From e28cfa1408036535cb26e11a9f63cf0724825647 Mon Sep 17 00:00:00 2001 From: Edge Date: Tue, 13 Jul 2021 15:19:18 +0800 Subject: [PATCH] v0.01 added base function and tested --- Edge计算引擎.pdf | 11933 ++++++++++++++++ Edge计算引擎.xmind | Bin 0 -> 93575 bytes README.md | 553 +- README_EN.md | 231 + a.csv | 2079 +++ autodiff/dor.h | 16 + autodiff/graph.h | 26 + autodiff/mor.h | 14 + autodiff/node.h | 72 + autodiff/por.h | 16 + autodiff/vectmath.h | 99 + conv_.cpp | 34 + data/data.csv | 1800 +++ data/nerual_data.csv | 100 + data/new_data2.csv | 100 + data_struct/data_struct_pro.c | 107 + data_struct/data_struct_pro.h | 47 + data_struct_test.cpp | 93 + file_pro/data_read.h | 196 + grad_edge/matrix_grad.h | 87 + image-20200128154352842.png | Bin 0 -> 173888 bytes image-20200418210521131.png | Bin 0 -> 7223 bytes install_diff/Makefile | 62 + install_diff/bin/ann | Bin 0 -> 79312 bytes install_diff/bin/gradient | Bin 0 -> 58272 bytes install_diff/bin/gradient_descent | Bin 0 -> 58328 bytes 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z%Al`Z!3PYj$T#Fr$c@l&zXSEo+8&hlL=X>4-AC&-_1rNn!*r?~lUi2S5pR)1CCHy{ z%%`_YNB`0q-;Mo9$^2*2oyXr57#^JAi!hwhhDTf%^yQsa#HVw-n1LF@kkv36L%!vg z*V*>Php9_kt1EifVb?VlZYi~8m$nKfZ{ zUl04rJt6H`MHi17osV+>FUvO!5z{ae^E8H}3a(v~hA#SAjWp$3V5LY3w%cOI*_c72?nRQr>Kj8c>i&Se7Fp`j(d>RJm(ih3chS@Q(dz zxan~LN!fo2Tv~+Cu_E7-q1t!-m%wFYYiVZc^lvq(LS1@%LTXWNl7?zbmQKCCTwQu< zng-bMp+4g7&i`E-uV{TCVIXlJL6kHvE^2PQuw!5%6YznIsZvA8fJdsM^8-jx1{eet z=)VLtpnnN!|GN3_=D#N4f0yqW`CmoV!o>z)Yh-Ed#PA>Bzm+(|FzXu~O<4@>; +# Edge-Engine + + + +## Edge : 一个开源的科学计算引擎 + +[README for English_version](./README_EN.md) + +声明：本项目禁止闭源商用，如有需要请和作者取得联系 + +email: zk@likedge.top + +
[![GitHub license](https://img.shields.io/badge/license-Apache--2.0-blue.svg)](https://raw.githubusercontent.com/tesseract-ocr/tesseract/master/LICENSE)
+ +------ + + + +> 项目开始日期 : 2019/10/01 +> +> 目前项目总代码 : 810 行 +> +> 测试 : main.cpp | nerual_network.cpp | 新增全连接神经网络架构(新增全连接网络正向传播和反向传播的测试demo) +> +> 测试环境: +> +> MacBook Pro +> +> 编译器环境: +> +> Configured with: --prefix=/Applications/Xcode.app/Contents/Developer/usr --with-gxx-include-dir=/Applications/Xcode.app/Contents/Developer/Platforms/MacOSX.platform/Developer/SDKs/MacOSX10.14.sdk/usr/include/c++/4.2.1 +> Apple LLVM version 10.0.1 (clang-1001.0.46.4) +> Target: x86_64-apple-darwin18.7.0 +> Thread model: posix + +image-20200418210521131 + + + +------ + +这是什么? + +![path](./picture/path.png) + +## 安装编译 + +``` +git clone git@github.com:AllenZYJ/Edge-Computing-Engine.git + +cd to install_diff +``` + +进入install_diff目录: + +执行 + +``` +make +make install +``` + +编译demo入口程序 + +```shell +➜ edge-computing-engine git:(master) ✗ g++ main.cpp -o ma -lautodiff +``` + +或者BP测试程序 + +```shell +➜ edge-computing-engine git:(master) ✗ g++ nerual_network.cpp -o ma +``` + +运行 + +```shell +➜ edge-computing-engine git:(master) ✗ ./main +``` + +最新卷积实现： + +```c++ +double conv_test(Matrix mid1,int input_dim = 3,int output_channels = 3,int stride = 1,int kernel_size = 2,int mode = 0,int padding = 0) +``` + + + +序贯模型api使用方法: + +edge_network(int input, int num_neuron) + +作为序列模型api + +edge_network作为一个类型存在,位于matrix_grad.h中结构体类型的数据 + +定义了前向传播函数,前向传播无激活版,反向传播,末层反向传播,四大最常用的函数主体. + +完整的序列模型: + +![image-20200128154352842](/Users/zhangyiji/Documents/code/cpp_demo/my_os/Edge-Computing-Engine/image-20200128154352842.png) + +## 新的demo程序实现5层全连接层,可自定义神经元和激活函数,损失函数 + +全连接层使用方法: + +第一层的权重自定义,而后调用forward函数前向传播一层,自动求出激活以后的值,激活函数可自定义. + +首先定义一个权重矩阵和偏置矩阵,第一个矩阵的维度大小使用数据列去定义: + +```c +Matrix bias1 = CreateRandMat(2,1); +Matrix weight1 = CreateRandMat(2,data.col); +``` + +之后可以输出第一层前向传播的值,同时可以定义下一层的bias的维度, row使用第一层的权重矩阵的行,第二层的权重矩阵的行使用了第一层的输出的行, 而列自行定义即可, 这一点体现了前向传播算法的维度相容. 也就是: + +```c +Matrix output1 = sequaltial.forward(get_T(get_row(data_mine,index)),weight1,bias1); ``` -#### 从命令行推送已经创建的仓库 +```c +Matrix weight2 = CreateRandMat(output1.row,2); +Matrix bias2 = CreateRandMat(weight2.row,1); +Matrix output2 = sequaltial.forward(output1,weight2,bias2); +``` + +同时第二层的输出也可以求出来,以此类推 . + +最终输出代码见nerual_test.cpp ![nerual_test1](/Users/zhangyiji/Documents/code/cpp_demo/my_os/Edge-Computing-Engine/picture/nerual_test1.png) -```bash -git remote add origin https://git.trustie.net/Edge/Edge-Computing-Engine.git -git push -u origin master +代码: +```c +Matrix data_mine = CreateRandMat(2,1); +Matrix label = CreateMatrix(2,1); +Matrix weight1 = CreateRandMat(2,2); +Matrix weight2 = CreateRandMat(2,2); +Matrix weight3 = CreateRandMat(2,2); +Matrix weight4 = CreateRandMat(2,2); +for(int epoch = 0;epoch<20;epoch++) +{ +cout_mat(weight1); +edge_network sequaltial(2,2); + +Matrix output1 = sequaltial.forward(data_mine,weight1); +Matrix output2 = sequaltial.forward(output1,weight2); +Matrix output3 = sequaltial.forward(output2,weight3); +Matrix output4 = sequaltial.forward(output3,weight4); +Matrix output_end = sequaltial.end_layer_backward(label,output4); +//get the forward +Matrix backward1 = sequaltial.backward(output_end,output3,weight4); +Matrix grad_w1w2 = mul_simple(backward1,data_mine); +Matrix backward2 = sequaltial.backward(backward1,output2,weight3); +Matrix grad_w3w4 = mul_simple(backward2,data_mine); +Matrix backward3 = sequaltial.backward(backward2,output1,weight2); +Matrix grad_w5w6 = mul_simple(backward3,data_mine); +Matrix backward4 = sequaltial.backward(backward3,output4,weight1); +Matrix grad_w7w8 = mul_simple(backward4,data_mine); +weight1 = subtract(weight1,times_mat(0.0001,padding(grad_w1w2,2,2))); +weight2 = subtract(weight2,times_mat(0.0001,padding(grad_w3w4,2,2))); +weight3 = subtract(weight3,times_mat(0.0001,padding(grad_w5w6,2,2))); +weight4 = subtract(weight4,times_mat(0.0001,padding(grad_w7w8,2,2))); +} +``` +```shell +---------epoch: 0------------ +loss: 4.65667 +loss: 3.28273 +---------epoch: 1------------ +loss: 4.65655 +loss: 3.28265 +---------epoch: 2------------ +loss: 4.65643 +loss: 3.28257 +---------epoch: 3------------ +loss: 4.65631 +loss: 3.28249 +---------epoch: 4------------ +loss: 4.65619 +loss: 3.2824 +---------epoch: 5------------ +loss: 4.65607 +loss: 3.28232 +---------epoch: 6------------ +loss: 4.65596 +loss: 3.28224 +---------epoch: 7------------ +loss: 4.65584 +loss: 3.28216 +---------epoch: 8------------ +loss: 4.65572 +loss: 3.28208 +---------epoch: 9------------ +loss: 4.6556 +loss: 3.282 +---------epoch: 10------------ +loss: 4.65548 +loss: 3.28192 +---------epoch: 11------------ +loss: 4.65536 +loss: 3.28184 +---------epoch: 12------------ +loss: 4.65524 +loss: 3.28176 +---------epoch: 13------------ +loss: 4.65512 +loss: 3.28168 +---------epoch: 14------------ +loss: 4.65501 +loss: 3.2816 +---------epoch: 15------------ +loss: 4.65489 +loss: 3.28152 +---------epoch: 16------------ +loss: 4.65477 +loss: 3.28144 +---------epoch: 17------------ +loss: 4.65465 +loss: 3.28136 +---------epoch: 18------------ +loss: 4.65453 +loss: 3.28128 +---------epoch: 19------------ +loss: 4.65441 +loss: 3.2812 ``` +## Bp反向传播的demo程序基于Pytorch官方代码模拟实现测试 + +迭代结果 : + +W1: 0.6944 1.52368 + -1.46644 -0.154097 +W2: 1.10079 + 0.462984 +loss: 0.559269 + +epoch:100 , 可自行测试. + +输出最终损失和参数迭代结果. + +-----------split-line----------- +2.79955 +0.36431 +-0.451694 +epoch: 100 error: 6.05895 +-----------split-line----------- +0.009167(sum of loss) + +### 目前实现的程序接口 + +### API: + +- [x] Matrix read_csv(string &file_path)读取格式化文件(csv),返回一个自动计算长度的矩阵. + +- [x] 实现格式化文件写入接口.比较pandas.to_csv. + +- [x] 矩阵广播机制,实现padding接口 + +- [x] 全连接层前向传播和反向传播接口,支持自动求导 + +- [x] 矩阵微分和自动求导接口封装 + +- [x] int save_txt(Matrix mid1,string path = "./",string delimiter = ",",string header="./") 设计文件流获取文件头部接口 , 写入格式化文件 , 已设计支持矩阵类型数据写入,支持自定义表头,写入文件路径 , 自定义分隔符,默认为" , ". + +- [x] Create a matrix : create(row,cols)开辟一个矩阵结构的内存,元素初值为0; + +- [x] Change the element for matrix void move_ele(int &ele1, int &ele2),修改某一个位置的元素的值. + +- [x] Matrix1+Matrix2 : Matrix add(Matrix mid1,Matrix mid2,int flag=1),矩阵加和操作接口,可选位运算加速. + +- [x] Flag is how to compete the ele ,default 1 ,bitwise operation(位运算加速). + +- [x] Matrix1-Matrix2 : Matrix subtract(Matrix mid1,Matrix mid2) + +- [x] Matrix1*Matrix2 : Matrix mul(Matrix mid1,Matrix mid2) + +- [x] Matrix1*n : Matrix times_mat(int times,Matrix mid1) + +- [x] Matrix1's Transposition : Matrix get_T(Matrix mid1)矩阵转置 + +- [x] Mul(matrix1,matrix2)矩阵乘积(完整数学定义). + +- [x] double* flatten(Matrix mid1) : Return a flattened array.矩阵展开 + +- [x] Matrix matrix_rs(Matrix mid1,int rs_row,int rs_col) 矩阵的结构压缩 + +- [x] double matrix_sum(Matrix mid1)矩阵求和 + +- [x] double matrix_mean(Matrix mid1)均值 + +- [x] Matrix appply(Matrix mid1,Matrix mid2,int axis = 0)矩阵拼接 + +- [x] Matrix iloc(Matrix mid1,int start_x=0,int end_x=0,int start_y=0,int end_y=0)矩阵切片 + +- [x] Matrix mul_simple(Matrix mid1,Matrix mid2)为了贴合机器学习的需要,实现了矩阵对应元素相乘,请与传统意义的矩阵乘法区分开. + +- [x] Relu激活函数矩阵接口 + +- [x] 均方误差矩阵接口 + +- [x] 创建随机权重矩阵接口 + + ### 即将着手开发: + +- [ ] 卷积神经网络定义(包括但不限于卷积核,池化层定义,自定义损失接口). + +- [ ] 随机森林算法封装. + +- [ ] 主流网络架构实现. + + + +## 反向传播测试demo: + +```c +#include +#include +#include +#include +#include +#include +#include +#include"./matrix/matrix_def.h" +#include"./matrix/matrix_pro.h" +#include"./welcome/score_wel.cpp" +#include"./logistic/logistic_def.h" +#include"./file_pro/data_read.h" +using namespace std; +clock_t start, stop; +double duration; +int main() +{ + welcome(); + string path = "./data/nerual_data.csv"; + Matrix data = read_csv(path); + Matrix bais = CreateMatrix(data.row,1); + Matrix x = iloc(data,0,100,0,2); + Matrix y = iloc(data,0,100,2,3); + int N=100,in_Dim=2,H_num=2,out_Dim=2; + double learning_rate = 0.0001; + Matrix W1 = CreateRandMat(in_Dim,H_num); + Matrix W2 = CreateRandMat(H_num,out_Dim); + cout_mat(W1); + cout_mat(W2); + for(int epoch = 0;epoch<100;epoch++) + { + Matrix x_w1 = mul(x,W1); + Matrix re = mat_relu(x_w1); + Matrix out = mul(re,W2); + Matrix mat_sq = mat_sq_loss(out,y); + Matrix grad_y_pred = times_mat(2.0,subtract(out,y)); + Matrix grad_w2 = mul(get_T(re),grad_y_pred); + Matrix grad_h_relu = mul(grad_y_pred,get_T(W2)); + Matrix grad_h_relu_copy = mat_relu(grad_h_relu); + Matrix grad_w1 = mul(get_T(x),grad_h_relu_copy); + Matrix dw1 = times_mat(learning_rate,mul(get_T(x),grad_h_relu_copy)); + W1 = subtract(W1,dw1); + W2 = subtract(W2,times_mat(learning_rate,grad_w2)); + cout<<"W1: "; + cout_mat(W1); + cout<<"W2: "; + cout_mat(W2); + cout<<"loss"<<": "; + cout< 参数 axis=0 : + +| 0 | 7 | 2 | +| ---- | ---- | ---- | +| 0 | 3 | 1 | +| 0 | 0 | 0 | +| 0 | 0 | 11 | +| 0 | 7 | 2 | +| 0 | 3 | 1 | +| 0 | 0 | 0 | +| 0 | 0 | 11 | +------ + +> axis = 1: + +| 0 | 7 | 2 | 0 | 7 | 2 | +| ---- | ---- | ---- | ---- | ---- | ---- | +| 0 | 3 | 1 | 0 | 3 | 1 | +| 0 | 0 | 0 | 0 | 0 | 0 | +| 0 | 0 | 11 | 0 | 0 | 11 | + +------ + +## 更新2019/11/18/00:12 + +- [x] read_csv 通过文件流读取逗号分隔符文件,返回一个自动计算长度的矩阵. + + 例如 CSV's head : + + | -0.017612 | 14.053064 | 0 | + | --------- | --------- | ---- | + | -1.395634 | 4.662541 | 1 | + | -0.752157 | 6.53862 | 0 | + | -1.322371 | 7.152853 | 0 | + | 0.423363 | 11.054677 | 0 | + | 0.406704 | 7.067335 | 1 | + + Get: + + ![](./picture/WX20191119-105411@2x.png) + + + + ## Logistic Regression demo base Edge: + + +```c +#include +#include +#include +#include +#include +#include +#include"./matrix/matrix_def.h" +#include"./matrix/matrix_pro.h" +#include"./welcome/score_wel.cpp" +#include"./logistic/logistic_def.h" +#include"./file_pro/data_read.h" +using namespace std; +clock_t start, stop; +double duration; +int main() +{ + welcome(); + string path = "./new_data2.csv"; + Matrix data = read_csv(path); + Matrix bais = CreateMatrix(data.row,1); + data = appply(data,bais,1); + Matrix y = iloc(data,0,0,3,4); + Matrix x_1 = iloc(data,0,0,0,3); + Matrix x_2 = get_T(x_1); + double alpha = 0.002; + int max_epoch = 100; + Matrix weight = CreateMatrix(3,1); + change_va(weight,0,0,1); + change_va(weight,1,0,1); + change_va(weight,2,0,1); + int epoch = 0; + for(epoch = 0;epoch<=max_epoch;epoch++) + { + cout<<"-----------split-line-----------"< 1. 矩阵元素默认为1 +> 2. 使用位运算加速防止填充过大的数值,但是会损失一定精度,慎用. +> 3. 记得delete(matrix)在你使用完一个矩阵计算单元以后. +> 4. api接口更多的接近于pandas和numpy的使用习惯. +> 5. 更多的细节参见目前最新的代码 +> 6. 欢迎star和关注. +> 7. autodiff部分感谢国外博主Omar的思路提醒. +> + +------ + + + +

+ + + 个人小站:[极度空间](http://likedge.top/) + +作者邮箱:zk@likedge.top | edge@ibooker.org.cn + + QQ:2533524298 diff --git a/README_EN.md b/README_EN.md new file mode 100644 index 0000000..f557b63 --- /dev/null +++ b/README_EN.md @@ -0,0 +1,231 @@ + + +
+ +# Edge-Engine + +## Edge : 一个开源的科学计算引擎 + + + +[![license](https://img.shields.io/github/license/mashape/apistatus.svg?maxAge=2592000) ](https://github.com/AllenZYJ/Edge-Computing-Engine/blob/add-license-1/LICENSE)![](https://img.shields.io/badge/Bulid-Version1.0-green.svg) + +> 项目开始日期 : 2019/10/01 + +> 目前项目总代码 : 709 行 +> +> 测试代码 : 810 行 +> +> 测试环境: +> +> MacBook Pro +> +> 编译器环境: +> +> Configured with: --prefix=/Applications/Xcode.app/Contents/Developer/usr --with-gxx-include-dir=/Applications/Xcode.app/Contents/Developer/Platforms/MacOSX.platform/Developer/SDKs/MacOSX10.14.sdk/usr/include/c++/4.2.1 +> Apple LLVM version 10.0.1 (clang-1001.0.46.4) +> Target: x86_64-apple-darwin18.7.0 +> Thread model: posix +> +> 目前实现的: + +How to install and run the demo: + +`git clone git@github.com:AllenZYJ/Edge-Computing-Engine.git` + +`cd to this dir ` + +`g++ main.cpp -o main` + +`./main` + +Matrix API: + +- [x] Matrix read_csv(string &file_path) +- [x] Create a matrix : create(row,cols) +- [x] Change the element for matrix void move_ele(int &ele1, int &ele2) +- [x] Matrix1+Matrix2 : Matrix add(Matrix mid1,Matrix mid2,int flag=1) +- [x] Flag is how to compete the ele ,default 1 ,bitwise operation(位运算加速). +- [x] Matrix1-Matrix2 : Matrix subtract(Matrix mid1,Matrix mid2) +- [x] Matrix1*Matrix2 : Matrix mul(Matrix mid1,Matrix mid2) +- [x] Matrix1*n : Matrix times_mat(int times,Matrix mid1) +- [x] Matrix1's Transposition : Matrix get_T(Matrix mid1) +- [x] Mul(matrix1,matrix2) +- [x] double* flatten(Matrix mid1) : Return a flattened array. +- [x] Matrix matrix_rs(Matrix mid1,int rs_row,int rs_col) +- [x] double matrix_sum(Matrix mid1) +- [x] double matrix_mean(Matrix mid1) +- [x] Matrix appply(Matrix mid1,Matrix mid2,int axis = 0) +- [x] Matrix iloc(Matrix mid1,int start_x=0,int end_x=0,int start_y=0,int end_y=0) + +## Demo: mat*mat + +Matrix **A**： + +| 第1列 | 第2列 | 第3列 | 第4列 | 第5列 | +| ------- | ------- | ------- | ------- | ------- | +| 72.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | +| 0.0000 | 64.0000 | 0.0000 | 0.0000 | 0.0000 | +| 16.0000 | 8.0000 | 0.0000 | 0.0000 | 0.0000 | +| 0.0000 | 0.0000 | 56.0000 | 16.0000 | 32.0000 | +| 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | +| 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | + +MAtrix **B**： + +| 第1列 | 第2列 | 第3列 | 第4列 | 第5列 | 第6列 | +| ------- | ------- | ------- | ------- | ------ | ------ | +| 72.0000 | 0.0000 | 16.0000 | 0.0000 | 0.0000 | 0.0000 | +| 0.0000 | 64.0000 | 8.0000 | 0.0000 | 0.0000 | 0.0000 | +| 0.0000 | 0.0000 | 0.0000 | 56.0000 | 0.0000 | 0.0000 | +| 0.0000 | 0.0000 | 0.0000 | 16.0000 | 0.0000 | 0.0000 | +| 0.0000 | 0.0000 | 0.0000 | 32.0000 | 0.0000 | 0.0000 | + +To + +| 第1列 | 第2列 | 第3列 | 第4列 | 第5列 | 第6列 | +| --------- | --------- | --------- | --------- | ------ | ------ | +| 5184.0000 | 0.0000 | 1152.0000 | 0.0000 | 0.0000 | 0.0000 | +| 0.0000 | 4096.0000 | 512.0000 | 0.0000 | 0.0000 | 0.0000 | +| 1152.0000 | 512.0000 | 320.0000 | 0.0000 | 0.0000 | 0.0000 | +| 0.0000 | 0.0000 | 0.0000 | 4416.0000 | 0.0000 | 0.0000 | +| 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | +| 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | + +## Demo : mat.flatten + +double* flatten(Matrix mid1) + +| 1 | 2 | 3 | +| :--: | :--: | :--: | +| 2 | 4 | 6 | +| 7 | 8 | 9 | + +​ To + +| 1 | 2 | 3 | 2 | 4 | 6 | 7 | 8 | 9 | +| ---- | ---- | ---- | ---- | ---- | ---- | ---- | ---- | :----------------- | +| | | | | | | | | Like numpy.flatten | + +## Demo : apply nearly mat + +​ Matrix appply(Matrix mid1,Matrix mid2,int axis = 0) + +> if axis=0 : + +| 0 | 7 | 2 | +| ---- | ---- | ---- | +| 0 | 3 | 1 | +| 0 | 0 | 0 | +| 0 | 0 | 11 | +| 0 | 7 | 2 | +| 0 | 3 | 1 | +| 0 | 0 | 0 | +| 0 | 0 | 11 | +------ + +> axis = 1: + +| 0 | 7 | 2 | 0 | 7 | 2 | +| ---- | ---- | ---- | ---- | ---- | ---- | +| 0 | 3 | 1 | 0 | 3 | 1 | +| 0 | 0 | 0 | 0 | 0 | 0 | +| 0 | 0 | 11 | 0 | 0 | 11 | + + + +- [x] read_csv + +- [x] return a matrix + + CSV head : + + | -0.017612 | 14.053064 | 0 | + | --------- | --------- | ---- | + | -1.395634 | 4.662541 | 1 | + | -0.752157 | 6.53862 | 0 | + | -1.322371 | 7.152853 | 0 | + | 0.423363 | 11.054677 | 0 | + | 0.406704 | 7.067335 | 1 | + + Get: + + ![](./picture/WX20191119-105411@2x.png) + + + + ## Test demo: + +```c +#include +#include +#include +#include +#include +#include +#include"./matrix/matrix_def.h" +#include"./matrix/matrix_pro.h" +#include"./welcome/score_wel.cpp" +#include"./logistic/logistic_def.h" +#include"./file_pro/data_read.h" +using namespace std; +clock_t start, stop; +double duration; +int main() +{ + welcome(); + string path = "./new_data2.csv"; + Matrix data = read_csv(path); + Matrix bais = CreateMatrix(data.row,1); + data = appply(data,bais,1); + Matrix y = iloc(data,0,0,3,4); + Matrix x_1 = iloc(data,0,0,0,3); + Matrix x_2 = get_T(x_1); + double alpha = 0.002; + int max_epoch = 100; + Matrix weight = CreateMatrix(3,1); + change_va(weight,0,0,1); + change_va(weight,1,0,1); + change_va(weight,2,0,1); + int epoch = 0; + for(epoch = 0;epoch<=max_epoch;epoch++) + { + cout<<"-----------split-line-----------"< 1. Matrix'element is default 1 +> 2. Dynamically allocate memory to prevent matrix from being too large +> 3. To save memory and delete later, use pointer to open up array space temporarily +> 4. if free please delete(matrix); +> 5. Api design like numpy or pandas +> 6. Talking is cheap u can get the code +> 7. welcome 🏃watched and star. +> + +------ + + + +
+ + + + 个人小站:[极度空间](likedge.top) + +作者邮箱:zk@likedge.top | edge@ibooker.org.cn + + QQ:2533524298 \ No newline at end of file diff --git a/a.csv b/a.csv new file mode 100644 index 0000000..46baf02 --- /dev/null +++ b/a.csv @@ -0,0 +1,2079 @@ +./ +0, +0, +./ +0, +0, +./ +0, +0, +./ +0, +0, +./ +0, +0, +./ +0, +0, +./ +0, +0, +./ +0, +0, +./ +0, +0, +./ +0, +0, +./ +0, +0, +./ +0, +0, +./ +0, +0, +./ +0, +0, +./ +0, +0, +./ +0, +0, +./ +0, +0, +./ +0, +0, +./ +0, +0, +./ +0, +0, +./ +0, +0, +./ +0, +0, +./ +0, +0, +./ +0, +0, +./ +0, +0, +./ +0, +0, +./ +0, +0, +./ +0, +0, +./ +0, +0, +./ +0, +0, +./ +0, +0, +./ +0, +0, +./ +0, +0, +./ +0, +0, +./ +0, +0, +./ +0, +0, +./ +0, +0, +./ +0, +0, +./ +0, +0, +./ +0, +0, +./ +0, +0, +./ +0, +0, +./ +0, +0, +./ +0, +0, +./ +0, +0, +./ +0, +0, +./ +0, +0, +./ +0, +0, +./ +0, +0, +./ +0, +0, +./ +0, +0, +./ +0, +0, +./ +0, +0, +./ +0, +0, +./ +0, +0, +./ +0, +0, +./ +0, +0, +./ +0, +0, +./ +0, +0, +./ +0, +0, +./ +0, +0, +./ +0, +0, +./ +0, +0, +./ 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b/autodiff/dor.h new file mode 100755 index 0000000..cfff375 --- /dev/null +++ b/autodiff/dor.h @@ -0,0 +1,16 @@ +#ifndef DYADIC_OPERATION_RESULT +#define DYADIC_OPERATION_RESULT + +struct DyadicOperationResult { + double value; + double left_grad; + double right_grad; + + DyadicOperationResult(double value, double left_grad, double right_grad){ + this->value = value; + this->left_grad = left_grad; + this->right_grad = right_grad; + } +}; + +#endif /* end of include guard: DYADIC_OPERATION_RESULT */ diff --git a/autodiff/graph.h b/autodiff/graph.h new file mode 100755 index 0000000..441ccf8 --- /dev/null +++ b/autodiff/graph.h @@ -0,0 +1,26 @@ +#ifndef GRAPH_H +#define GRAPH_H + +#include +#include +#include + +class Graph { + private: + std::map > > nodes; + static Graph* instance; + Graph(); + + public: + static long int uid_counter; + static long int uid(); + static Graph* getInstance(); + + void connect(const long int& uid, const std::pair& edge); + std::vector > get(const long int& uid) const; + bool has(const long int& uid) const; + + void new_recording(); +}; + +#endif /* end of include guard: GRAPH_H */ diff --git a/autodiff/mor.h b/autodiff/mor.h new file mode 100755 index 0000000..b2fe98b --- /dev/null +++ b/autodiff/mor.h @@ -0,0 +1,14 @@ +#ifndef MONADIC_OPERATION_RESULT +#define MONADIC_OPERATION_RESULT + +struct MonadicOperationResult { + double value; + double grad; + + MonadicOperationResult(double value, double grad){ + this->value = value; + this->grad = grad; + } +}; + +#endif /* end of include guard: MONADIC_OPERATION_RESULT */ diff --git a/autodiff/node.h b/autodiff/node.h new file mode 100755 index 0000000..34c1330 --- /dev/null +++ b/autodiff/node.h @@ -0,0 +1,72 @@ +#ifndef NODE_H +#define NODE_H + +#include +#include + +#include "graph.h" +#include "mor.h" +#include "dor.h" +#include "por.h" + +class Node { + private: + double value; + long int uid; + + double gradient_recursive(Graph* graph, const long int& current_uid, const long int& stop_uid) const; + + public: + Node(const double& value=0); + Node(const Node& node); + + static Node monadic_operation(const Node& n, MonadicOperationResult (*)(const double&)); + static Node dyadic_operation(const Node& l, const Node& r, DyadicOperationResult (*)(const double&, const double&)); + static Node polyadic_operation(const std::vector& nodes, PolyadicOperationResult (*)(const std::vector&)); + + double gradient(const Node& node) const; + std::vector gradient(const std::vector& nodes) const; + std::vector > gradient(const std::vector >& nodes) const; + + friend Node operator+(const Node& l, const Node& r); + friend Node operator-(const Node& l, const Node& r); + friend Node operator*(const Node& l, const Node& r); + friend Node operator/(const Node& l, const Node& r); + + Node& operator+=(const Node& r); + Node& operator-=(const Node& r); + Node& operator*=(const Node& r); + Node& operator/=(const Node& r); + + friend bool operator==(const Node& l, const Node& r); + friend bool operator<(const Node& l, const Node& r); + friend bool operator>(const Node& l, const Node& r); + friend bool operator<=(const Node& l, const Node& r); + friend bool operator>=(const Node& l, const Node& r); + + friend Node sin(const Node& x); + friend Node cos(const Node& x); + friend Node tan(const Node& x); + friend Node sinh(const Node& x); + friend Node cosh(const Node& x); + friend Node tanh(const Node& x); + friend Node asin(const Node& x); + friend Node acos(const Node& x); + friend Node atan(const Node& x); + + friend Node log(const Node& x, const Node& base); + friend Node log10(const Node& x); + friend Node ln(const Node& x); + + friend Node pow(const Node& x, const Node& p); + friend Node exp(const Node& x); + friend Node sqrt(const Node& x); + + friend Node abs(const Node& x); + friend Node min(const Node& l, const Node& r); + friend Node max(const Node& l, const Node& r); + + friend std::ostream& operator<<(std::ostream& os, const Node& node); +}; + +#endif /* end of include guard: NODE_H */ diff --git a/autodiff/por.h b/autodiff/por.h new file mode 100755 index 0000000..6eedd50 --- /dev/null +++ b/autodiff/por.h @@ -0,0 +1,16 @@ +#ifndef POLYADIC_OPERATION_RESULT +#define POLYADIC_OPERATION_RESULT + +#include + +struct PolyadicOperationResult { + double value; + std::vector gradients; + + PolyadicOperationResult(double value, const std::vector& gradients){ + this->value = value; + this->gradients = gradients; + } +}; + +#endif /* end of include guard: POLYADIC_OPERATION_RESULT */ diff --git a/autodiff/vectmath.h b/autodiff/vectmath.h new file mode 100755 index 0000000..7426398 --- /dev/null +++ b/autodiff/vectmath.h @@ -0,0 +1,99 @@ +#ifndef VECTMATH +#define VECTMATH + +#include +#include +#include +#include +#include + +// dot product +template +std::vector > dot(const std::vector >& a, const std::vector >& b){ + assert(a[0].size()==b.size()); + + T w=0; + std::vector > result(a.size(), std::vector(b[0].size())); + for (int i=0 ; i +std::vector& operator-=(std::vector& u, const std::vector& v){ + assert(u.size()==v.size()); + for(size_t i=0 ; i +std::vector operator+(const std::vector& u, const std::vector& v){ + assert(u.size()==v.size()); + std::vector w(u.size()); + for(size_t i=0 ; i +std::vector operator*(const S& s, const std::vector& u){ + std::vector result(u.size()); + for(size_t i=0 ; i +std::vector& operator>>(U (*fun)(U&), std::vector& u){ + std::transform(u.begin(), u.end(), u.begin(), fun); + return u; +} + +template +std::vector& operator>>(S (*fun)(S&), std::vector& u){ + for(auto& v : u){ + fun >> v; + } + return u; +} + +template +std::vector& operator>>(U (*fun)(), std::vector& u){ + for(auto& e : u){ + e = fun(); + } + return u; +} + +template +std::vector& operator>>(S (*fun)(), std::vector& u){ + for(auto& v : u){ + fun >> v; + } + return u; +} + +template +std::ostream& operator<<(std::ostream& os, const std::vector& u){ + os << "["; + for(size_t i=0 ; i +#include +#include +#include +#include +#include +#include "./autodiff/node.h" +#include"./matrix/matrix_def.h" +#include"./matrix/matrix_pro.h" +#include"./welcome/score_wel.cpp" +#include"./logistic/logistic_def.h" +#include"./file_pro/data_read.h" +#include"./grad_edge/matrix_grad.h" +using namespace std; +clock_t start, stop; +double duration; +int main() +{ + welcome(); + conv_test(CreateRandMat(5,6),3,4,1,2,0,0); + return 0; + +} \ No newline at end of file diff --git a/data/data.csv b/data/data.csv new file mode 100644 index 0000000..defba2f --- /dev/null +++ b/data/data.csv @@ -0,0 +1,1800 @@ +-0.017612,14.053064,0 +-1.395634,4.662541,1 +-0.752157,6.53862,0 +-1.322371,7.152853,0 +0.423363,11.054677,0 +0.406704,7.067335,1 +0.667394,12.741452,0 +-2.46015,6.866805,1 +0.569411,9.548755,0 +-0.026632,10.427743,0 +0.850433,6.920334,1 +1.347183,13.1755,0 +1.176813,3.16702,1 +-1.781871,9.097953,0 +-0.566606,5.749003,1 +0.931635,1.589505,1 +-0.024205,6.151823,1 +-0.036453,2.690988,1 +-0.196949,0.444165,1 +1.014459,5.754399,1 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b/data_struct/data_struct_pro.c new file mode 100644 index 0000000..b99e9fb --- /dev/null +++ b/data_struct/data_struct_pro.c @@ -0,0 +1,107 @@ +/* +███████╗██████╗ ██████╗ ███████╗ ███████╗███╗ ██╗ ██████╗ ██╗███╗ ██╗███████╗ +██╔════╝██╔══██╗██╔════╝ ██╔════╝ ██╔════╝████╗ ██║██╔════╝ ██║████╗ ██║██╔════╝ +█████╗ ██║ ██║██║ ███╗█████╗ █████╗ ██╔██╗ ██║██║ ███╗██║██╔██╗ ██║█████╗ +██╔══╝ ██║ ██║██║ ██║██╔══╝ ██╔══╝ ██║╚██╗██║██║ ██║██║██║╚██╗██║██╔══╝ +███████╗██████╔╝╚██████╔╝███████╗ ███████╗██║ ╚████║╚██████╔╝██║██║ ╚████║███████╗ +╚══════╝╚═════╝ ╚═════╝ ╚══════╝ ╚══════╝╚═╝ ╚═══╝ ╚═════╝ ╚═╝╚═╝ ╚═══╝╚══════╝ +Author：Edge +Web：likedge.top +Date：20201213 +*/ +#include "data_struct_pro.h" +#define random(x) (rand()%x) +link_list::link_list() +{ + cout<<"test"<len=n; + this->link_list_head =(lnode*)malloc(sizeof(lnode)); + lnode *node1=(lnode*)malloc(sizeof(lnode)); + lnode *p= this->link_list_head; + // this->link_list_head =new lnode(1,0); + for(int index_link_node=0;index_link_nodenext_index=node1; + p->data=index_link_node; + cout<data<next_index<next_index; + // cout<<"Node:"<link_list_head->next_index<data<next_index; + } +} +//insert element for what u input,in this index +void insert_element_ll(int index_toinsert,link_list ll_toinsert,int to_insertele) +{ + lnode *insert_p=ll_toinsert.link_list_head; + for(int index_move = 0;index_movenext_index; + insert_p->next_index=node1; + insert_p->next_index->data=to_insertele; + node1->next_index=old_next_index; + + } + insert_p=insert_p->next_index; + } +} +//delete the element from where you index +void dele_element_ll(int index_todele,link_list ll_todele) +{ + lnode *dele_p=ll_todele.link_list_head; + for(int index_move=0;index_movenext_index; + dele_p->next_index=old_index_to_dele->next_index; + } + dele_p=dele_p->next_index; + } + +} +void insert_end_ll(int to_insert_end,link_list ll_toinsert_end) +{ + + lnode *end_p=ll_toinsert_end.link_list_head; + for(int index_move_toend=0;index_move_toend<=ll_toinsert_end.len;index_move_toend++) + { + cout<data=to_insert_end; + cout<next_index=node_to_insert_end; + } + end_p=end_p->next_index; + } + ll_toinsert_end.len+=1; + cout< +#include +#include +#include +#include +#include +#include"./autodiff/node.h" +#include"./matrix/matrix_def.h" +#include"./matrix/matrix_pro.h" +#include"./welcome/score_wel.cpp" +#include"./logistic/logistic_def.h" +#include"./file_pro/data_read.h" +#include"./grad_edge/matrix_grad.h" +#include"./data_struct/data_struct_pro.h" +#include"./data_struct/data_struct_pro.c" +using namespace std; +int a[101],n;//定义全局变量，这两个变量需要在子函数中使用 +int i,j,t; +//quick_sort +void quicksort(int left,int right) + { + int i,j,t,temp; + if(left>right) + return; + + temp=a[left]; //temp中存的就是基准数 + i=left; + j=right; + while(i!=j) + { + //顺序很重要，要先从右边开始找 + while(a[j]>=temp && i +#include +#include +#include +#include +using namespace std; +string data; +double str2double(char *src) +{ + double ret = 0,sign = 1; + char *p = src; + if(*p == '+'){sign = 1;p ++;} + else if(*p == '-'){sign = -1; p ++; } + while(*p && (*p != '.')) + { + ret*=10; + ret += (*p) - '0'; + p++; + } + if(*p == '.') + { + double step = 0.1; + p++; + while(*p) + { + ret+=step*((*p)-'0'); + step/=10; + p++; + } + } + return ret*sign; +} + +str_Matrix read_file(string &file_path) +{ + int count_rows = 0,count_col = 0; + ifstream infile; + infile.open(file_path); + while(!infile.eof()) + { + count_col = 0; + count_rows+=1; + infile >> data; + int iSize = data.size(); + int flag_if = 1; + for(int i = 0;i < iSize; i++) + { + if(data[i]==',') + { + count_col++; + } + } + } + cout<> data; + string base = ""; + string added =""; + string added2 = ""; + string base2 = ""; + int iSize = data.size(); + int flag_if = 1; + int count_times = 0; + int count_times2 = 0; + for(int i = 0;i < iSize; i++) + { + //cout<> data; + int iSize = data.size(); + int flag_if = 1; + for(int i = 0;i < iSize; i++) + { + if(data[i]==',') + { + count_col++; + } + } + } + Matrix data_ma = CreateMatrix(count_rows,count_col+1); + ifstream infile2; + infile2.open(file_path); + int next_flag = 0; + while(!infile2.eof()) + { + infile2 >> data; + string base = ""; + string added =""; + string added2 = ""; + string base2 = ""; + int iSize = data.size(); + int flag_if = 1; + int count_times = 0; + int count_times2 = 0; + for(int i = 0;i < iSize; i++) + { + if(data[i]!=',') + { + added+=data[i]; + } + else if(data[i]==',') + { + count_times+=1; + base = added; + char *result = (char*)base.data(); + data_ma.matrix[next_flag][count_times-1] = str2double(result); + added =""; + base = ""; + } + if(count_times==count_col) + { + added2+=data[i+1]; + base2 = added2; + char *result2 = (char*)base2.data(); + data_ma.matrix[next_flag][count_times] = str2double(result2); + } + } + next_flag+=1; + } + return data_ma; +} +int save_txt(Matrix mid1,string path = "./",string delimiter = ",",string header="./") +{ + int index_x,index_y; + ofstream fout(path,ios::app); + fout< +#include +#include +#include +#include +#include +#include"./autodiff/node.h" +#include"../matrix/matrix_def.h" +#include"../matrix/matrix_pro.h" +using namespace std; +float sigmoid(float x){ + return 1/(1+exp(x)); +} +Node sigmoid(Node z){ + Node sigmoid = 1/(1+(1/exp(z))); + return sigmoid; +} +struct edge_network +{ + edge_network(int input, int num_neuron){ + } + Matrix forward(Matrix data,Matrix weights,Matrix bais) + { + // cout<<"data: "; + // cout_mat(data); + // cout<<"weights: "<>n(o!B*DaTHn4*F-3L-ut1Ox<%tc-**1O#jn1O(J6{3~D&%tz8O2nb|Z zb8&G+S#fbvMF(3`b1M@F2$`@%4LFd>Aasd z;u>$pAik;$$ICe?=|Y@S-c{d*qE83@dW*e>Ap(I|*ntf?zjdJFXJ*D1!E1R@S=I@d zR%C9bZEVYWsrW{NK6D2`YL9LPzxgN-dIRa3e41D71raKwXe&seU)&Q<%JsPuhAfHR zJ_$dW);<_tqsR(#gBSe-!uQ?A*+)%?PxT^#CB9j(?lra|hx8bsR1mwL$xt^V+@L}! z$cST;x!;Fn6WI;ihSMC7q~nRF3+PRwtIvGHbSMNdk8X`V3NM_sQ?Y2U;dY~b+Z(h&mz97GMzky#fc+JFc)IuuTn=?@A?P71#n7)6+8 ze;N2qaUZf`O)^^F`w!w;S5vSbi%pSKiFsGqdfZ77H@j946O%vEYO%Y)aIT+xyD%(o 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root/obj/graph.o examples/obj/ann.o +OBJS_GRADIENT = root/obj/node.o root/obj/graph.o examples/obj/gradient.o +OBJS_SPEED = root/obj/node.o root/obj/graph.o examples/obj/speed.o +OBJS_SIMPLE = root/obj/node.o root/obj/graph.o examples/obj/simple.o + +all : gradient_descent ann gradient speed simple + +gradient_descent : $(BIN) root/include/vectmath.h root/include/mor.h root/include/dor.h root/include/por.h + $(MAKE) -C examples obj obj/gradient_descent.o + $(MAKE) -C root obj obj/node.o obj/graph.o + $(CXX) -o $(BIN)/gradient_descent $(OBJS_GRADIENT_DESCENT) $(LIBS) + +ann : $(BIN) root/include/vectmath.h root/include/mor.h root/include/dor.h root/include/por.h + $(MAKE) -C examples obj obj/ann.o + $(MAKE) -C root obj obj/node.o obj/graph.o + $(CXX) -o $(BIN)/ann $(OBJS_ANN) $(LIBS) + +gradient : $(BIN) root/include/vectmath.h root/include/mor.h root/include/dor.h root/include/por.h + $(MAKE) -C examples obj obj/gradient.o + $(MAKE) -C root obj obj/node.o obj/graph.o + $(CXX) -o $(BIN)/gradient $(OBJS_GRADIENT) $(LIBS) + +speed : $(BIN) root/include/vectmath.h root/include/mor.h root/include/dor.h root/include/por.h + $(MAKE) -C examples obj obj/speed.o + $(MAKE) -C root obj obj/node.o obj/graph.o + $(CXX) -o $(BIN)/speed $(OBJS_SPEED) $(LIBS) + +simple : $(BIN) root/include/mor.h root/include/dor.h root/include/por.h + $(MAKE) -C examples obj obj/simple.o + $(MAKE) -C root obj obj/node.o obj/graph.o + $(CXX) -o $(BIN)/simple $(OBJS_SIMPLE) $(LIBS) + +$(BIN) : + if [ ! -d $(BIN) ]; then mkdir $(BIN); fi + +$(LIB) : + if [ ! -d $(LIB) ]; then mkdir $(LIB); fi + +clean : + $(MAKE) -C root clean + $(MAKE) -C examples clean + if [ -d $(BIN) ]; then rm $(BIN) -r; fi + +install : $(LIB) + ar rcs $(LIB)/lib$(LIB_NAME).a root/obj/graph.o root/obj/node.o + if [ ! -d /usr/local/include/$(LIB_NAME) ]; then sudo mkdir /usr/local/include/$(LIB_NAME); fi + sudo cp $(LIB)/lib$(LIB_NAME).a /usr/local/lib + sudo cp root/include/*.h /usr/local/include/$(LIB_NAME) + +.PHONY : 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+#include "../../root/include/node.h" + +typedef std::vector Vector; +typedef std::vector Matrix; + +Node random_number(){ + return rand()/(double)RAND_MAX; +} + +Node tan_h(Node& x){ + return (1-exp(-2*x))/(1+exp(-2*x)); +} + +Node mean_square_error(Vector& y_true, Vector& y_pred){ + Node loss; + for(size_t i=0 ; iactivation = activation; + this->input_shape = input; + this->output_shape = output; + weights.resize(input, Vector(output)); + bias.resize(1, Vector(output)); + random_number >> weights; + random_number >> bias; + } + + Matrix forward(Matrix& previous){ + Matrix output = dot(previous, weights) + bias; + output = activation >> output; + return output; + } + + void backward(Node& loss, const float& learning_rate){ + weights -= learning_rate*loss.gradient(weights); + bias -= learning_rate*loss.gradient(bias); + } +}; + +struct Network { + std::vector layers; + int input_shape; + Graph* graph; + + Network(){ + graph = Graph::getInstance(); + } + + void input_layer(int input_shape){ + this->input_shape = input_shape; + } + + void add(int output_shape, Node (*activation)(Node&)){ + int input = layers.empty()?input_shape:layers.back().output_shape; + layers.push_back(Layer(input, output_shape, activation)); + } + + Matrix run(Matrix& input){ + Matrix output(input.size()); + for(size_t j=0 ; jnew_recording(); + } + } + std::cout << std::endl; + } +}; + +int main(int argc, char const *argv[]) { + srand(time(NULL)); + + Matrix input = {{0,0},{0,1},{1,0},{1,1}}; + Matrix output = {{0},{1},{1},{0}}; + + Network network; + network.input_layer(2); + network.add(3, tan_h); + network.add(1, tan_h); + network.fit(input, output, mean_square_error, 500, 0.1); + + Matrix pred = network.run(input); + std::cout << pred << std::endl; + return 0; +} diff --git a/install_diff/examples/src/gradient.cpp b/install_diff/examples/src/gradient.cpp new file mode 100644 index 0000000..4b131de --- /dev/null +++ b/install_diff/examples/src/gradient.cpp @@ -0,0 +1,15 @@ +#include + +#include "../../root/include/vectmath.h" +#include "../../root/include/node.h" + +Node function(std::vector x){ + return pow(x[0]-x[1], 2) + x[0]*x[1]*x[2]; // (x-y)^2 + x*y*z +} + +int main(int argc, char const *argv[]) { + std::vector x = {5,6,7}; + Node f = function(x); + std::cout << "grad(f) = " << f.gradient(x) << std::endl; + return 0; +} diff --git a/install_diff/examples/src/gradient_descent.cpp b/install_diff/examples/src/gradient_descent.cpp new file mode 100644 index 0000000..019f7e6 --- /dev/null +++ b/install_diff/examples/src/gradient_descent.cpp @@ -0,0 +1,27 @@ +#include + +#include "../../root/include/vectmath.h" +#include "../../root/include/node.h" + +Node function(std::vector& x){ + return pow(x[0], 2) + pow(x[1], 2); // x^2 + y^2 +} + +int main(int argc, char const *argv[]) { + Graph* graph = Graph::getInstance(); + + std::vector x = {50, 50}; + Node f; + + int epochs = 30; + float learning_rate = 0.1; + for(size_t i=0 ; inew_recording(); + } + + std::cout << 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+ std::cout << "f(x,y) = x*y + sin(x)" << std::endl; + std::cout << "f(" << x << "," << y << ") = " << f << std::endl; + std::cout << "∂f/∂x = " << f.gradient(x) << std::endl; + std::cout << "∂f/∂y = " << f.gradient(y) << std::endl; + return 0; +} diff --git a/install_diff/examples/src/speed.cpp b/install_diff/examples/src/speed.cpp new file mode 100644 index 0000000..fe58f78 --- /dev/null +++ b/install_diff/examples/src/speed.cpp @@ -0,0 +1,51 @@ +#include +#include +#include +#include +#include + +#include "../../root/include/vectmath.h" +#include "../../root/include/node.h" + +template +std::vector > get_random_matrix(const int& height, const int& width, T t){ + std::vector > mat(height, std::vector(width)); + for(auto& v : mat){ + for(auto& e : v){ + e = rand()/(double)RAND_MAX; + } + } + return mat; +} + +int main(int argc, char const *argv[]) { + srand(time(0)); + + int size = 30; + std::vector > a = get_random_matrix(size, size, double()); + std::vector > b = get_random_matrix(size, size, double()); + std::vector > c = get_random_matrix(size, size, Node()); + std::vector > d = get_random_matrix(size, size, Node()); + + std::cout << std::fixed; + std::cout << std::setprecision(10); + + std::cout << "Running with double...\t"; + std::cout.flush(); + auto start = std::chrono::high_resolution_clock::now(); + std::vector > ab = dot(a, b); + auto finish = std::chrono::high_resolution_clock::now(); + std::chrono::duration elapsed = finish - start; + std::cout << "Elapsed time: " << elapsed.count() << " s" << std::endl; + + std::cout << "Running with Node...\t"; + std::cout.flush(); + start = std::chrono::high_resolution_clock::now(); + std::vector > cd = dot(c, d); + finish = std::chrono::high_resolution_clock::now(); + elapsed = finish - start; + std::cout << "Elapsed time: " << elapsed.count() << " s" << std::endl; + + std::cout << "Yet to be improved..." << std::endl; + return 0; +} diff --git a/install_diff/lib/libautodiff.a 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= $(ODIR)/graph.o $(ODIR)/node.o + +all : $(ODIR) $(OBJS) + +$(ODIR)/graph.o : src/graph.cpp include/graph.h + $(CXX) -c $< -o $@ $(CXXFLAGS) + +$(ODIR)/node.o : src/node.cpp include/node.h + $(CXX) -c $< -o $@ $(CXXFLAGS) + +$(ODIR) : + if [ ! -d $(ODIR) ]; then mkdir $(ODIR); fi + +clean : + if [ -d $(ODIR) ]; then rm $(ODIR) -r; fi + +.PHONY : all +.PHONY : clean + diff --git a/install_diff/root/include/dor.h b/install_diff/root/include/dor.h new file mode 100644 index 0000000..cfff375 --- /dev/null +++ b/install_diff/root/include/dor.h @@ -0,0 +1,16 @@ +#ifndef DYADIC_OPERATION_RESULT +#define DYADIC_OPERATION_RESULT + +struct DyadicOperationResult { + double value; + double left_grad; + double right_grad; + + DyadicOperationResult(double value, double left_grad, double right_grad){ + this->value = value; + this->left_grad = left_grad; + this->right_grad = right_grad; + } +}; + +#endif /* end of include guard: DYADIC_OPERATION_RESULT */ diff --git a/install_diff/root/include/graph.h b/install_diff/root/include/graph.h new file mode 100644 index 0000000..441ccf8 --- /dev/null +++ b/install_diff/root/include/graph.h @@ -0,0 +1,26 @@ +#ifndef GRAPH_H +#define GRAPH_H + +#include +#include +#include + +class Graph { + private: + std::map > > nodes; + static Graph* instance; + Graph(); + + public: + static long int uid_counter; + static long int uid(); + static Graph* getInstance(); + + void connect(const long int& uid, const std::pair& edge); + std::vector > get(const long int& uid) const; + bool has(const long int& uid) const; + + void new_recording(); +}; + +#endif /* end of include guard: GRAPH_H */ diff --git a/install_diff/root/include/mor.h b/install_diff/root/include/mor.h new file mode 100644 index 0000000..b2fe98b --- /dev/null +++ b/install_diff/root/include/mor.h @@ -0,0 +1,14 @@ +#ifndef MONADIC_OPERATION_RESULT +#define MONADIC_OPERATION_RESULT + +struct MonadicOperationResult { + double value; + double grad; + + MonadicOperationResult(double value, double grad){ + this->value = value; + this->grad = grad; + } +}; + +#endif /* end of include guard: MONADIC_OPERATION_RESULT */ diff --git a/install_diff/root/include/node.h b/install_diff/root/include/node.h new file mode 100644 index 0000000..34c1330 --- /dev/null +++ b/install_diff/root/include/node.h @@ -0,0 +1,72 @@ +#ifndef NODE_H +#define NODE_H + +#include +#include + +#include "graph.h" +#include "mor.h" +#include "dor.h" +#include "por.h" + +class Node { + private: + double value; + long int uid; + + double gradient_recursive(Graph* graph, const long int& current_uid, const long int& stop_uid) const; + + public: + Node(const double& value=0); + Node(const Node& node); + + static Node monadic_operation(const Node& n, MonadicOperationResult (*)(const double&)); + static Node dyadic_operation(const Node& l, const Node& r, DyadicOperationResult (*)(const double&, const double&)); + static Node polyadic_operation(const std::vector& nodes, PolyadicOperationResult (*)(const std::vector&)); + + double gradient(const Node& node) const; + std::vector gradient(const std::vector& nodes) const; + std::vector > gradient(const std::vector >& nodes) const; + + friend Node operator+(const Node& l, const Node& r); + friend Node operator-(const Node& l, const Node& r); + friend Node operator*(const Node& l, const Node& r); + friend Node operator/(const Node& l, const Node& r); + + Node& operator+=(const Node& r); + Node& operator-=(const Node& r); + Node& operator*=(const Node& r); + Node& operator/=(const Node& r); + + friend bool operator==(const Node& l, const Node& r); + friend bool operator<(const Node& l, const Node& r); + friend bool operator>(const Node& l, const Node& r); + friend bool operator<=(const Node& l, const Node& r); + friend bool operator>=(const Node& l, const Node& r); + + friend Node sin(const Node& x); + friend Node cos(const Node& x); + friend Node tan(const Node& x); + friend Node sinh(const Node& x); + friend Node cosh(const Node& x); + friend Node tanh(const Node& x); + friend Node asin(const Node& x); + friend Node acos(const Node& x); + friend Node atan(const Node& x); + + friend Node log(const Node& x, const Node& base); + friend Node log10(const Node& x); + friend Node ln(const Node& x); + + friend Node pow(const Node& x, const Node& p); + friend Node exp(const Node& x); + friend Node sqrt(const Node& x); + + friend Node abs(const Node& x); + friend Node min(const Node& l, const Node& r); + friend Node max(const Node& l, const Node& r); + + friend std::ostream& operator<<(std::ostream& os, const Node& node); +}; + +#endif /* end of include guard: NODE_H */ diff --git a/install_diff/root/include/por.h b/install_diff/root/include/por.h new file mode 100644 index 0000000..6eedd50 --- /dev/null +++ b/install_diff/root/include/por.h @@ -0,0 +1,16 @@ +#ifndef POLYADIC_OPERATION_RESULT +#define POLYADIC_OPERATION_RESULT + +#include + +struct PolyadicOperationResult { + double value; + std::vector gradients; + + PolyadicOperationResult(double value, const std::vector& gradients){ + this->value = value; + this->gradients = gradients; + } +}; + +#endif /* end of include guard: POLYADIC_OPERATION_RESULT */ diff --git a/install_diff/root/include/vectmath.h b/install_diff/root/include/vectmath.h new file mode 100644 index 0000000..7426398 --- /dev/null +++ b/install_diff/root/include/vectmath.h @@ -0,0 +1,99 @@ +#ifndef VECTMATH +#define VECTMATH + +#include +#include +#include +#include +#include + +// dot product +template +std::vector > dot(const std::vector >& a, const std::vector >& b){ + assert(a[0].size()==b.size()); + + T w=0; + std::vector > result(a.size(), std::vector(b[0].size())); + for (int i=0 ; i +std::vector& operator-=(std::vector& u, const std::vector& v){ + assert(u.size()==v.size()); + for(size_t i=0 ; i +std::vector operator+(const std::vector& u, const std::vector& v){ + assert(u.size()==v.size()); + std::vector w(u.size()); + for(size_t i=0 ; i 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+std::vector > Graph::get(const long int& uid) const{ + return nodes.at(uid); +} + +bool Graph::has(const long int& uid) const{ + return nodes.find(uid)!=nodes.end(); +} + +void Graph::new_recording(){ + nodes.clear(); +} diff --git a/install_diff/root/src/node.cpp b/install_diff/root/src/node.cpp new file mode 100644 index 0000000..dab3e44 --- /dev/null +++ b/install_diff/root/src/node.cpp @@ -0,0 +1,275 @@ +#include "../include/node.h" + +Node::Node(const double& value) { + this->value = value; + this->uid = Graph::uid(); +} + +Node::Node(const Node& node){ + this->value = node.value; + this->uid = node.uid; +} + +double Node::gradient_recursive(Graph* graph, const long int& current_uid, const long int& stop_uid) const{ + if(current_uid==stop_uid){ + return 1.0; + } + + double sum=0.0; + if(graph->has(current_uid)){ + for(auto& pair : graph->get(current_uid)){ + sum += pair.first*gradient_recursive(graph, pair.second, stop_uid); + } + } + return sum; +} + +double Node::gradient(const Node& node) const{ + Graph* graph = Graph::getInstance(); + return gradient_recursive(graph, this->uid, node.uid); +} + +std::vector Node::gradient(const std::vector& nodes) const{ + Graph* graph = Graph::getInstance(); + std::vector grad(nodes.size()); + for(size_t i=0 ; iuid, nodes[i].uid); + } + return grad; +} + +std::vector > Node::gradient(const std::vector >& nodes) const{ + Graph* graph = Graph::getInstance(); + std::vector > grad(nodes.size()); + for(size_t i=0 ; iuid, nodes[i][j].uid); + } + } + return grad; +} + +Node Node::monadic_operation(const Node& n, MonadicOperationResult (*fun)(const double&)){ + MonadicOperationResult res = fun(n.value); + Node result(res.value); + Graph* graph = Graph::getInstance(); + graph->connect(result.uid, std::make_pair(res.grad, n.uid)); + return result; +} + +Node Node::dyadic_operation(const Node& left, const Node& right, DyadicOperationResult (*fun)(const double&, const double&)){ + DyadicOperationResult res = fun(left.value, right.value); + Node result(res.value); + Graph* graph = Graph::getInstance(); + graph->connect(result.uid, std::make_pair(res.left_grad, left.uid)); + graph->connect(result.uid, std::make_pair(res.right_grad, right.uid)); + return result; +} + +Node Node::polyadic_operation(const std::vector& nodes, PolyadicOperationResult (*fun)(const std::vector&)){ + std::vector values(nodes.size()); + for(size_t i=0 ; iconnect(result.uid, std::make_pair(res.gradients[i], nodes[i].uid)); + } + return result; +} + +Node operator+(const Node& left, const Node& right){ + return Node::dyadic_operation(left, right, [](const double& l, const double& r){ + return DyadicOperationResult(l+r, 1.0, 1.0); + }); +} + +Node operator-(const Node& left, const Node& right){ + return Node::dyadic_operation(left, right, [](const double& l, const double& r){ + return DyadicOperationResult(l-r, 1.0, -1.0); + }); +} + +Node operator*(const Node& left, const Node& right){ + return Node::dyadic_operation(left, right, [](const double& l, const double& r){ + return DyadicOperationResult(l*r, r, l); + }); +} + +Node operator/(const Node& left, const Node& right){ + return Node::dyadic_operation(left, right, [](const double& l, const double& r){ + return DyadicOperationResult(l/r, 1.0/r, -1.0*l/(r*r)); + }); +} + +Node& Node::operator+=(const Node& r){ + *this = *this + r; + return *this; +} + +Node& Node::operator-=(const Node& r){ + *this = *this - r; + return *this; +} + +Node& Node::operator*=(const Node& r){ + *this = *this * r; + return *this; +} + +Node& Node::operator/=(const Node& r){ + *this = *this / r; + return *this; +} + +bool operator==(const Node& left, const Node& right){ + return left.value==right.value; +} + +bool operator<(const Node& left, const Node& right){ + return left.value(const Node& left, const Node& right){ + return left.value>right.value; +} + +bool operator<=(const Node& left, const Node& right){ + return left.value<=right.value; +} + +bool operator>=(const Node& left, const Node& right){ + return left.value>=right.value; +} + +Node sin(const Node& x){ + return Node::monadic_operation(x, [](const double& n){ + return MonadicOperationResult(::sin(n), ::cos(n)); + }); +} + +Node cos(const Node& x){ + return Node::monadic_operation(x, [](const double& n){ + return MonadicOperationResult(::cos(n), -1.0*::sin(n)); + }); +} + +Node tan(const Node& x){ + return Node::monadic_operation(x, [](const double& n){ + return MonadicOperationResult(::tan(n), 1.0/::pow(::cos(n), 2)); + }); +} + +Node sinh(const Node& x){ + return Node::monadic_operation(x, [](const double& n){ + return MonadicOperationResult(::sinh(n), ::cosh(n)); + }); +} + +Node cosh(const Node& x){ + return Node::monadic_operation(x, [](const double& n){ + return MonadicOperationResult(::cosh(n), ::sinh(n)); + }); +} + +Node asin(const Node& x){ + return Node::monadic_operation(x, [](const double& n){ + return MonadicOperationResult(::asin(n), 1.0/(::sqrt(1-n*n))); + }); +} + +Node acos(const Node& x){ + return Node::monadic_operation(x, [](const double& n){ + return MonadicOperationResult(::acos(n), -1.0/(::sqrt(1-n*n))); + }); +} + +Node atan(const Node& x){ + return Node::monadic_operation(x, [](const double& n){ + return MonadicOperationResult(::atan(n), 1.0/(1+n*n)); + }); +} + +Node tanh(const Node& x){ + return Node::monadic_operation(x, [](const double& n){ + return MonadicOperationResult(::tanh(n), 1.0-::pow(::tanh(n), 2)); + }); +} + +Node log(const Node& x, const Node& base){ + return Node::dyadic_operation(x, base, [](const double& a, const double& b){ + return DyadicOperationResult(::log(a)/::log(b), 1.0/(a*::log(b)), -1.0*::log(a)/(b*::log(b))); + }); +} + +Node log10(const Node& x){ + return Node::monadic_operation(x, [](const double& n){ + return MonadicOperationResult(::log(n)/::log(10), 1.0/(n*::log(10))); + }); +} + +Node ln(const Node& x){ + return Node::monadic_operation(x, [](const double& n){ + return MonadicOperationResult(::log(n), 1.0/::log(n)); + }); +} + +Node pow(const Node& x, const Node& base){ + return Node::dyadic_operation(x, base, [](const double& a, const double& b){ + if(a<=0){ + return DyadicOperationResult(::pow(a,b), b*::pow(a,b-1), 0); + } + return DyadicOperationResult(::pow(a,b), b*::pow(a,b-1), ::log(a)*::pow(a,b)); + }); +} + +Node exp(const Node& x){ + return Node::monadic_operation(x, [](const double& n){ + return MonadicOperationResult(::exp(n), ::exp(n)); + }); +} + +Node sqrt(const Node& x){ + return Node::monadic_operation(x, [](const double& n){ + return MonadicOperationResult(::sqrt(n), 1.0/(2*::sqrt(n))); + }); +} + +Node abs(const Node& x){ + return Node::monadic_operation(x, [](const double& n){ + int sign = n==0 ? 0 : n/::abs(n); + return MonadicOperationResult(::abs(n), sign); + }); +} + +Node min(const Node& left, const Node& right){ + return Node::dyadic_operation(left, right, [](const double& a, const double& b){ + if(ab){ + return DyadicOperationResult(b, 0, 1); + } + return DyadicOperationResult(a, 0, 0); + }); +} + +Node max(const Node& left, const Node& right){ + return Node::dyadic_operation(left, right, [](const double& a, const double& b){ + if(a>b){ + return DyadicOperationResult(a, 1, 0); + } + if(a$tDv_E$Yde zpTN7~#joH&@gpb-f*-&y;Y%{@u1fbRi!bnJ(wBM3%&(`?91b4b9qT)m19)5nczNy1 zi_?jzyE(+0CE znx^@pl&)*AYS(bxkjZJm!$k0)dwRR;vNVWsZQ24e6M2`XQg2r@9}R};%x&)Ci+EY+ z_j^#c{N7RNBYoLZwLQ6bta_@ZXWZ;rnc(!joOzP9)po7eabx*7+}#3H3tMeT73xX7 z6V8s^iVaN3lB|VMEOh~0>S4L#1q7lzjG2BCOO={_C<}beT~ED)6`AKVy^z5Wws`8t sWx!l63W;k^ZXK5rPexXBTre!l#u|RdYM5rZup(pC@%M!0-FX9k0skWg`v3p{ literal 0 HcmV?d00001 diff --git a/logistic/log b/logistic/log new file mode 100755 index 0000000000000000000000000000000000000000..959d28500350072361efe4d0ceceff6bd9c6763c GIT binary patch literal 19992 zcmeHPeRLevb)VI)i5wedO>p8gAzlNfb|A1TTecKISYkaG#}W~iRg4odTCGOXHmeWz z!`Mkw1hP^MgE-2;ArR;}YL5?96Ot%BY4G7BLf8T+R0*PWi_+t!+s4q@9wk|fV-)J5 z{_dMMyR##?*e0}pRCE01y?ft%_uYHneP4H0e(9}Wz5PB(@^~ewr$mw@KT>9yB=z;I 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+███████╗██████╗ ██████╗ ███████╗ ███████╗███╗ ██╗ ██████╗ ██╗███╗ ██╗███████╗ +██╔════╝██╔══██╗██╔════╝ ██╔════╝ ██╔════╝████╗ ██║██╔════╝ ██║████╗ ██║██╔════╝ +█████╗ ██║ ██║██║ ███╗█████╗ █████╗ ██╔██╗ ██║██║ ███╗██║██╔██╗ ██║█████╗ +██╔══╝ ██║ ██║██║ ██║██╔══╝ ██╔══╝ ██║╚██╗██║██║ ██║██║██║╚██╗██║██╔══╝ +███████╗██████╔╝╚██████╔╝███████╗ ███████╗██║ ╚████║╚██████╔╝██║██║ ╚████║███████╗ +╚══════╝╚═════╝ ╚═════╝ ╚══════╝ ╚══════╝╚═╝ ╚═══╝ ╚═════╝ ╚═╝╚═╝ ╚═══╝╚══════╝ +Author：Edge +Web：likedge.top +Date：20200925 +*/ +double get_sigmoid(double temp) +{ +// cout<<"temp"< +#include +#include +#include +#include +#include +#include "./autodiff/node.h" +#include"./matrix/matrix_def.h" +#include"./matrix/matrix_pro.h" +#include"./welcome/score_wel.cpp" +#include"./logistic/logistic_def.h" +#include"./file_pro/data_read.h" +#include"./grad_edge/matrix_grad.h" +#include"./data_struct/data_struct_pro.h" +using namespace std; +clock_t start, stop; +double duration; +Node z=1; +Node t1 = 1,a13 = 1; +/*自定义的损失函数*/ +Node loss_act(Node t1,Node a13) +{ + Node loss = 0.5*(pow((t1-a13),2)); + return loss; +} +Node sigmoid_act(Node z) +{ +Node sigmoid_act = 1/(1+(1/exp(z))); +return sigmoid_act; +} +//loss +Node (*loss)(Node,Node) = loss_act; +Node (*act)(Node) = sigmoid_act; +int main() +{ + Matrix data_1 = ones(1,3); + Matrix data_2 = ones(3,1); + cout_mat(mul(data_1,data_2)); + welcome(); + //begin + cout<<"auto build on gcc"<+tts$2nxrE4h0wxqSc4cR0=k(}n7mPHCnj zaSQxqPaGM_9#0t~pB!4XK)M}4ftgckldXzZ^_!W=TG7i)*6aDASE*$xoqVmCIkmXO zTX}M=Qg8XC>XwzKR=1R@UZzs;8>P1S$=4gTq3H!4mP92ABnpHIwEU@+CoI{xY9u=> zfy5EiW{d`bt&bt$N$@joNm1+^v*~*&!|m zxfqd)QD@d!r@l6E3-x-v+)0@`Ntq6>N77PIpTgx@%~mBP zdHOS6*&B8GinZ26*>kyxJa#}mf3j940S`85ObHdQP>nuaJ;XkR;>p8P6@A>ZH>4G)$xkmCQ!PYk198**7gSwHO?fy6c#s`IgEO)#t^cSDd>Kb%*Gh*c9_s zSgIB22a=bL4SFCJCyJLckvOVPpSUUdkbWd~c$6PqPnU|i)YRy!RU^sC4X@yPIy6OV z>9e$HG&Kn;(jFhivXw4~<@D9bJ5eYXs*@2T9;g#zdf7y75|zZrq$s&2pQpU>yxE3&8^)fZQYT 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██║██╔════╝ +█████╗ ██║ ██║██║ ███╗█████╗ █████╗ ██╔██╗ ██║██║ ███╗██║██╔██╗ ██║█████╗ +██╔══╝ ██║ ██║██║ ██║██╔══╝ ██╔══╝ ██║╚██╗██║██║ ██║██║██║╚██╗██║██╔══╝ +███████╗██████╔╝╚██████╔╝███████╗ ███████╗██║ ╚████║╚██████╔╝██║██║ ╚████║███████╗ +╚══════╝╚═════╝ ╚═════╝ ╚══════╝ ╚══════╝╚═╝ ╚═══╝ ╚═════╝ ╚═╝╚═╝ ╚═══╝╚══════╝ +Author：Edge +Web：likedge.top +Date：20200925 +*/ +int main() diff --git a/matrix/matrix_def.h b/matrix/matrix_def.h new file mode 100644 index 0000000..63521d8 --- /dev/null +++ b/matrix/matrix_def.h @@ -0,0 +1,121 @@ +#ifndef MATRIX_DEF +#define MATRIX_DEF +#pragma once +#include +#include +#include +#include +using namespace std; +/* +███████╗██████╗ ██████╗ ███████╗ ███████╗███╗ ██╗ ██████╗ ██╗███╗ ██╗███████╗ +██╔════╝██╔══██╗██╔════╝ ██╔════╝ ██╔════╝████╗ ██║██╔════╝ ██║████╗ ██║██╔════╝ +█████╗ ██║ ██║██║ ███╗█████╗ █████╗ ██╔██╗ ██║██║ ███╗██║██╔██╗ ██║█████╗ +██╔══╝ ██║ ██║██║ ██║██╔══╝ ██╔══╝ ██║╚██╗██║██║ ██║██║██║╚██╗██║██╔══╝ +███████╗██████╔╝╚██████╔╝███████╗ ███████╗██║ ╚████║╚██████╔╝██║██║ ╚████║███████╗ +╚══════╝╚═════╝ ╚═════╝ ╚══════╝ ╚══════╝╚═╝ ╚═══╝ ╚═════╝ ╚═╝╚═╝ ╚═══╝╚══════╝ +Author：Edge +Web：likedge.top +Date：20200925 +*/ +//CreateMatrix Create a Matrix for ones; +//ex: +//2*3 +//0 0 0 +//0 0 0 +//change the value in matrix +typedef struct +{ + int row,col; + float **matrix; +}Matrix; +typedef struct +{ + int row,col; + string **str_matrix; +}str_Matrix; +str_Matrix CreateStr_Ma(int ro, int co) +{ + str_Matrix str_arr; + int row,col; + string **designma; + designma = (string**)malloc(ro*sizeof(string*)); + for(int i = 0;i +#include +#include +#define random(x) (rand()%x) + +void move_ele(int &ele1, int &ele2) +{ + ele1 ^= ele2 ^= ele1 ^= ele2; +} + +int add_by(int a,int b) +{ + int ans; + while(b) + { + ans = a^b; + b = ((a&b)<<1); + a = ans; + } + return a; +} + +//two matrix add +Matrix add(Matrix mid1,Matrix mid2,int flag=1) +{ + if(mid1.row == mid2.row&&mid1.col == mid2.col) + { + for(int x = 0;x0) + {return val_relu;} + else + {return 0;} +} +Matrix mat_relu(Matrix mid1) +{ + Matrix relu_mat = CreateMatrix(mid1.row,mid1.col); + for(int index_x = 0;index_x +#include +#include +#include +#include +#include"./autodiff/node.h" +#include"./matrix/matrix_def.h" +#include"./matrix/matrix_pro.h" +#include"./welcome/score_wel.cpp" +#include"./logistic/logistic_def.h" +#include"./file_pro/data_read.h" +#include"./grad_edge/matrix_grad.h" +using namespace std; +Node z = 1; +Node t1 = 1,a13 = 1; +Node loss_act(Node t1,Node a13) +{ + Node loss = 0.5*(pow((t1-a13),2)); + return loss; +} +Node sigmoid_act(Node z) +{ + Node sigmoid_act = 1/(1+(1/exp(z))); + return sigmoid_act; +} +Node (*loss)(Node,Node) = loss_act; +Node (*act)(Node) = sigmoid_act; +int main() +{ + cout<<"begin to train"<3;T_TFpl^{sEO z;Uv{@PP6F`v}`j>Be5k_4OTDjTw1}KyOf1 zz&CYJ#0w3l&h$RG(kXS%-TlYQ#E)v&T@D7?I{rAEGom`X$4Sz9S`oW{?Ru4767rA| z@>}u4RmeNf)Tc#oCYU*e+t;(O!C0PX7BvU$FF@RRc0Ww(9~hNT!xu6c)~8Bz5DBh@ 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b/picture/方向.svg new file mode 100644 index 0000000..2d29f7d --- /dev/null +++ b/picture/方向.svg @@ -0,0 +1 @@ + \ No newline at end of file diff --git a/picture/星月.svg b/picture/星月.svg new file mode 100644 index 0000000..ed4249a --- /dev/null +++ b/picture/星月.svg @@ -0,0 +1 @@ + \ No newline at end of file diff --git a/picture/火箭.svg b/picture/火箭.svg new file mode 100644 index 0000000..389f40b --- /dev/null +++ b/picture/火箭.svg @@ -0,0 +1 @@ + \ No newline at end of file diff --git a/requitement/.gitignore b/requitement/.gitignore new file mode 100755 index 0000000..08910a3 --- /dev/null +++ b/requitement/.gitignore @@ -0,0 +1,4 @@ +.gmake +obj/ +bin/ +lib/ diff --git a/requitement/Makefile b/requitement/Makefile new file mode 100755 index 0000000..c0e24c0 --- /dev/null +++ b/requitement/Makefile @@ -0,0 +1,62 @@ +CXX = g++ +BIN = bin +LIB = lib +LIB_NAME = autodiff +OBJS_GRADIENT_DESCENT = root/obj/node.o root/obj/graph.o examples/obj/gradient_descent.o +OBJS_ANN = root/obj/node.o root/obj/graph.o examples/obj/ann.o +OBJS_GRADIENT = root/obj/node.o root/obj/graph.o examples/obj/gradient.o +OBJS_SPEED = root/obj/node.o root/obj/graph.o examples/obj/speed.o +OBJS_SIMPLE = root/obj/node.o root/obj/graph.o examples/obj/simple.o + +all : gradient_descent ann gradient speed simple + +gradient_descent : $(BIN) root/include/vectmath.h root/include/mor.h root/include/dor.h root/include/por.h + $(MAKE) -C examples obj obj/gradient_descent.o + $(MAKE) -C root obj obj/node.o obj/graph.o + $(CXX) -o $(BIN)/gradient_descent $(OBJS_GRADIENT_DESCENT) $(LIBS) + +ann : $(BIN) root/include/vectmath.h root/include/mor.h root/include/dor.h root/include/por.h + $(MAKE) -C examples obj obj/ann.o + $(MAKE) -C root obj obj/node.o obj/graph.o + $(CXX) -o $(BIN)/ann $(OBJS_ANN) $(LIBS) + +gradient : $(BIN) root/include/vectmath.h root/include/mor.h root/include/dor.h root/include/por.h + $(MAKE) -C examples obj obj/gradient.o + $(MAKE) -C root obj obj/node.o obj/graph.o + $(CXX) -o $(BIN)/gradient $(OBJS_GRADIENT) $(LIBS) + +speed : $(BIN) root/include/vectmath.h root/include/mor.h root/include/dor.h root/include/por.h + $(MAKE) -C examples obj obj/speed.o + $(MAKE) -C root obj obj/node.o obj/graph.o + $(CXX) -o $(BIN)/speed $(OBJS_SPEED) $(LIBS) + +simple : $(BIN) root/include/mor.h root/include/dor.h root/include/por.h + $(MAKE) -C examples obj obj/simple.o + $(MAKE) -C root obj obj/node.o obj/graph.o + $(CXX) -o $(BIN)/simple $(OBJS_SIMPLE) $(LIBS) + +$(BIN) : + if [ ! -d $(BIN) ]; then mkdir $(BIN); fi + +$(LIB) : + if [ ! -d $(LIB) ]; then mkdir $(LIB); fi + +clean : + $(MAKE) -C root clean + $(MAKE) -C examples clean + if [ -d $(BIN) ]; then rm $(BIN) -r; fi + +install : $(LIB) + ar rcs $(LIB)/lib$(LIB_NAME).a root/obj/graph.o root/obj/node.o + if [ ! -d /usr/local/include/$(LIB_NAME) ]; then sudo mkdir /usr/local/include/$(LIB_NAME); fi + sudo cp $(LIB)/lib$(LIB_NAME).a /usr/local/lib + sudo cp root/include/*.h /usr/local/include/$(LIB_NAME) + +.PHONY : all +.PHONY : gradient_descent +.PHONY : ann +.PHONY : gradient +.PHONY : speed +.PHONY : simple +.PHONY : clean +.PHONY : install diff --git a/requitement/examples/Makefile b/requitement/examples/Makefile new file mode 100755 index 0000000..5633ce1 --- /dev/null +++ b/requitement/examples/Makefile @@ -0,0 +1,31 @@ +CXX = g++ +ODIR = obj +CXXFLAGS = -std=c++11 -O3 +OBJS = $(ODIR)/gradient_descent.o $(ODIR)/ann.o $(ODIR)/gradient.o $(ODIR)/speed.o $(ODIR)/simple.o + +all : $(ODIR) $(OBJS) + +$(ODIR)/gradient_descent.o : src/gradient_descent.cpp ../root/include/vectmath.h ../root/include/node.h + $(CXX) -c $< -o $@ $(CXXFLAGS) + +$(ODIR)/ann.o : src/ann.cpp ../root/include/vectmath.h ../root/include/node.h + $(CXX) -c $< -o $@ $(CXXFLAGS) + +$(ODIR)/gradient.o : src/gradient.cpp ../root/include/vectmath.h ../root/include/node.h + $(CXX) -c $< -o $@ $(CXXFLAGS) + +$(ODIR)/speed.o : src/speed.cpp ../root/include/vectmath.h ../root/include/node.h + $(CXX) -c $< -o $@ $(CXXFLAGS) + +$(ODIR)/simple.o : src/simple.cpp ../root/include/node.h + $(CXX) -c $< -o $@ $(CXXFLAGS) + +$(ODIR) : + if [ ! -d $(ODIR) ]; then mkdir $(ODIR); fi + +clean : + if [ -d $(ODIR) ]; then rm $(ODIR) -r; fi + +.PHONY : all +.PHONY : clean + diff --git a/requitement/examples/src/ann.cpp b/requitement/examples/src/ann.cpp new file mode 100755 index 0000000..73da71d --- /dev/null +++ b/requitement/examples/src/ann.cpp @@ -0,0 +1,126 @@ +#include +#include + +#include "../../root/include/vectmath.h" +#include "../../root/include/node.h" + +typedef std::vector Vector; +typedef std::vector Matrix; + +Node random_number(){ + return rand()/(double)RAND_MAX; +} + +Node tan_h(Node& x){ + return (1-exp(-2*x))/(1+exp(-2*x)); +} + +Node mean_square_error(Vector& y_true, Vector& y_pred){ + Node loss; + for(size_t i=0 ; iactivation = activation; + this->input_shape = input; + this->output_shape = output; + weights.resize(input, Vector(output)); + bias.resize(1, Vector(output)); + random_number >> weights; + random_number >> bias; + } + + Matrix forward(Matrix& previous){ + Matrix output = dot(previous, weights) + bias; + output = activation >> output; + return output; + } + + void backward(Node& loss, const float& learning_rate){ + weights -= learning_rate*loss.gradient(weights); + bias -= learning_rate*loss.gradient(bias); + } +}; + +struct Network { + std::vector layers; + int input_shape; + Graph* graph; + + Network(){ + graph = Graph::getInstance(); + } + + void input_layer(int input_shape){ + this->input_shape = input_shape; + } + + void add(int output_shape, Node (*activation)(Node&)){ + int input = layers.empty()?input_shape:layers.back().output_shape; + layers.push_back(Layer(input, output_shape, activation)); + } + + Matrix run(Matrix& input){ + Matrix output(input.size()); + for(size_t j=0 ; jnew_recording(); + } + } + std::cout << std::endl; + } +}; + +int main(int argc, char const *argv[]) { + srand(time(NULL)); + + Matrix input = {{0,0},{0,1},{1,0},{1,1}}; + Matrix output = {{0},{1},{1},{0}}; + + Network network; + network.input_layer(2); + network.add(3, tan_h); + network.add(1, tan_h); + network.fit(input, output, mean_square_error, 500, 0.1); + + Matrix pred = network.run(input); + std::cout << pred << std::endl; + return 0; +} diff --git a/requitement/examples/src/gradient.cpp b/requitement/examples/src/gradient.cpp new file mode 100755 index 0000000..4b131de --- /dev/null +++ b/requitement/examples/src/gradient.cpp @@ -0,0 +1,15 @@ +#include + +#include "../../root/include/vectmath.h" +#include "../../root/include/node.h" + +Node function(std::vector x){ + return pow(x[0]-x[1], 2) + x[0]*x[1]*x[2]; // (x-y)^2 + x*y*z +} + +int main(int argc, char const *argv[]) { + std::vector x = {5,6,7}; + Node f = function(x); + std::cout << "grad(f) = " << f.gradient(x) << std::endl; + return 0; +} diff --git a/requitement/examples/src/gradient_descent.cpp b/requitement/examples/src/gradient_descent.cpp new file mode 100755 index 0000000..019f7e6 --- /dev/null +++ b/requitement/examples/src/gradient_descent.cpp @@ -0,0 +1,27 @@ +#include + +#include "../../root/include/vectmath.h" +#include "../../root/include/node.h" + +Node function(std::vector& x){ + return pow(x[0], 2) + pow(x[1], 2); // x^2 + y^2 +} + +int main(int argc, char const *argv[]) { + Graph* graph = Graph::getInstance(); + + std::vector x = {50, 50}; + Node f; + + int epochs = 30; + float learning_rate = 0.1; + for(size_t i=0 ; inew_recording(); + } + + std::cout << "f = " << f << std::endl; + std::cout << "x = " << x << std::endl; + return 0; +} diff --git a/requitement/examples/src/simple.cpp b/requitement/examples/src/simple.cpp new file mode 100755 index 0000000..37dda1b --- /dev/null +++ b/requitement/examples/src/simple.cpp @@ -0,0 +1,13 @@ +#include +#include "../../root/include/node.h" + +int main(int argc, char const *argv[]) { + Node x=2, y=3; + Node f = x*y + sin(x); + + std::cout << "f(x,y) = x*y + sin(x)" << std::endl; + std::cout << "f(" << x << "," << y << ") = " << f << std::endl; + std::cout << "∂f/∂x = " << f.gradient(x) << std::endl; + std::cout << "∂f/∂y = " << f.gradient(y) << std::endl; + return 0; +} diff --git a/requitement/examples/src/speed.cpp b/requitement/examples/src/speed.cpp new file mode 100755 index 0000000..fe58f78 --- /dev/null +++ b/requitement/examples/src/speed.cpp @@ -0,0 +1,51 @@ +#include +#include +#include +#include +#include + +#include "../../root/include/vectmath.h" +#include "../../root/include/node.h" + +template +std::vector > get_random_matrix(const int& height, const int& width, T t){ + std::vector > mat(height, std::vector(width)); + for(auto& v : mat){ + for(auto& e : v){ + e = rand()/(double)RAND_MAX; + } + } + return mat; +} + +int main(int argc, char const *argv[]) { + srand(time(0)); + + int size = 30; + std::vector > a = get_random_matrix(size, size, double()); + std::vector > b = get_random_matrix(size, size, double()); + std::vector > c = get_random_matrix(size, size, Node()); + std::vector > d = get_random_matrix(size, size, Node()); + + std::cout << std::fixed; + std::cout << std::setprecision(10); + + std::cout << "Running with double...\t"; + std::cout.flush(); + auto start = std::chrono::high_resolution_clock::now(); + std::vector > ab = dot(a, b); + auto finish = std::chrono::high_resolution_clock::now(); + std::chrono::duration elapsed = finish - start; + std::cout << "Elapsed time: " << elapsed.count() << " s" << std::endl; + + std::cout << "Running with Node...\t"; + std::cout.flush(); + start = std::chrono::high_resolution_clock::now(); + std::vector > cd = dot(c, d); + finish = std::chrono::high_resolution_clock::now(); + elapsed = finish - start; + std::cout << "Elapsed time: " << elapsed.count() << " s" << std::endl; + + std::cout << "Yet to be improved..." << std::endl; + return 0; +} diff --git a/requitement/root/Makefile b/requitement/root/Makefile new file mode 100755 index 0000000..1e9a102 --- /dev/null +++ b/requitement/root/Makefile @@ -0,0 +1,22 @@ +CXX = g++ +ODIR = obj +CXXFLAGS = -std=c++11 -O3 +OBJS = $(ODIR)/graph.o $(ODIR)/node.o + +all : $(ODIR) $(OBJS) + +$(ODIR)/graph.o : src/graph.cpp include/graph.h + $(CXX) -c $< -o $@ $(CXXFLAGS) + +$(ODIR)/node.o : src/node.cpp include/node.h + $(CXX) -c $< -o $@ $(CXXFLAGS) + +$(ODIR) : + if [ ! -d $(ODIR) ]; then mkdir $(ODIR); fi + +clean : + if [ -d $(ODIR) ]; then rm $(ODIR) -r; fi + +.PHONY : all +.PHONY : clean + diff --git a/requitement/root/include/dor.h b/requitement/root/include/dor.h new file mode 100755 index 0000000..cfff375 --- /dev/null +++ b/requitement/root/include/dor.h @@ -0,0 +1,16 @@ +#ifndef DYADIC_OPERATION_RESULT +#define DYADIC_OPERATION_RESULT + +struct DyadicOperationResult { + double value; + double left_grad; + double right_grad; + + DyadicOperationResult(double value, double left_grad, double right_grad){ + this->value = value; + this->left_grad = left_grad; + this->right_grad = right_grad; + } +}; + +#endif /* end of include guard: DYADIC_OPERATION_RESULT */ diff --git a/requitement/root/include/graph.h b/requitement/root/include/graph.h new file mode 100755 index 0000000..441ccf8 --- /dev/null +++ b/requitement/root/include/graph.h @@ -0,0 +1,26 @@ +#ifndef GRAPH_H +#define GRAPH_H + +#include +#include +#include + +class Graph { + private: + std::map > > nodes; + static Graph* instance; + Graph(); + + public: + static long int uid_counter; + static long int uid(); + static Graph* getInstance(); + + void connect(const long int& uid, const std::pair& edge); + std::vector > get(const long int& uid) const; + bool has(const long int& uid) const; + + void new_recording(); +}; + +#endif /* end of include guard: GRAPH_H */ diff --git a/requitement/root/include/mor.h b/requitement/root/include/mor.h new file mode 100755 index 0000000..b2fe98b --- /dev/null +++ b/requitement/root/include/mor.h @@ -0,0 +1,14 @@ +#ifndef MONADIC_OPERATION_RESULT +#define MONADIC_OPERATION_RESULT + +struct MonadicOperationResult { + double value; + double grad; + + MonadicOperationResult(double value, double grad){ + this->value = value; + this->grad = grad; + } +}; + +#endif /* end of include guard: MONADIC_OPERATION_RESULT */ diff --git a/requitement/root/include/node.h b/requitement/root/include/node.h new file mode 100755 index 0000000..34c1330 --- /dev/null +++ b/requitement/root/include/node.h @@ -0,0 +1,72 @@ +#ifndef NODE_H +#define NODE_H + +#include +#include + +#include "graph.h" +#include "mor.h" +#include "dor.h" +#include "por.h" + +class Node { + private: + double value; + long int uid; + + double gradient_recursive(Graph* graph, const long int& current_uid, const long int& stop_uid) const; + + public: + Node(const double& value=0); + Node(const Node& node); + + static Node monadic_operation(const Node& n, MonadicOperationResult (*)(const double&)); + static Node dyadic_operation(const Node& l, const Node& r, DyadicOperationResult (*)(const double&, const double&)); + static Node polyadic_operation(const std::vector& nodes, PolyadicOperationResult (*)(const std::vector&)); + + double gradient(const Node& node) const; + std::vector gradient(const std::vector& nodes) const; + std::vector > gradient(const std::vector >& nodes) const; + + friend Node operator+(const Node& l, const Node& r); + friend Node operator-(const Node& l, const Node& r); + friend Node operator*(const Node& l, const Node& r); + friend Node operator/(const Node& l, const Node& r); + + Node& operator+=(const Node& r); + Node& operator-=(const Node& r); + Node& operator*=(const Node& r); + Node& operator/=(const Node& r); + + friend bool operator==(const Node& l, const Node& r); + friend bool operator<(const Node& l, const Node& r); + friend bool operator>(const Node& l, const Node& r); + friend bool operator<=(const Node& l, const Node& r); + friend bool operator>=(const Node& l, const Node& r); + + friend Node sin(const Node& x); + friend Node cos(const Node& x); + friend Node tan(const Node& x); + friend Node sinh(const Node& x); + friend Node cosh(const Node& x); + friend Node tanh(const Node& x); + friend Node asin(const Node& x); + friend Node acos(const Node& x); + friend Node atan(const Node& x); + + friend Node log(const Node& x, const Node& base); + friend Node log10(const Node& x); + friend Node ln(const Node& x); + + friend Node pow(const Node& x, const Node& p); + friend Node exp(const Node& x); + friend Node sqrt(const Node& x); + + friend Node abs(const Node& x); + friend Node min(const Node& l, const Node& r); + friend Node max(const Node& l, const Node& r); + + friend std::ostream& operator<<(std::ostream& os, const Node& node); +}; + +#endif /* end of include guard: NODE_H */ diff --git a/requitement/root/include/por.h b/requitement/root/include/por.h new file mode 100755 index 0000000..6eedd50 --- /dev/null +++ b/requitement/root/include/por.h @@ -0,0 +1,16 @@ +#ifndef POLYADIC_OPERATION_RESULT +#define POLYADIC_OPERATION_RESULT + +#include + +struct PolyadicOperationResult { + double value; + std::vector gradients; + + PolyadicOperationResult(double value, const std::vector& gradients){ + this->value = value; + this->gradients = gradients; + } +}; + +#endif /* end of include guard: POLYADIC_OPERATION_RESULT */ diff --git a/requitement/root/include/vectmath.h b/requitement/root/include/vectmath.h new file mode 100755 index 0000000..7426398 --- /dev/null +++ b/requitement/root/include/vectmath.h @@ -0,0 +1,99 @@ +#ifndef VECTMATH +#define VECTMATH + +#include +#include +#include +#include +#include + +// dot product +template +std::vector > dot(const std::vector >& a, const std::vector >& b){ + assert(a[0].size()==b.size()); + + T w=0; + std::vector > result(a.size(), std::vector(b[0].size())); + for (int i=0 ; i +std::vector& operator-=(std::vector& u, const std::vector& v){ + assert(u.size()==v.size()); + for(size_t i=0 ; i +std::vector operator+(const std::vector& u, const std::vector& v){ + assert(u.size()==v.size()); + std::vector w(u.size()); + for(size_t i=0 ; i +std::vector operator*(const S& s, const std::vector& u){ + std::vector result(u.size()); + for(size_t i=0 ; i +std::vector& operator>>(U (*fun)(U&), std::vector& u){ + std::transform(u.begin(), u.end(), u.begin(), fun); + return u; +} + +template +std::vector& operator>>(S (*fun)(S&), std::vector& u){ + for(auto& v : u){ + fun >> v; + } + return u; +} + +template +std::vector& operator>>(U (*fun)(), std::vector& u){ + for(auto& e : u){ + e = fun(); + } + return u; +} + +template +std::vector& operator>>(S (*fun)(), std::vector& u){ + for(auto& v : u){ + fun >> v; + } + return u; +} + +template +std::ostream& operator<<(std::ostream& os, const std::vector& u){ + os << "["; + for(size_t i=0 ; i& edge){ + nodes[uid].push_back(edge); +} + +std::vector > Graph::get(const long int& uid) const{ + return nodes.at(uid); +} + +bool Graph::has(const long int& uid) const{ + return nodes.find(uid)!=nodes.end(); +} + +void Graph::new_recording(){ + nodes.clear(); +} diff --git a/requitement/root/src/node.cpp b/requitement/root/src/node.cpp new file mode 100755 index 0000000..dab3e44 --- /dev/null +++ b/requitement/root/src/node.cpp @@ -0,0 +1,275 @@ +#include "../include/node.h" + +Node::Node(const double& value) { + this->value = value; + this->uid = Graph::uid(); +} + +Node::Node(const Node& node){ + this->value = node.value; + this->uid = node.uid; +} + +double Node::gradient_recursive(Graph* graph, const long int& current_uid, const long int& stop_uid) const{ + if(current_uid==stop_uid){ + return 1.0; + } + + double sum=0.0; + if(graph->has(current_uid)){ + for(auto& pair : graph->get(current_uid)){ + sum += pair.first*gradient_recursive(graph, pair.second, stop_uid); + } + } + return sum; +} + +double Node::gradient(const Node& node) const{ + Graph* graph = Graph::getInstance(); + return gradient_recursive(graph, this->uid, node.uid); +} + +std::vector Node::gradient(const std::vector& nodes) const{ + Graph* graph = Graph::getInstance(); + std::vector grad(nodes.size()); + for(size_t i=0 ; iuid, nodes[i].uid); + } + return grad; +} + +std::vector > Node::gradient(const std::vector >& nodes) const{ + Graph* graph = Graph::getInstance(); + std::vector > grad(nodes.size()); + for(size_t i=0 ; iuid, nodes[i][j].uid); + } + } + return grad; +} + +Node Node::monadic_operation(const Node& n, MonadicOperationResult (*fun)(const double&)){ + MonadicOperationResult res = fun(n.value); + Node result(res.value); + Graph* graph = Graph::getInstance(); + graph->connect(result.uid, std::make_pair(res.grad, n.uid)); + return result; +} + +Node Node::dyadic_operation(const Node& left, const Node& right, DyadicOperationResult (*fun)(const double&, const double&)){ + DyadicOperationResult res = fun(left.value, right.value); + Node result(res.value); + Graph* graph = Graph::getInstance(); + graph->connect(result.uid, std::make_pair(res.left_grad, left.uid)); + graph->connect(result.uid, std::make_pair(res.right_grad, right.uid)); + return result; +} + +Node Node::polyadic_operation(const std::vector& nodes, PolyadicOperationResult (*fun)(const std::vector&)){ + std::vector values(nodes.size()); + for(size_t i=0 ; iconnect(result.uid, std::make_pair(res.gradients[i], nodes[i].uid)); + } + return result; +} + +Node operator+(const Node& left, const Node& right){ + return Node::dyadic_operation(left, right, [](const double& l, const double& r){ + return DyadicOperationResult(l+r, 1.0, 1.0); + }); +} + +Node operator-(const Node& left, const Node& right){ + return Node::dyadic_operation(left, right, [](const double& l, const double& r){ + return DyadicOperationResult(l-r, 1.0, -1.0); + }); +} + +Node operator*(const Node& left, const Node& right){ + return Node::dyadic_operation(left, right, [](const double& l, const double& r){ + return DyadicOperationResult(l*r, r, l); + }); +} + +Node operator/(const Node& left, const Node& right){ + return Node::dyadic_operation(left, right, [](const double& l, const double& r){ + return DyadicOperationResult(l/r, 1.0/r, -1.0*l/(r*r)); + }); +} + +Node& Node::operator+=(const Node& r){ + *this = *this + r; + return *this; +} + +Node& Node::operator-=(const Node& r){ + *this = *this - r; + return *this; +} + +Node& Node::operator*=(const Node& r){ + *this = *this * r; + return *this; +} + +Node& Node::operator/=(const Node& r){ + *this = *this / r; + return *this; +} + +bool operator==(const Node& left, const Node& right){ + return left.value==right.value; +} + +bool operator<(const Node& left, const Node& right){ + return left.value(const Node& left, const Node& right){ + return left.value>right.value; +} + +bool operator<=(const Node& left, const Node& right){ + return left.value<=right.value; +} + +bool operator>=(const Node& left, const Node& right){ + return left.value>=right.value; +} + +Node sin(const Node& x){ + return Node::monadic_operation(x, [](const double& n){ + return MonadicOperationResult(::sin(n), ::cos(n)); + }); +} + +Node cos(const Node& x){ + return Node::monadic_operation(x, [](const double& n){ + return MonadicOperationResult(::cos(n), -1.0*::sin(n)); + }); +} + +Node tan(const Node& x){ + return Node::monadic_operation(x, [](const double& n){ + return MonadicOperationResult(::tan(n), 1.0/::pow(::cos(n), 2)); + }); +} + +Node sinh(const Node& x){ + return Node::monadic_operation(x, [](const double& n){ + return MonadicOperationResult(::sinh(n), ::cosh(n)); + }); +} + +Node cosh(const Node& x){ + return Node::monadic_operation(x, [](const double& n){ + return MonadicOperationResult(::cosh(n), ::sinh(n)); + }); +} + +Node asin(const Node& x){ + return Node::monadic_operation(x, [](const double& n){ + return MonadicOperationResult(::asin(n), 1.0/(::sqrt(1-n*n))); + }); +} + +Node acos(const Node& x){ + return Node::monadic_operation(x, [](const double& n){ + return MonadicOperationResult(::acos(n), -1.0/(::sqrt(1-n*n))); + }); +} + +Node atan(const Node& x){ + return Node::monadic_operation(x, [](const double& n){ + return MonadicOperationResult(::atan(n), 1.0/(1+n*n)); + }); +} + +Node tanh(const Node& x){ + return Node::monadic_operation(x, [](const double& n){ + return MonadicOperationResult(::tanh(n), 1.0-::pow(::tanh(n), 2)); + }); +} + +Node log(const Node& x, const Node& base){ + return Node::dyadic_operation(x, base, [](const double& a, const double& b){ + return DyadicOperationResult(::log(a)/::log(b), 1.0/(a*::log(b)), -1.0*::log(a)/(b*::log(b))); + }); +} + +Node log10(const Node& x){ + return Node::monadic_operation(x, [](const double& n){ + return MonadicOperationResult(::log(n)/::log(10), 1.0/(n*::log(10))); + }); +} + +Node ln(const Node& x){ + return Node::monadic_operation(x, [](const double& n){ + return MonadicOperationResult(::log(n), 1.0/::log(n)); + }); +} + +Node pow(const Node& x, const Node& base){ + return Node::dyadic_operation(x, base, [](const double& a, const double& b){ + if(a<=0){ + return DyadicOperationResult(::pow(a,b), b*::pow(a,b-1), 0); + } + return DyadicOperationResult(::pow(a,b), b*::pow(a,b-1), ::log(a)*::pow(a,b)); + }); +} + +Node exp(const Node& x){ + return Node::monadic_operation(x, [](const double& n){ + return MonadicOperationResult(::exp(n), ::exp(n)); + }); +} + +Node sqrt(const Node& x){ + return Node::monadic_operation(x, [](const double& n){ + return MonadicOperationResult(::sqrt(n), 1.0/(2*::sqrt(n))); + }); +} + +Node abs(const Node& x){ + return Node::monadic_operation(x, [](const double& n){ + int sign = n==0 ? 0 : n/::abs(n); + return MonadicOperationResult(::abs(n), sign); + }); +} + +Node min(const Node& left, const Node& right){ + return Node::dyadic_operation(left, right, [](const double& a, const double& b){ + if(ab){ + return DyadicOperationResult(b, 0, 1); + } + return DyadicOperationResult(a, 0, 0); + }); +} + +Node max(const Node& left, const Node& right){ + return Node::dyadic_operation(left, right, [](const double& a, const double& b){ + if(a>b){ + return DyadicOperationResult(a, 1, 0); + } + if(avalue = value; + this->left_grad = left_grad; + this->right_grad = right_grad; + } +}; + +#endif /* end of include guard: DYADIC_OPERATION_RESULT */ diff --git a/root/include/graph.h b/root/include/graph.h new file mode 100755 index 0000000..441ccf8 --- /dev/null +++ b/root/include/graph.h @@ -0,0 +1,26 @@ +#ifndef GRAPH_H +#define GRAPH_H + +#include +#include +#include + +class Graph { + private: + std::map > > nodes; + static Graph* instance; + Graph(); + + public: + static long int uid_counter; + static long int uid(); + static Graph* getInstance(); + + void connect(const long int& uid, const std::pair& edge); + std::vector > get(const long int& uid) const; + bool has(const long int& uid) const; + + void new_recording(); +}; + +#endif /* end of include guard: GRAPH_H */ diff --git a/root/include/mor.h b/root/include/mor.h new file mode 100755 index 0000000..b2fe98b --- /dev/null +++ b/root/include/mor.h @@ -0,0 +1,14 @@ +#ifndef MONADIC_OPERATION_RESULT +#define MONADIC_OPERATION_RESULT + +struct MonadicOperationResult { + double value; + double grad; + + MonadicOperationResult(double value, double grad){ + this->value = value; + this->grad = grad; + } +}; + +#endif /* end of include guard: MONADIC_OPERATION_RESULT */ diff --git a/root/include/node.h b/root/include/node.h new file mode 100755 index 0000000..34c1330 --- /dev/null +++ b/root/include/node.h @@ -0,0 +1,72 @@ +#ifndef NODE_H +#define NODE_H + +#include +#include + +#include "graph.h" +#include "mor.h" +#include "dor.h" +#include "por.h" + +class Node { + private: + double value; + long int uid; + + double gradient_recursive(Graph* graph, const long int& current_uid, const long int& stop_uid) const; + + public: + Node(const double& value=0); + Node(const Node& node); + + static Node monadic_operation(const Node& n, MonadicOperationResult (*)(const double&)); + static Node dyadic_operation(const Node& l, const Node& r, DyadicOperationResult (*)(const double&, const double&)); + static Node polyadic_operation(const std::vector& nodes, PolyadicOperationResult (*)(const std::vector&)); + + double gradient(const Node& node) const; + std::vector gradient(const std::vector& nodes) const; + std::vector > gradient(const std::vector >& nodes) const; + + friend Node operator+(const Node& l, const Node& r); + friend Node operator-(const Node& l, const Node& r); + friend Node operator*(const Node& l, const Node& r); + friend Node operator/(const Node& l, const Node& r); + + Node& operator+=(const Node& r); + Node& operator-=(const Node& r); + Node& operator*=(const Node& r); + Node& operator/=(const Node& r); + + friend bool operator==(const Node& l, const Node& r); + friend bool operator<(const Node& l, const Node& r); + friend bool operator>(const Node& l, const Node& r); + friend bool operator<=(const Node& l, const Node& r); + friend bool operator>=(const Node& l, const Node& r); + + friend Node sin(const Node& x); + friend Node cos(const Node& x); + friend Node tan(const Node& x); + friend Node sinh(const Node& x); + friend Node cosh(const Node& x); + friend Node tanh(const Node& x); + friend Node asin(const Node& x); + friend Node acos(const Node& x); + friend Node atan(const Node& x); + + friend Node log(const Node& x, const Node& base); + friend Node log10(const Node& x); + friend Node ln(const Node& x); + + friend Node pow(const Node& x, const Node& p); + friend Node exp(const Node& x); + friend Node sqrt(const Node& x); + + friend Node abs(const Node& x); + friend Node min(const Node& l, const Node& r); + friend Node max(const Node& l, const Node& r); + + friend std::ostream& operator<<(std::ostream& os, const Node& node); +}; + +#endif /* end of include guard: NODE_H */ diff --git a/root/include/por.h b/root/include/por.h new file mode 100755 index 0000000..6eedd50 --- /dev/null +++ b/root/include/por.h @@ -0,0 +1,16 @@ +#ifndef POLYADIC_OPERATION_RESULT +#define POLYADIC_OPERATION_RESULT + +#include + +struct PolyadicOperationResult { + double value; + std::vector gradients; + + PolyadicOperationResult(double value, const std::vector& gradients){ + this->value = value; + this->gradients = gradients; + } +}; + +#endif /* end of include guard: POLYADIC_OPERATION_RESULT */ diff --git a/root/include/vectmath.h b/root/include/vectmath.h new file mode 100755 index 0000000..7426398 --- /dev/null +++ b/root/include/vectmath.h @@ -0,0 +1,99 @@ +#ifndef VECTMATH +#define VECTMATH + +#include +#include +#include +#include +#include + +// dot product +template +std::vector > dot(const std::vector >& a, const std::vector >& b){ + assert(a[0].size()==b.size()); + + T w=0; + std::vector > result(a.size(), std::vector(b[0].size())); + for (int i=0 ; i +std::vector& operator-=(std::vector& u, const std::vector& v){ + assert(u.size()==v.size()); + for(size_t i=0 ; i +std::vector operator+(const std::vector& u, const std::vector& v){ + assert(u.size()==v.size()); + std::vector w(u.size()); + for(size_t i=0 ; i +std::vector operator*(const S& s, const std::vector& u){ + std::vector result(u.size()); + for(size_t i=0 ; i +std::vector& operator>>(U (*fun)(U&), std::vector& u){ + std::transform(u.begin(), u.end(), u.begin(), fun); + return u; +} + +template +std::vector& operator>>(S (*fun)(S&), std::vector& u){ + for(auto& v : u){ + fun >> v; + } + return u; +} + +template +std::vector& operator>>(U (*fun)(), std::vector& u){ + for(auto& e : u){ + e = fun(); + } + return u; +} + +template +std::vector& operator>>(S (*fun)(), std::vector& u){ + for(auto& v : u){ + fun >> v; + } + return u; +} + +template +std::ostream& operator<<(std::ostream& os, const std::vector& u){ + os << "["; + for(size_t i=0 ; itleWK@h9>@C5>peUB(27_cG4yW6YWreq88S{mUg9U_B;38 z7u!h+?8?u-ckVg&eBE=8pWh#^e0*&=W3HtPU%1@3E-%5C9~Z{gaSaiDol&#WW>k;@ zj4DM#Cvz^E*LBkvGU?79y51h%)$ULQtfNI3q>p?FdKp_o6K*z4;0#^wNhEY*C}Ctw z-Hh*@uWzH$vr#RGtzhg6!hnB?bbo(3RnXrQY7aS7Audm0im8z04CStP=z3S&j2C8f 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zwN0XZRko$JLzclcTQqVSe!^D#Y--&MYL)!+<8{G~PWD66!*nxP&?rpQmoc<(oRz@i2Ib z5uJ^7Rx1TdZL?X2;qZ9sw$!#;q4wIwP={Fuf5K0(PA`OWJVkK@aC4ZW!Qn9v9G=;GBz#eo!Od%K%CrOwaD?Blg?8}nP?X~rd!4?XP zN^9Kk`r8}@ZGJ~Vb5eonUCcu&%Scqj77{S0Td{k%~AblZx^C z0PJc+wN4cI1PfO5_(e$0Cnwv^6C%nw|N^M0qiWAhDz=n3&(} z$jg}VEXI(9CB+y?YjanZg)#2HaO1zF*k)}lN+NoSwEqGys&T;p literal 0 HcmV?d00001 diff --git a/root/src/graph.cpp b/root/src/graph.cpp new file mode 100755 index 0000000..bece0d0 --- /dev/null +++ b/root/src/graph.cpp @@ -0,0 +1,33 @@ +#include "../include/graph.h" + +Graph* Graph::instance = 0; +long int Graph::uid_counter = 1; + +long int Graph::uid(){ + return uid_counter++; +} + +Graph* Graph::getInstance(){ + if(instance==NULL){ + instance = new Graph(); + } + return instance; +} + +Graph::Graph(){} + +void Graph::connect(const long int& uid, const std::pair& edge){ + nodes[uid].push_back(edge); +} + +std::vector > Graph::get(const long int& uid) const{ + return nodes.at(uid); +} + +bool Graph::has(const long int& uid) const{ + return nodes.find(uid)!=nodes.end(); +} + +void Graph::new_recording(){ + nodes.clear(); +} diff --git a/root/src/node.cpp b/root/src/node.cpp new file mode 100755 index 0000000..dab3e44 --- /dev/null +++ b/root/src/node.cpp @@ -0,0 +1,275 @@ +#include "../include/node.h" + +Node::Node(const double& value) { + this->value = value; + this->uid = Graph::uid(); +} + +Node::Node(const Node& node){ + this->value = node.value; + this->uid = node.uid; +} + +double Node::gradient_recursive(Graph* graph, const long int& current_uid, const long int& stop_uid) const{ + if(current_uid==stop_uid){ + return 1.0; + } + + double sum=0.0; + if(graph->has(current_uid)){ + for(auto& pair : graph->get(current_uid)){ + sum += pair.first*gradient_recursive(graph, pair.second, stop_uid); + } + } + return sum; +} + +double Node::gradient(const Node& node) const{ + Graph* graph = Graph::getInstance(); + return gradient_recursive(graph, this->uid, node.uid); +} + +std::vector Node::gradient(const std::vector& nodes) const{ + Graph* graph = Graph::getInstance(); + std::vector grad(nodes.size()); + for(size_t i=0 ; iuid, nodes[i].uid); + } + return grad; +} + +std::vector > Node::gradient(const std::vector >& nodes) const{ + Graph* graph = Graph::getInstance(); + std::vector > grad(nodes.size()); + for(size_t i=0 ; iuid, nodes[i][j].uid); + } + } + return grad; +} + +Node Node::monadic_operation(const Node& n, MonadicOperationResult (*fun)(const double&)){ + MonadicOperationResult res = fun(n.value); + Node result(res.value); + Graph* graph = Graph::getInstance(); + graph->connect(result.uid, std::make_pair(res.grad, n.uid)); + return result; +} + +Node Node::dyadic_operation(const Node& left, const Node& right, DyadicOperationResult (*fun)(const double&, const double&)){ + DyadicOperationResult res = fun(left.value, right.value); + Node result(res.value); + Graph* graph = Graph::getInstance(); + graph->connect(result.uid, std::make_pair(res.left_grad, left.uid)); + graph->connect(result.uid, std::make_pair(res.right_grad, right.uid)); + return result; +} + +Node Node::polyadic_operation(const std::vector& nodes, PolyadicOperationResult (*fun)(const std::vector&)){ + std::vector values(nodes.size()); + for(size_t i=0 ; iconnect(result.uid, std::make_pair(res.gradients[i], nodes[i].uid)); + } + return result; +} + +Node operator+(const Node& left, const Node& right){ + return Node::dyadic_operation(left, right, [](const double& l, const double& r){ + return DyadicOperationResult(l+r, 1.0, 1.0); + }); +} + +Node operator-(const Node& left, const Node& right){ + return Node::dyadic_operation(left, right, [](const double& l, const double& r){ + return DyadicOperationResult(l-r, 1.0, -1.0); + }); +} + +Node operator*(const Node& left, const Node& right){ + return Node::dyadic_operation(left, right, [](const double& l, const double& r){ + return DyadicOperationResult(l*r, r, l); + }); +} + +Node operator/(const Node& left, const Node& right){ + return Node::dyadic_operation(left, right, [](const double& l, const double& r){ + return DyadicOperationResult(l/r, 1.0/r, -1.0*l/(r*r)); + }); +} + +Node& Node::operator+=(const Node& r){ + *this = *this + r; + return *this; +} + +Node& Node::operator-=(const Node& r){ + *this = *this - r; + return *this; +} + +Node& Node::operator*=(const Node& r){ + *this = *this * r; + return *this; +} + +Node& Node::operator/=(const Node& r){ + *this = *this / r; + return *this; +} + +bool operator==(const Node& left, const Node& right){ + return left.value==right.value; +} + +bool operator<(const Node& left, const Node& right){ + return left.value(const Node& left, const Node& right){ + return left.value>right.value; +} + +bool operator<=(const Node& left, const Node& right){ + return left.value<=right.value; +} + +bool operator>=(const Node& left, const Node& right){ + return left.value>=right.value; +} + +Node sin(const Node& x){ + return Node::monadic_operation(x, [](const double& n){ + return MonadicOperationResult(::sin(n), ::cos(n)); + }); +} + +Node cos(const Node& x){ + return Node::monadic_operation(x, [](const double& n){ + return MonadicOperationResult(::cos(n), -1.0*::sin(n)); + }); +} + +Node tan(const Node& x){ + return Node::monadic_operation(x, [](const double& n){ + return MonadicOperationResult(::tan(n), 1.0/::pow(::cos(n), 2)); + }); +} + +Node sinh(const Node& x){ + return Node::monadic_operation(x, [](const double& n){ + return MonadicOperationResult(::sinh(n), ::cosh(n)); + }); +} + +Node cosh(const Node& x){ + return Node::monadic_operation(x, [](const double& n){ + return MonadicOperationResult(::cosh(n), ::sinh(n)); + }); +} + +Node asin(const Node& x){ + return Node::monadic_operation(x, [](const double& n){ + return MonadicOperationResult(::asin(n), 1.0/(::sqrt(1-n*n))); + }); +} + +Node acos(const Node& x){ + return Node::monadic_operation(x, [](const double& n){ + return MonadicOperationResult(::acos(n), -1.0/(::sqrt(1-n*n))); + }); +} + +Node atan(const Node& x){ + return Node::monadic_operation(x, [](const double& n){ + return MonadicOperationResult(::atan(n), 1.0/(1+n*n)); + }); +} + +Node tanh(const Node& x){ + return Node::monadic_operation(x, [](const double& n){ + return MonadicOperationResult(::tanh(n), 1.0-::pow(::tanh(n), 2)); + }); +} + +Node log(const Node& x, const Node& base){ + return Node::dyadic_operation(x, base, [](const double& a, const double& b){ + return DyadicOperationResult(::log(a)/::log(b), 1.0/(a*::log(b)), -1.0*::log(a)/(b*::log(b))); + }); +} + +Node log10(const Node& x){ + return Node::monadic_operation(x, [](const double& n){ + return MonadicOperationResult(::log(n)/::log(10), 1.0/(n*::log(10))); + }); +} + +Node ln(const Node& x){ + return Node::monadic_operation(x, [](const double& n){ + return MonadicOperationResult(::log(n), 1.0/::log(n)); + }); +} + +Node pow(const Node& x, const Node& base){ + return Node::dyadic_operation(x, base, [](const double& a, const double& b){ + if(a<=0){ + return DyadicOperationResult(::pow(a,b), b*::pow(a,b-1), 0); + } + return DyadicOperationResult(::pow(a,b), b*::pow(a,b-1), ::log(a)*::pow(a,b)); + }); +} + +Node exp(const Node& x){ + return Node::monadic_operation(x, [](const double& n){ + return MonadicOperationResult(::exp(n), ::exp(n)); + }); +} + +Node sqrt(const Node& x){ + return Node::monadic_operation(x, [](const double& n){ + return MonadicOperationResult(::sqrt(n), 1.0/(2*::sqrt(n))); + }); +} + +Node abs(const Node& x){ + return Node::monadic_operation(x, [](const double& n){ + int sign = n==0 ? 0 : n/::abs(n); + return MonadicOperationResult(::abs(n), sign); + }); +} + +Node min(const Node& left, const Node& right){ + return Node::dyadic_operation(left, right, [](const double& a, const double& b){ + if(ab){ + return DyadicOperationResult(b, 0, 1); + } + return DyadicOperationResult(a, 0, 0); + }); +} + +Node max(const Node& left, const Node& right){ + return Node::dyadic_operation(left, right, [](const double& a, const 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+Data_struct_define +link_list: ll +graph + + +--------------------------------------------------------------- +if you have the better answer on it , it is nothing, just test~ +--------------------------------------------------------------- + +*/ +#include +using namespace std; +int main(){ + cout<<"hello,world"<TBlK|p8leE2l&Q+RxM{Qi=K z*Xg(FOK+sm)Sn|2ObZd7HWc9ZFV|NrPff!4gQ;PfgmV#04@lyl-`^5wYmopPJ3cQe zK=|Gch%^M}B$E>mw1R$rb4%;$=0uPk-=%j6d|PBC6|6GkNqi^B0D;e69jI*#G$G86 zZ%>=RmqX0Pk6`H)0VC+EXsB;aR@jcO|89YAt;nqrOl>*Z&+lJTQQ;4?RRkJa{4M3H z?fAT35cn>YL=l`qpAE6!U(wvsR8zl3hTHMgwhMfxNd6IQ{n>H*{jK$P)znw|YwD{S zkkF1V_(g#)DDe?&$6>`!ayJ)g{r<%ZmoM}$y77i(Li&ONkLH!B0rSr*9O9vRT=0W$ z4ars*9Uq!g{DP_NK=QFzMv>$9*ELWjYg+tOt@RZn=xYlK`toERg01a3L53>_?O>CW z)cOXIpIEk4GK=6Gl{t-@$~Q}bh>dT6`R5gm;+dk=@2@TQH?ON(-B9aqY-y796lwV# z5%}Dy5do{b6i@wr8F}Q-@2@OxDOZqcha~LYoys?Yt@x5Dg^&1FSJzOl!iAhDNYkcC zd?W+vXT>MQP(@kvWzmuwuGbeY5z>Zu2lHPGs-z-kZuM_j)9)-iM8}+a&-&AYFXsPX<3+!p 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b/union_test/matrix_test.cpp @@ -0,0 +1,29 @@ +#include +#include +#include +#include +#include +#include +#include"../matrix/matrix_def.h" +#include"../welcome/score_wel.cpp" +#include"../matrix/matrix_pro.h" +struct testMatrix +{ + int row=100,col=100; + float **matrix; +}Matrix_1; +int main(){ + Matrix a=ones(4,4); + Matrix b=CreateRandMat(4,4); + str_Matrix c=CreateStr_Ma(4,4); + cout_mat(a); + cout<<"=----------="< +#include +#include +#include +#include +#include +#include"../matrix/matrix_def.h" +#include"../welcome/score_wel.cpp" +#include"../matrix/matrix_pro.h" diff --git a/生产流程.pdf b/生产流程.pdf new file mode 100644 index 0000000..4d16130 --- /dev/null +++ b/生产流程.pdf @@ -0,0 +1,8456 @@ +%PDF-1.4 +% + +1 0 obj + << + /Title () + /Author () + /Subject () + /Keywords () + /Creator (XMind) + /Producer (XMind R3.7.8.201807240049) + /CreationDate (D:20200806113840+08'00') + /ModDate (D:20200806113840+08'00') + /Trapped /False + >> +endobj + +2 0 obj + << + /Type /Catalog + /Pages 3 0 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