feat: add Jupyter notebook for TensorBoard integration and logging example

15.ipynb

@@ -0,0 +1,126 @@
+{
+ "cells": [
+  {
+   "metadata": {},
+   "cell_type": "code",
+   "source": "!pip install tensorboard",
+   "id": "add52c783768e27a",
+   "outputs": [],
+   "execution_count": null
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-06-20T09:23:44.953818Z",
+     "start_time": "2025-06-20T09:23:44.941696Z"
+    }
+   },
+   "cell_type": "code",
+   "source": [
+    "%load_ext tensorboard\n",
+    "%tensorboard --logdir runs --host 0.0.0.0 --port 6006"
+   ],
+   "id": "6d148c29e2c0fbbe",
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "The tensorboard extension is already loaded. To reload it, use:\n",
+      "  %reload_ext tensorboard\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "Reusing TensorBoard on port 6006 (pid 414), started 0:24:42 ago. (Use '!kill 414' to kill it.)"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ],
+      "text/html": [
+       "\n",
+       "      <iframe id=\"tensorboard-frame-42c02cf9641fd4a7\" width=\"100%\" height=\"800\" frameborder=\"0\">\n",
+       "      </iframe>\n",
+       "      <script>\n",
+       "        (function() {\n",
+       "          const frame = document.getElementById(\"tensorboard-frame-42c02cf9641fd4a7\");\n",
+       "          const url = new URL(\"/\", window.location);\n",
+       "          const port = 6006;\n",
+       "          if (port) {\n",
+       "            url.port = port;\n",
+       "          }\n",
+       "          frame.src = url;\n",
+       "        })();\n",
+       "      </script>\n",
+       "    "
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "execution_count": 12
+  },
+  {
+   "cell_type": "code",
+   "id": "initial_id",
+   "metadata": {
+    "collapsed": true,
+    "ExecuteTime": {
+     "end_time": "2025-06-20T09:23:36.713794Z",
+     "start_time": "2025-06-20T09:23:32.977971Z"
+    }
+   },
+   "source": [
+    "from torch.utils.tensorboard import SummaryWriter\n",
+    "import numpy as np\n",
+    "\n",
+    "# 创建一个SummaryWriter对象\n",
+    "writer = SummaryWriter()\n",
+    "\n",
+    "for n_iter in range(100):\n",
+    "    writer.add_scalar('Loss/train', np.random.random(), n_iter)\n",
+    "    writer.add_scalar('Loss/test', np.random.random(), n_iter)\n",
+    "    writer.add_scalar('Accuracy/train', np.random.random(), n_iter)\n",
+    "    writer.add_scalar('Accuracy/test', np.random.random(), n_iter)\n",
+    "\n",
+    "img = np.zeros((3, 100, 100))\n",
+    "img[0] = np.arange(0, 10000).reshape(100, 100) / 10000\n",
+    "img[1] = np.arange(0, 10000).reshape(100, 100) / 10000\n",
+    "\n",
+    "writer.add_image('my_image', img, 0)\n",
+    "writer.close()"
+   ],
+   "outputs": [],
+   "execution_count": 11
+  }
+ ],
+ "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
+}