From 5a024d321d805adcbbbbde61a95c9f43b11fc3d2 Mon Sep 17 00:00:00 2001
From: MengShiYao <511825078@qq.com>
Date: Thu, 9 Dec 2021 12:15:06 +0000
Subject: [PATCH] =?UTF-8?q?add=20code/2021=5Fautumn/=E5=AD=9F=E8=BD=BC?=
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---
 ...5\260\346\215\256\351\207\215\345\273\272" | 44 +++++++++++++++++++
 1 file changed, 44 insertions(+)
 create mode 100644 "code/2021_autumn/\345\255\237\350\275\274\345\260\247-\345\237\272\344\272\216\346\267\261\345\272\246\346\256\213\345\267\256\350\207\252\347\274\226\347\240\201\347\275\221\347\273\234\347\232\204AOD\346\225\260\346\215\256\351\207\215\345\273\272"

diff --git "a/code/2021_autumn/\345\255\237\350\275\274\345\260\247-\345\237\272\344\272\216\346\267\261\345\272\246\346\256\213\345\267\256\350\207\252\347\274\226\347\240\201\347\275\221\347\273\234\347\232\204AOD\346\225\260\346\215\256\351\207\215\345\273\272" "b/code/2021_autumn/\345\255\237\350\275\274\345\260\247-\345\237\272\344\272\216\346\267\261\345\272\246\346\256\213\345\267\256\350\207\252\347\274\226\347\240\201\347\275\221\347\273\234\347\232\204AOD\346\225\260\346\215\256\351\207\215\345\273\272"
new file mode 100644
index 0000000..e4d27af
--- /dev/null
+++ "b/code/2021_autumn/\345\255\237\350\275\274\345\260\247-\345\237\272\344\272\216\346\267\261\345\272\246\346\256\213\345\267\256\350\207\252\347\274\226\347\240\201\347\275\221\347\273\234\347\232\204AOD\346\225\260\346\215\256\351\207\215\345\273\272"
@@ -0,0 +1,44 @@
+import numpy as np
+import mindspore
+import mindspore.nn as nn
+from mindspore import tensor
+
+class RAE(nn.Cell):
+    def __init__(self):
+        super(RAE, self).__init__()
+        self.en1 = nn.Dense(11,128)
+        self.bn1 = nn.BatchNorm1d(128)
+        self.en2 = nn.Dense(128,64)
+        self.bn2 = nn.BatchNorm1d(64)
+        self.en3 = nn.Dense(64,32)
+        self.bn3 = nn.BatchNorm1d(32)
+        self.en4 = nn.Dense(32,16)
+        self.bn4 = nn.BatchNorm1d(16)
+        self.laten = nn.Dense(16,32)
+        self.bn5 = nn.BatchNorm1d(32)
+        self.de1 = nn.Dense(32,64)
+        self.bn6 = nn.BatchNorm1d(64)
+        self.de2 = nn.Dense(64, 128)
+        self.bn7 = nn.BatchNorm1d(128)
+        self.de3 = nn.Dense(128,11)
+        self.bn8 = nn.BatchNorm1d(11)
+        self.outlayer = nn.Dense(11,12)
+        self.relu = nn.ReLU()
+
+    def construct(self, x):
+        x1 = self.relu(self.bn1(self.en1(x)))
+        x2 = self.relu(self.bn2(self.en2(x1)))
+        x3 = self.relu(self.bn3(self.en3(x2)))
+        x4 = self.relu(self.bn4(self.en4(x3)))
+        x4 = self.relu(self.bn5(self.laten(x4)))
+        x4 = x4 + x3
+        x4 = self.relu(self.bn6(self.de1(x4)))
+        x4 = x4 + x2
+        x4 = self.relu(self.bn6(x4))
+        x4 = self.relu(self.bn7(self.de2(x4)))
+        x4 = x4 + x1
+        x4 = self.relu(self.bn7(x4))
+        x4 = self.relu(self.bn8(self.de3(x4)))
+        x4 = self.outlayer(x4)
+
+        return x4
-- 
Gitee