<?xml version="1.0" encoding="utf-8" ?><rss version="2.0"><channel><title><![CDATA[Stanford6的博客]]></title><description><![CDATA[]]></description><link>https://blog.youkuaiyun.com/Stanford6</link><language>zh-cn</language><generator>https://blog.youkuaiyun.com/</generator><copyright><![CDATA[Copyright &copy; Stanford6]]></copyright><item><title><![CDATA[树莓派安装中文输入法的简单方法]]></title><link>https://blog.youkuaiyun.com/Stanford6/article/details/120547187</link><guid>https://blog.youkuaiyun.com/Stanford6/article/details/120547187</guid><author>Stanford6</author><pubDate>Wed, 29 Sep 2021 13:55:46 +0800</pubDate><description><![CDATA[树莓派安装中文输入法的简单方法
# 第一步
sudo apt update

# 第二步
sudo apt install -y fcitx-googlepinyin

# 第三步
reboot

# 第四步 可以看到右上角的键盘符号， 输入时，点击它就能切换谷歌拼音输入法
![在这里插入图片描述](https://img-blog.csdnimg.cn/203dd0a978574ad29361ded351f6b224.png?x-oss-process=image/watermark,type_ZHJva]]></description><category></category></item><item><title><![CDATA[python调用百度unit实现对话（科大讯飞平台也类似）]]></title><link>https://blog.youkuaiyun.com/Stanford6/article/details/120018100</link><guid>https://blog.youkuaiyun.com/Stanford6/article/details/120018100</guid><author>Stanford6</author><pubDate>Tue, 31 Aug 2021 15:12:54 +0800</pubDate><description><![CDATA[本博客记录python调用百度unit实现对话，再搭配语音合成、语音唤醒即可实现自定义的聊天机器人等。参考其它博客，硬是没跑起来，一直报错，可能是API3.0改版的原因，改动的地方程序中已标出。
1  改动1，这个地方很多坑，1，内容要放在"   "里面， 2"version"要填"3.0"不是2.0  3，“service_id”:"S57400"换成自己的机器人ID，如图，
post_data = "{\"version\":\"3.0\",\"service_id\":\"S57400\",\"ses]]></description><category></category></item><item><title><![CDATA[MATLAB 使用PLS建模并预测]]></title><link>https://blog.youkuaiyun.com/Stanford6/article/details/120006391</link><guid>https://blog.youkuaiyun.com/Stanford6/article/details/120006391</guid><author>Stanford6</author><pubDate>Mon, 30 Aug 2021 21:54:40 +0800</pubDate><description><![CDATA[1 数据标准化（可省略）
例如z-score
2 主成分分析
help pca     # 使用这个指令查看帮助
[coeff, score, latent, tsquared, explained] = pca(ingredients);

3 PLS建模并预测
 help plsregres  # 使用这个指令查看帮助
 
[xl,yl,xs,ys,beta,pctvar,mse] = plsregress(X,Y, ‘主成分个数’);


...]]></description><category></category></item><item><title><![CDATA[keras中使用concatenate报错]]></title><link>https://blog.youkuaiyun.com/Stanford6/article/details/119374967</link><guid>https://blog.youkuaiyun.com/Stanford6/article/details/119374967</guid><author>Stanford6</author><pubDate>Wed, 04 Aug 2021 09:00:04 +0800</pubDate><description><![CDATA[Layer concatenate_1 was called with an input that isn't a symbolic tensor. Received type: &lt;class 'tuple'&gt;. Full input:

原代码
x = concatenate((input_1, input_2), axis=1)

修改代码
x = concatenate([input_1, input_2], axis=1)


]]></description><category></category></item><item><title><![CDATA[python读取含有结构体struct的.mat文件]]></title><link>https://blog.youkuaiyun.com/Stanford6/article/details/115623698</link><guid>https://blog.youkuaiyun.com/Stanford6/article/details/115623698</guid><author>Stanford6</author><pubDate>Mon, 12 Apr 2021 15:18:42 +0800</pubDate><description><![CDATA[数据如图

data_path2 = './tablet_dataset/tablet_new.mat'
x_train = sio.loadmat(data_path2)['x_train_1'][0, 0]['data']
print("x_train.shape,", x_train.shape)

另一种写法
data_path2 = './tablet_dataset/tablet_new.mat'
x_train = sio.loadmat(data_path2)['x_train_1']
x_]]></description><category></category></item><item><title><![CDATA[ValueError: You are trying to load a weight file containing 5 layers into a model with 9 layers.]]></title><link>https://blog.youkuaiyun.com/Stanford6/article/details/115606260</link><guid>https://blog.youkuaiyun.com/Stanford6/article/details/115606260</guid><author>Stanford6</author><pubDate>Sun, 11 Apr 2021 20:56:17 +0800</pubDate><description><![CDATA[kera报错：ValueError: You are trying to load a weight file containing 5 layers into a model with 9 layers.
报错原因：擅自修改模型的层的名称
解决办法：load_weight()时添加参数by_name = True
weight_path = ' '
model.load_weights(weight_path, by_name = True)


...]]></description><category></category></item><item><title><![CDATA[LG G7ULM版只有移动2G,不能用4G的解决方法]]></title><link>https://blog.youkuaiyun.com/Stanford6/article/details/115584693</link><guid>https://blog.youkuaiyun.com/Stanford6/article/details/115584693</guid><author>Stanford6</author><pubDate>Sat, 10 Apr 2021 21:37:31 +0800</pubDate><description><![CDATA[Go to Settings Connections Mobile networks
Access Point Names
Add a new APN by pressing ADD on right top
corner. If device has already set values for China
Mobile for any fields below leave them. Change
others as below.
Name:China Mobile
APN:cmnet
Proxy:
P]]></description><category></category></item><item><title><![CDATA[tensorflow2/kera搭建网络模型报错Input layers to a `Model` must be `InputLayer` objects. Received inputs:]]></title><link>https://blog.youkuaiyun.com/Stanford6/article/details/115553948</link><guid>https://blog.youkuaiyun.com/Stanford6/article/details/115553948</guid><author>Stanford6</author><pubDate>Fri, 09 Apr 2021 16:38:21 +0800</pubDate><description><![CDATA[报错内容
Input layers to a `Model` must be `InputLayer` objects. 
Received inputs: Tensor("batch_normalization_1/cond/Merge:0", 
shape=(?, 321, 64), dtype=float32). 
Input 0 (0-based) originates from layer type `BatchNormalization`.

原程序
def build_disk_and_q_n]]></description><category></category></item><item><title><![CDATA[简单解决jupyter notebook没有其它conda环境及访问D,E盘的问题]]></title><link>https://blog.youkuaiyun.com/Stanford6/article/details/115391887</link><guid>https://blog.youkuaiyun.com/Stanford6/article/details/115391887</guid><author>Stanford6</author><pubDate>Fri, 02 Apr 2021 10:12:18 +0800</pubDate><description><![CDATA[本教程是在windows系统上操作
1 解决jupyter notebook没有其它conda环境
1.1打开anaconda prompt, 在base环境下使用命令
conda install nb_conda

安装可能会很慢，需要切换conda源，在C:\Users\用户名\下打开.condarc文件（没有就新建一个）
channels:
  #- defaults
  - https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main/
  - ht]]></description><category></category></item><item><title><![CDATA[数据归一化-matlab代码]]></title><link>https://blog.youkuaiyun.com/Stanford6/article/details/115347524</link><guid>https://blog.youkuaiyun.com/Stanford6/article/details/115347524</guid><author>Stanford6</author><pubDate>Wed, 31 Mar 2021 12:36:00 +0800</pubDate><description><![CDATA[记A为原始数据，A1为归一化后的数据， PS为对应关系**
1.归一化
FlattenedData = A(:)'; % 展开矩阵为一列，然后转置为一行。

[A1,PS] = mapminmax(FlattenedData, -1, 1); % 归一化到[-1, 1]。

A2 = reshape(A1, size(A)); 还原为原始矩阵形式。

2.反归一化
A3= mapminmax('reverse',A1,PS)；  %反归一化
A4=reshape(A3, size(A));         ]]></description><category></category></item><item><title><![CDATA[keras报错：ValueError: Layer model_1 was called with an input that isn’t a symbolic tensor]]></title><link>https://blog.youkuaiyun.com/Stanford6/article/details/115301209</link><guid>https://blog.youkuaiyun.com/Stanford6/article/details/115301209</guid><author>Stanford6</author><pubDate>Mon, 29 Mar 2021 14:47:53 +0800</pubDate><description><![CDATA[keras报错：ValueError: Layer model_1 was called with an input that isn’t a symbolic tensor
后面还有错误
Received type: &lt;class 'numpy.ndarray'&gt;

All inputs to the layer should be tensors.

解决办法
例如搭建了自定义的网络模型self.discriminator_layer1, 在调用时不能忘了加.predict
self.dis]]></description><category></category></item><item><title><![CDATA[windows系统conda环境安装pytorch gpu版、tensorflow gpu版]]></title><link>https://blog.youkuaiyun.com/Stanford6/article/details/107401129</link><guid>https://blog.youkuaiyun.com/Stanford6/article/details/107401129</guid><author>Stanford6</author><pubDate>Fri, 17 Jul 2020 10:01:49 +0800</pubDate><description><![CDATA[1.查看电脑英伟达驱动的cuda版本

**2.（conda环境里再次安装cuda,但版本必须低于或等于上面查询的版本，这样就不用做一些教程说的去英伟达官网下载cuda,注册下载cudnn），创建conda环境：
conda create -n pytorch python=3.7

使用命令conda activate pytorch 进入conda虚拟环境后，使用命令安装英伟达的SDK10.1版本：
conda install cudatoolkit=10.1

安装英伟达深度学习软件包7.6版本
co]]></description><category></category></item><item><title><![CDATA[ubuntu18.4中使用dock安装配置Autoware]]></title><link>https://blog.youkuaiyun.com/Stanford6/article/details/103391058</link><guid>https://blog.youkuaiyun.com/Stanford6/article/details/103391058</guid><author>Stanford6</author><pubDate>Wed, 04 Dec 2019 17:41:40 +0800</pubDate><description><![CDATA[ubuntu18.4中使用dock安装配置Autoware一、准备工作二、安装 docker1、 添加 docker 的官方 key2、确认添加成功3、添加 docker repository4、安装 docker三、安装 Autoware四、Autoware.AI的安装五、运行官方的demo2、运行autowre3、依次把文件添加进去
一、准备工作
官方对电脑配置的建议：
通用x86；
Inte...]]></description><category></category></item></channel></rss>