>Thu, 25 Nov 2021 21:33:40 +0800</pubDate><description><![CDATA[深度学习的优势


在小规模数据集上，深度学习算法相对于其他手工精心设计的算法可能并不会表现出优势，有时甚至并不能比那些算法效果更好，但当数据集变大时进入大数据领域时 ，深度学习才能表现出稳定的优势。
同时，不同结构的深度学习对于非结构化的数据（例如图像，序列数据处理比其他的机器学习算法更有优势。
深度学习的兴起依赖于三点：大数据，计算资源，算法的提升（使得深度学习训练得更快，激活函数从sigmod函数变成ReLu函数）
2. logistic回归分类回顾
2.1 损失函数和代价函数定义
吴恩达这里把损失.]]></description><category></category></item><item><title><![CDATA[linux关闭终端后台运行进程方法nohup]]></title><link>https://blog.youkuaiyun.com/qq_37508554/article/details/121529938</link><guid>https://blog.youkuaiyun.com/qq_37508554/article/details/121529938</guid><author>qq_37508554</author><pubDate>Thu, 25 Nov 2021 09:14:46 +0800</pubDate><description><![CDATA[通过ps ux指令查看所有的进程的PID，通过 kill 指令关闭进程
ps ux  # 查看所有进程的PID
kill -9 PID  # 关闭特定进程



Linux自带的nohup命令设定训练在后台运行，避免因为终端断开链接而使训练停止
只需要在以前训练的指令前增加 nohup命令，同时在结尾加上&amp;符号即可
# nohup xxxxxx &amp;  其中‘xxxxxx’为原始指令
nohup python -m visdom.server &amp;  # 后台运行visdom.ser..]]></description><category></category></item><item><title><![CDATA[显卡驱动报错：NVIDIA-SMI has failed because it couldn‘t communicate with the NVIDIA driver]]></title><link>https://blog.youkuaiyun.com/qq_37508554/article/details/121465616</link><guid>https://blog.youkuaiyun.com/qq_37508554/article/details/121465616</guid><author>qq_37508554</author><pubDate>Mon, 22 Nov 2021 10:14:41 +0800</pubDate><description><![CDATA[系统：ubuntu 18.04
突然发现cuda不能用
torch.cuda.is_available() ==&gt;False
终端输入 nvidia-smi显示如下

NVIDIA-SMI has failed because it couldn’t communicate with the NVIDIA driver

其他博客上说：“这是一个常见问题，经常出现在ubuntu系统中，主要原因还是系统内核升级了，导致新版本内核和原来显卡驱动不匹配”
并且给出了两种解决方案
解决方法一：
只需执行两条命]]></description><category></category></item><item><title><![CDATA[Python代理邮箱发送邮件（163邮箱为例）]]></title><link>https://blog.youkuaiyun.com/qq_37508554/article/details/120764321</link><guid>https://blog.youkuaiyun.com/qq_37508554/article/details/120764321</guid><author>qq_37508554</author><pubDate>Thu, 14 Oct 2021 15:00:21 +0800</pubDate><description><![CDATA[import smtplib,sys
from email.mime.text import MIMEText
from email.header import  Header


def mail_tools(mail_from,send_to,title,input_msg):
	#mail_from='mail_from&lt;mail_from_name@163.com&gt;'#收件人看到的邮件来源信息
	#send_to="#######@qq.com"#收件人邮箱
	#title="下雨"#邮]]></description><category></category></item><item><title><![CDATA[Tf2，pytorch 获取Tensor的值]]></title><link>https://blog.youkuaiyun.com/qq_37508554/article/details/120757907</link><guid>https://blog.youkuaiyun.com/qq_37508554/article/details/120757907</guid><author>qq_37508554</author><pubDate>Thu, 14 Oct 2021 09:56:29 +0800</pubDate><description><![CDATA[tensorflow pytorch 获取Tensor的值

 
tensor = tf.Variable(10, dtype=tf.int32) 
 
with tf.compat.v1.Session() as sess:
    sess.run(tf.compat.v1.global_variables_initializer())
    value = sess.run(tensor)        #value 就是你想要的值


]]></description><category></category></item><item><title><![CDATA[利用Spring Boot（SMTP）发送邮件]]></title><link>https://blog.youkuaiyun.com/qq_37508554/article/details/87904796</link><guid>https://blog.youkuaiyun.com/qq_37508554/article/details/87904796</guid><author>qq_37508554</author><pubDate>Fri, 03 Jul 2020 08:53:46 +0800</pubDate><description><![CDATA[利用Spring Boot发送邮件，以163邮箱为例
]]></description><category></category></item></channel></rss>