diff --git a/.main.cpp.swp b/.main.cpp.swp
new file mode 100644
index 0000000000000000000000000000000000000000..0fb75dfcf4cdb2beb55de61b5683f5dc6a6bac8e
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diff --git a/README.md b/README.md
index f4e6d8e70c8ef0015246fd443c7f58775db0d40d..c102bcb4065b4f23054d229ca4fd4227f83bcd02 100644
--- a/README.md
+++ b/README.md
@@ -1,5 +1,4 @@
 <div align=center><img src="./picture/01.svg"/></div>
-
 # Edge-Engine
 
 ## Edge : 一个开源的科学计算引擎
@@ -62,6 +61,20 @@ make install
 ➜  edge-computing-engine git:(master) ✗ ./main
 ```
 
+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:
@@ -500,7 +513,6 @@ Something :
 <div align = center><img src = './picture/星月.svg'></div>
 
 
-
  个人小站:[极度空间](http://likedge.top/)
 
 作者邮箱:zk@likedge.top | edge@ibooker.org.cn
diff --git a/grad_edge/.matrix_grad.h.swp b/grad_edge/.matrix_grad.h.swp
index d4d10fe61d8a3482e199c94a633b8fc2276dfbae..e0aac8fc560bf9b1b1ac30e7164a0a95ae7666c3 100644
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diff --git a/image-20200128154352842.png b/image-20200128154352842.png
new file mode 100644
index 0000000000000000000000000000000000000000..ae8b354d4479828bcbd2e233bc87a9ffc880c512
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diff --git a/ma b/ma
index 8e2cab1a3d00c623440032aa6a0f86ddb3bfc400..d55d9ec4724f7ddf8775cc4a95a98817f369e28e 100755
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diff --git a/main.cpp b/main.cpp
index 1f87690d8f8c3dd0036fff2e2ca7ea84e0425290..168a5fbcd3b5806db3c8cc8e09651467e912cf62 100644
--- a/main.cpp
+++ b/main.cpp
@@ -32,25 +32,13 @@ int main()
 {
 	cout<<"------------autodiff for neraul network-----------"<<endl;
 	Matrix data_mine = CreateMatrix(2,1);
-	change_va(data_mine,0,0,0.55);
-	change_va(data_mine,1,0,0.2);
 	cout<<"data mine"<<endl;
 	cout_mat(data_mine);
 	cout<<"data mine"<<endl;
 	Matrix label = CreateRandMat(2,1);
-    change_va(label,0,0,0.4);
-	change_va(label,1,0,0.8);
 	Matrix weight1 = CreateRandMat(2,2);
-	change_va(weight1,0,0,0.1);
-	change_va(weight1,0,1,0.2);
-	change_va(weight1,1,0,0.2);
-	change_va(weight1,1,1,0.4);
 	Matrix bais1 = ones(2,1);
 	Matrix weight2 = CreateRandMat(2,2);
-	change_va(weight2,0,0,0.5);
-	change_va(weight2,1,0,0.6);
-    change_va(weight2,0,1,0.7);
-	change_va(weight2,1,1,0.8);
 	Matrix bais2 = ones(2,1);
 	for(int epoch = 0;epoch<1;epoch++)
 	{