decentralized-machine-learning
所属分类：其他
开发工具：GO
文件大小：0KB
下载次数：0
上传日期：2019-01-14 12:08:56
上 传 者：
sh-1993
说明： 去中心化机器学习，，
(decentralized machine learning,,)
文件列表:
_Chunks/ (0, 2019-01-14)
_Chunks/38f9085b3ac85b061a2b49dfbf2994d44f58bd284887d5636398f19a61b20b4f (8192, 2019-01-14)
_Chunks/9c02900d81cc86567731c564a62b440d2c01212c958303aed99abbd56bcead6e (8192, 2019-01-14)
_Chunks/9f2b92b782af4a8bcf4f73d41bb8962957ea925f36e42945c3c8fbe54e7d27cb (32, 2019-01-14)
_Chunks/b04cd0182659133b6f7fbfcba2096b4201f710b2732405f6f5c2ebf82a050dec (96, 2019-01-14)
_Chunks/ce947ee2d56bc0b87430be6380afc5b41e283dec17517432fb4bfe647fb080dd (3893, 2019-01-14)
_Chunks/e4ffbac3fb216defb7b59ea7375c6960303472d6f7f570e6cf2e820ed37da891 (7509, 2019-01-14)
_Datasets/ (0, 2019-01-14)
_Datasets/UCI CBM Dataset/ (0, 2019-01-14)
_Datasets/UCI CBM Dataset/Features.txt (758, 2019-01-14)
_Datasets/UCI CBM Dataset/uci_cbm_dataset.txt (3448926, 2019-01-14)
_Datasets/gen.py (610, 2019-01-14)
_Datasets/mnist/ (0, 2019-01-14)
_Datasets/mnist/images/ (0, 2019-01-14)
_Datasets/mnist/images/0.png (304, 2019-01-14)
_Datasets/mnist/images/1.png (326, 2019-01-14)
_Datasets/mnist/images/10.png (290, 2019-01-14)
_Datasets/mnist/images/11.png (199, 2019-01-14)
_Datasets/mnist/images/12.png (337, 2019-01-14)
_Datasets/mnist/images/13.png (245, 2019-01-14)
_Datasets/mnist/images/14.png (254, 2019-01-14)
_Datasets/mnist/images/15.png (291, 2019-01-14)
_Datasets/mnist/images/16.png (319, 2019-01-14)
_Datasets/mnist/images/17.png (339, 2019-01-14)
_Datasets/mnist/images/18.png (292, 2019-01-14)
_Datasets/mnist/images/19.png (292, 2019-01-14)
_Datasets/mnist/images/2.png (323, 2019-01-14)
_Datasets/mnist/images/20.png (300, 2019-01-14)
_Datasets/mnist/images/21.png (312, 2019-01-14)
_Datasets/mnist/images/22.png (257, 2019-01-14)
_Datasets/mnist/images/23.png (238, 2019-01-14)
_Datasets/mnist/images/24.png (332, 2019-01-14)
_Datasets/mnist/images/25.png (192, 2019-01-14)
_Datasets/mnist/images/26.png (287, 2019-01-14)
_Datasets/mnist/images/27.png (298, 2019-01-14)
_Datasets/mnist/images/28.png (316, 2019-01-14)
_Datasets/mnist/images/29.png (348, 2019-01-14)
... ...
## Prererequisites
- Install python3
- Install virtualenv
- Download [hidden_layer_train_uni_split.zip](https://drive.google.com/file/d/1oTq_px8un_yL4BYwsNcJqofRpIYFtV3w/view?fbclid=IwAR1LnWR7-cQ_SE0BnR462n2J-aYml00GFNHmaYB99jbLZ9pNCpEYf0AXiIE) and [hidden_layer_test.csv](https://drive.google.com/file/d/1wvjx4Vo_n37WjRdSGoAgQX4_vXHhc5KS/view?usp=sharing)
## Directory & File Structure
```
finalproject
+-- rand1.py
+-- main.go and other go files
+-- mnist_training.sh
+-- client
| +-- main.go
demo
+-- hidden_layer_test.csv
+-- mnist_training.sh
+-- hidden_layer_train_split
| +-- hidden_layer_train_split_0.csv ~ hidden_layer_train_split_9.csv
```
## Place files
Before the training, we need to create a new directory demo/ like above and put the following directory & files
1. unzip [hidden_layer_train_uni_split.zip](https://drive.google.com/file/d/1oTq_px8un_yL4BYwsNcJqofRpIYFtV3w/view?fbclid=IwAR1LnWR7-cQ_SE0BnR462n2J-aYml00GFNHmaYB99jbLZ9pNCpEYf0AXiIE) and rename as hidden_layer_train_uni_split/ (to be dowloaded)
2. [hidden_layer_test.csv](https://drive.google.com/file/d/1wvjx4Vo_n37WjRdSGoAgQX4_vXHhc5KS/view?usp=sharing) (to be dowloaded)
3. mnist_training.sh (from finalproject)
## Execution
Run the mnist_training.sh in demo/ and you can observe the training at demo/A/A.out
```
./mnist_training.sh $mode $newpeers $byzantineMode
$mode: distributed/byzantine
$newpeers: Y/N (Y: new peers will join)
$byzantineMode: Y/N (Y: Peer E will serve as Byzantine node)
```
Web will be run at localhost:10000
- Test Simple distributed algorithm with the join of new peers
- ./mnist_training.sh distributed Y N
- Test Simple distributed algorithm with E as Byzantine node
- ./mnist_training.sh distributed N Y
- Test Byzantine algorithm with E as Byzantine node
- ./mnist_training.sh byzantine N Y
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