feat: rename Jupyter notebook and add custom Dataset class implementation

06.ipynb

@@ -0,0 +1,138 @@
+{
+ "cells": [
+  {
+   "metadata": {},
+   "cell_type": "markdown",
+   "source": [
+    "### Dataset类\n",
+    "其实这就表示，无论使用自定义的数据集，还是官方为我们封装好的数据集，其本质都是继承了Dataset类。而在继承Dataset类时，至少需要重写以下几个方法：\n",
+    "\n",
+    "* \\_\\_init\\_\\_()：构造函数，可自定义数据读取方法以及进行数据预处理；\n",
+    "* \\_\\_len\\_\\_()：返回数据集大小；\n",
+    "* \\_\\_getitem\\_\\_()：索引数据集中的某一个数据。"
+   ],
+   "id": "6f460291da56d507"
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-06-12T12:58:38.694696Z",
+     "start_time": "2025-06-12T12:58:38.690734Z"
+    }
+   },
+   "cell_type": "code",
+   "source": [
+    "import torch\n",
+    "from torch.utils.data import Dataset\n",
+    "\n",
+    "\n",
+    "class MyDataset(Dataset):\n",
+    "    # 构造函数\n",
+    "    def __init__(self, data_tensor, target_tensor):\n",
+    "        self.data_tensor = data_tensor\n",
+    "        self.target_tensor = target_tensor\n",
+    "\n",
+    "    # 返回数据集大小\n",
+    "    def __len__(self):\n",
+    "        return self.data_tensor.size(0)\n",
+    "\n",
+    "    # 返回索引的数据与标签\n",
+    "    def __getitem__(self, idx):\n",
+    "        return self.data_tensor[idx], self.target_tensor[idx]"
+   ],
+   "id": "1244f4325aad0ac5",
+   "outputs": [],
+   "execution_count": 64
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-06-12T12:59:08.444392Z",
+     "start_time": "2025-06-12T12:59:08.435084Z"
+    }
+   },
+   "cell_type": "code",
+   "source": [
+    "# 生成数据\n",
+    "data_tensor = torch.randn(10, 3)\n",
+    "target_tensor = torch.randint(2, (10,)) # 二分类任务\n",
+    "\n",
+    "print(data_tensor)\n",
+    "print(target_tensor)"
+   ],
+   "id": "e2f8ad8dc637791a",
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "tensor([[-1.1016,  0.8803,  1.3645],\n",
+      "        [ 0.6674,  0.4500,  0.0367],\n",
+      "        [ 1.3528,  0.2438,  0.4721],\n",
+      "        [-1.3651, -1.1315,  0.0299],\n",
+      "        [ 1.4538,  1.3622, -0.5165],\n",
+      "        [ 0.7515,  0.6168, -0.9036],\n",
+      "        [ 1.3542, -0.3779, -1.2439],\n",
+      "        [-0.4588, -0.2233, -0.3531],\n",
+      "        [-0.0515,  0.8951,  0.3544],\n",
+      "        [ 0.0181,  0.4075, -2.0888]])\n",
+      "tensor([0, 0, 1, 0, 0, 1, 1, 1, 1, 0])\n"
+     ]
+    }
+   ],
+   "execution_count": 66
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-06-12T12:59:25.092189Z",
+     "start_time": "2025-06-12T12:59:25.085985Z"
+    }
+   },
+   "cell_type": "code",
+   "source": [
+    "# 创建数据集\n",
+    "my_dataset = MyDataset(data_tensor, target_tensor)\n",
+    "\n",
+    "# 查看数据集大小\n",
+    "print(\"dataset size：\",len(my_dataset))\n",
+    "\n",
+    "# 使用索引获取数据\n",
+    "print(\"data:\", my_dataset[0])  # 获取第一个数据"
+   ],
+   "id": "cd8f86852f54b0c5",
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "dataset size： 10\n",
+      "data: (tensor([-1.1016,  0.8803,  1.3645]), tensor(0))\n"
+     ]
+    }
+   ],
+   "execution_count": 67
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 2
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython2",
+   "version": "2.7.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}