diff --git a/5.ipynb b/5.ipynb
new file mode 100644
index 0000000..eed6718
--- /dev/null
+++ b/5.ipynb
@@ -0,0 +1,236 @@
+{
+ "cells": [
+  {
+   "metadata": {},
+   "cell_type": "code",
+   "outputs": [],
+   "execution_count": null,
+   "source": "import torch",
+   "id": "d3cf166c4c1b5e28"
+  },
+  {
+   "metadata": {},
+   "cell_type": "code",
+   "outputs": [],
+   "execution_count": null,
+   "source": [
+    "# 连接操作\n",
+    "A = torch.ones(3, 3)\n",
+    "B = 2 * torch.ones(3, 3)\n",
+    "\n",
+    "C = torch.cat((A, B), 1)\n",
+    "C"
+   ],
+   "id": "8995ad1fc7997846"
+  },
+  {
+   "metadata": {},
+   "cell_type": "code",
+   "outputs": [],
+   "execution_count": null,
+   "source": [
+    "# 堆叠操作\n",
+    "A = torch.arange(0, 4)\n",
+    "B = torch.arange(4, 8)\n",
+    "\n",
+    "C = torch.stack((A, B), 1)\n",
+    "C"
+   ],
+   "id": "3bc82f18d81a5906"
+  },
+  {
+   "metadata": {},
+   "cell_type": "code",
+   "outputs": [],
+   "execution_count": null,
+   "source": [
+    "# 堆叠操作\n",
+    "A = torch.arange(6).reshape(2, 3)\n",
+    "B = torch.arange(7, 13).reshape(2, 3)\n",
+    "C = torch.stack((A, B), 2)\n",
+    "print(C.shape)\n",
+    "C"
+   ],
+   "id": "e33ad7cbb371544b"
+  },
+  {
+   "metadata": {},
+   "cell_type": "code",
+   "outputs": [],
+   "execution_count": null,
+   "source": [
+    "A = torch.tensor([[1, 2], [3, 4]])  # shape = (2, 2)\n",
+    "B = torch.tensor([[5, 6], [7, 8]])  # shape = (2, 2)\n",
+    "\n",
+    "S = torch.stack((A, B), dim=0)  # 在最外面添加一个新维度 → shape = (2, 2, 2)\n",
+    "print(S)\n",
+    "S = torch.stack((A, B), dim=1)  # 插入第1维 → shape = (2, 2, 2)\n",
+    "print(S)\n",
+    "S = torch.stack((A, B), dim=2)  # 插入第2维 → shape = (2, 2, 2)\n",
+    "print(S)"
+   ],
+   "id": "3ae1ac55280d699"
+  },
+  {
+   "metadata": {},
+   "cell_type": "code",
+   "outputs": [],
+   "execution_count": null,
+   "source": [
+    "# 切分操作\n",
+    "A = torch.arange(10) + 1\n",
+    "B = torch.chunk(A, 3, 0)\n",
+    "B"
+   ],
+   "id": "d05ece3cb5c8b356"
+  },
+  {
+   "metadata": {},
+   "cell_type": "code",
+   "outputs": [],
+   "execution_count": null,
+   "source": [
+    "# 切分操作\n",
+    "A = torch.arange(10) + 1\n",
+    "B = torch.split(A, 3, 0)\n",
+    "B"
+   ],
+   "id": "e6b4083b682fa47f"
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-06-12T11:53:25.664652Z",
+     "start_time": "2025-06-12T11:53:25.653976Z"
+    }
+   },
+   "cell_type": "code",
+   "source": [
+    "x = torch.arange(10)\n",
+    "torch.chunk(x, 3)\n",
+    "# 输出：3个 tensor，形状为 [4], [3], [3]"
+   ],
+   "id": "b59b47ca78552e94",
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(tensor([0, 1, 2, 3]), tensor([4, 5, 6, 7]), tensor([8, 9]))"
+      ]
+     },
+     "execution_count": 36,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "execution_count": 36
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-06-12T11:58:17.374940Z",
+     "start_time": "2025-06-12T11:58:17.367564Z"
+    }
+   },
+   "cell_type": "code",
+   "source": [
+    "# 索引操作\n",
+    "A = torch.arange(16).view(4, 4)\n",
+    "torch.index_select(A, 1, torch.tensor([1, 3]))"
+   ],
+   "id": "66be63810446009e",
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "tensor([[ 1,  3],\n",
+       "        [ 5,  7],\n",
+       "        [ 9, 11],\n",
+       "        [13, 15]])"
+      ]
+     },
+     "execution_count": 53,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "execution_count": 53
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-06-12T12:01:09.454904Z",
+     "start_time": "2025-06-12T12:01:09.448698Z"
+    }
+   },
+   "cell_type": "code",
+   "source": [
+    "A = torch.rand(5)\n",
+    "torch.masked_select(A, A > 0.3)"
+   ],
+   "id": "75ba3061d9102d3f",
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "tensor([0.5685, 0.4049, 0.4695])"
+      ]
+     },
+     "execution_count": 61,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "execution_count": 61
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-06-12T12:08:23.692196Z",
+     "start_time": "2025-06-12T12:08:23.683368Z"
+    }
+   },
+   "cell_type": "code",
+   "source": [
+    "# 提取出其中第一行的第一个，第二行的第一、第二个，第三行的最后一个\n",
+    "A = torch.tensor([[4, 5, 7], [3, 9, 8], [2, 3, 4]])\n",
+    "torch.diagonal(A)"
+   ],
+   "id": "ae81a2f0efa79d83",
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "tensor([4, 9, 4])"
+      ]
+     },
+     "execution_count": 62,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "execution_count": 62
+  }
+ ],
+ "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
+}
diff --git a/main.py b/main.py
index 97ae2e5..44f4c2e 100644
--- a/main.py
+++ b/main.py
@@ -1,4 +1,21 @@
 import torch
 import numpy as np
 
-print(torch.__version__)
\ No newline at end of file
+print(torch.__version__)
+
+
+A = torch.tensor([[1, 2, 3], [4, 5, 6]])  # shape = (2, 3)
+
+B0 = torch.stack([A, A], dim=0)
+print("dim=0:\n", B0)
+print("shape:", B0.shape)
+
+B1 = torch.stack([A, A], dim=1)
+print("dim=1:\n", B1)
+print("shape:", B1.shape)
+
+B2 = torch.stack([A, A], dim=2)
+print("dim=2:\n", B2)
+print("shape:", B2.shape)
+
+np.max()
\ No newline at end of file