feat: add Jupyter notebook demonstrating Softmax and linear layer usage in PyTorch

17.ipynb

@@ -0,0 +1,108 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "id": "initial_id",
+   "metadata": {
+    "collapsed": true,
+    "ExecuteTime": {
+     "end_time": "2025-06-25T06:29:17.879978Z",
+     "start_time": "2025-06-25T06:29:16.365981Z"
+    }
+   },
+   "source": [
+    "import torch\n",
+    "import torch.nn as nn\n",
+    "\n",
+    "y = torch.randn(2)\n",
+    "print(y)\n",
+    "\n",
+    "m = nn.Softmax(dim=0)\n",
+    "out = m(y)\n",
+    "print(out)"
+   ],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "tensor([-0.9296, -0.1961])\n",
+      "tensor([0.3244, 0.6756])\n"
+     ]
+    }
+   ],
+   "execution_count": 1
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-06-25T06:31:29.348989Z",
+     "start_time": "2025-06-25T06:31:29.328174Z"
+    }
+   },
+   "cell_type": "code",
+   "source": [
+    "x = torch.randint(0, 255, (1, 128 * 128), dtype=torch.float32)\n",
+    "fc = nn.Linear(128 * 128, 2)\n",
+    "y = fc(x)\n",
+    "print(y)"
+   ],
+   "id": "7a0673da7cb52123",
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "tensor([[59.5330, 43.6760]], grad_fn=<AddmmBackward0>)\n"
+     ]
+    }
+   ],
+   "execution_count": 2
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-06-25T06:31:56.045399Z",
+     "start_time": "2025-06-25T06:31:56.041215Z"
+    }
+   },
+   "cell_type": "code",
+   "source": [
+    "output = nn.Softmax(dim=1)(y)\n",
+    "print(output)"
+   ],
+   "id": "a7135e5b93ea1669",
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "tensor([[1.0000e+00, 1.2984e-07]], grad_fn=<SoftmaxBackward0>)\n"
+     ]
+    }
+   ],
+   "execution_count": 3
+  }
+ ],
+ "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
+}