routine

lab/6_MLP-pt.ipynb

@@ -0,0 +1,83 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "MultiLayerPerceptron(\n",
+      "  (hidden_layer1): Linear(in_features=10, out_features=20, bias=True)\n",
+      "  (hidden_layer2): Linear(in_features=20, out_features=10, bias=True)\n",
+      "  (output_layer): Linear(in_features=10, out_features=2, bias=True)\n",
+      "  (activation1): ReLU()\n",
+      "  (activation2): Sigmoid()\n",
+      ")\n"
+     ]
+    }
+   ],
+   "source": [
+    "import torch\n",
+    "import torch.nn as nn\n",
+    "\n",
+    "# 设置使用gpu7\n",
+    "device = torch.device(\"cuda:7\" if torch.cuda.is_available() else \"cpu\")\n",
+    "\n",
+    "# 定义一个简单的神经元层\n",
+    "class MultiLayerPerceptron(nn.Module):\n",
+    "    def __init__(self, input_size, hidden_size1, hidden_size2, output_size):\n",
+    "        super(MultiLayerPerceptron, self).__init__()\n",
+    "        self.hidden_layer1 = nn.Linear(input_size, hidden_size1)\n",
+    "        self.hidden_layer2 = nn.Linear(hidden_size1, hidden_size2)\n",
+    "        self.output_layer = nn.Linear(hidden_size2, output_size)\n",
+    "        \n",
+    "        # 定义不同的激活函数\n",
+    "        self.activation1 = nn.ReLU()  # 第一个隐藏层使用 ReLU\n",
+    "        self.activation2 = nn.Sigmoid()  # 第二个隐藏层使用 Sigmoid\n",
+    "\n",
+    "    def forward(self, x):\n",
+    "        # 第一个隐藏层及其激活函数\n",
+    "        x = self.hidden_layer1(x)\n",
+    "        x = self.activation1(x)\n",
+    "        \n",
+    "        # 第二个隐藏层及其激活函数\n",
+    "        x = self.hidden_layer2(x)\n",
+    "        x = self.activation2(x)\n",
+    "        \n",
+    "        # 输出层\n",
+    "        x = self.output_layer(x)\n",
+    "        return x\n",
+    "\n",
+    "# 创建一个MLP实例\n",
+    "mlp = MultiLayerPerceptron(input_size=10, hidden_size1=20, hidden_size2=10, output_size=2)\n",
+    "\n",
+    "# 打印模型结构\n",
+    "print(mlp)\n"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "ail",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}