Improve code documentation

README.md

@@ -1,4 +1,36 @@
-# matrix_standalone
-matrix standalone version
+#### Matrix Standalone (Federated Learning Project)
+A simple version of the horizontal federated learning project to achieve image classification learning. This project is simulated locally, and does not involve network communication details and failure processing. It only involves model aggregation functions, which can quickly verify the relevant algorithms and capabilities of federated learning.
 
-test edit
+### Operating Manual
+```shell
+python3 fl_integration.py
+```
+
+#### Simulation Ensemble Run(fl_integration) 
+
+It will define a server object and multiple client objects respectively to simulate horizontal federation training scenarios.
+
+
+#### Server（fl_server）
+
+Perform model aggregation on the local model uploaded by the selected client.
+
+
+
+#### Client（fl_client）
+
+Receive commands and global models from the server, and use local data to train local models.
+
+
+##### Functional screenshot
+
+<img src="./doc/img/20220507-024348.jpg" width="930">
+
+
+##### Results screenshot
+
+<img src="./doc/img/acc.jpg" width="930">
+
+<img src="./doc/img/loss.jpg" width="930">
+
+---

cifar10.py

@@ -2,6 +2,7 @@
 import matplotlib.pyplot as plt
 import tensorflow as tf
 
+
 # Take a look at some samples from the dataset: each class shows some
 def showPic(X_train, y_train):
     classes = ['plane', 'car', 'bird', 'cat', 'deer', 'dog', 'frog', 'horse', 'ship', 'truck']
@@ -20,6 +21,7 @@ def showPic(X_train, y_train):
                 plt.title(cls)
     plt.show()
 
+
 if __name__ == '__main__':
     (x_train, y_train), (x_test, y_test) = tf.keras.datasets.cifar10.load_data()
     showPic(x_train, y_train)

doc/result/centralized training

@@ -0,0 +1,150 @@
+/Users/jacky/opt/anaconda3/envs/learn/bin/python /Users/jacky/Documents/iit/CS584/homework/project1/main.py
+Files already downloaded and verified
+begin global model training 
+
+
+1 节点 1 K
+
+
+Global Epoch 0
+Epoch 0 done.
+Epoch 1 done.
+Epoch 2 done.
+server acc 0.13999999999999999
+Epoch 0, acc: 0.140000, loss: 9.019233
+
+Global Epoch 1
+Epoch 0 done.
+Epoch 1 done.
+Epoch 2 done.
+server acc 0.27999999999999997
+Epoch 1, acc: 0.280000, loss: 7.860937
+
+Global Epoch 2
+Epoch 0 done.
+Epoch 1 done.
+Epoch 2 done.
+server acc 0.49
+Epoch 2, acc: 0.490000, loss: 7.028633
+
+Global Epoch 3
+Epoch 0 done.
+Epoch 1 done.
+Epoch 2 done.
+server acc 1.2
+Epoch 3, acc: 1.200000, loss: 6.383927
+
+Global Epoch 4
+Epoch 0 done.
+Epoch 1 done.
+Epoch 2 done.
+server acc 2.23
+Epoch 4, acc: 2.230000, loss: 5.866239
+
+Global Epoch 5
+Epoch 0 done.
+Epoch 1 done.
+Epoch 2 done.
+server acc 4.5600000000000005
+Epoch 5, acc: 4.560000, loss: 5.445751
+
+Global Epoch 6
+Epoch 0 done.
+Epoch 1 done.
+Epoch 2 done.
+server acc 8.35
+Epoch 6, acc: 8.350000, loss: 5.043958
+
+Global Epoch 7
+Epoch 0 done.
+Epoch 1 done.
+Epoch 2 done.
+server acc 14.330000000000002
+Epoch 7, acc: 14.330000, loss: 4.656721
+
+Global Epoch 8
+Epoch 0 done.
+Epoch 1 done.
+Epoch 2 done.
+server acc 22.42
+Epoch 8, acc: 22.420000, loss: 4.259869
+
+Global Epoch 9
+Epoch 0 done.
+Epoch 1 done.
+Epoch 2 done.
+server acc 31.47
+Epoch 9, acc: 31.470000, loss: 3.858892
+
+Global Epoch 10
+Epoch 0 done.
+Epoch 1 done.
+Epoch 2 done.
+server acc 41.760000000000005
+Epoch 10, acc: 41.760000, loss: 3.459392
+
+Global Epoch 11
+Epoch 0 done.
+Epoch 1 done.
+Epoch 2 done.
+server acc 49.57
+Epoch 11, acc: 49.570000, loss: 3.077812
+
+Global Epoch 12
+Epoch 0 done.
+Epoch 1 done.
+Epoch 2 done.
+server acc 55.84
+Epoch 12, acc: 55.840000, loss: 2.712965
+
+Global Epoch 13
+Epoch 0 done.
+Epoch 1 done.
+Epoch 2 done.
+server acc 60.39
+Epoch 13, acc: 60.390000, loss: 2.394304
+
+Global Epoch 14
+Epoch 0 done.
+Epoch 1 done.
+Epoch 2 done.
+server acc 63.53
+Epoch 14, acc: 63.530000, loss: 2.099478
+
+Global Epoch 15
+Epoch 0 done.
+Epoch 1 done.
+Epoch 2 done.
+server acc 65.91
+Epoch 15, acc: 65.910000, loss: 1.842624
+
+Global Epoch 16
+Epoch 0 done.
+Epoch 1 done.
+Epoch 2 done.
+server acc 68.02
+Epoch 16, acc: 68.020000, loss: 1.625131
+
+Global Epoch 17
+Epoch 0 done.
+Epoch 1 done.
+Epoch 2 done.
+server acc 69.74000000000001
+Epoch 17, acc: 69.740000, loss: 1.444850
+
+Global Epoch 18
+Epoch 0 done.
+Epoch 1 done.
+Epoch 2 done.
+server acc 71.16
+Epoch 18, acc: 71.160000, loss: 1.292109
+
+Global Epoch 19
+Epoch 0 done.
+Epoch 1 done.
+Epoch 2 done.
+server acc 72.28
+Epoch 19, acc: 72.280000, loss: 1.169403
+
+
+进程已结束,退出代码0