diff --git a/04.ipynb b/04.ipynb index dad047e..40aa68c 100644 --- a/04.ipynb +++ b/04.ipynb @@ -6,8 +6,8 @@ "metadata": { "collapsed": true, "ExecuteTime": { - "end_time": "2025-06-11T15:26:24.930498Z", - "start_time": "2025-06-11T15:26:24.925343Z" + "end_time": "2025-06-12T02:34:22.530839Z", + "start_time": "2025-06-12T02:34:20.159404Z" } }, "source": [ @@ -23,18 +23,18 @@ "'2.2.1'" ] }, - "execution_count": 4, + "execution_count": 1, "metadata": {}, "output_type": "execute_result" } ], - "execution_count": 4 + "execution_count": 1 }, { "metadata": { "ExecuteTime": { - "end_time": "2025-06-11T15:30:24.600025Z", - "start_time": "2025-06-11T15:30:24.594879Z" + "end_time": "2025-06-12T02:34:24.139479Z", + "start_time": "2025-06-12T02:34:24.116052Z" } }, "cell_type": "code", @@ -55,13 +55,13 @@ ] } ], - "execution_count": 11 + "execution_count": 2 }, { "metadata": { "ExecuteTime": { - "end_time": "2025-06-11T15:30:58.264992Z", - "start_time": "2025-06-11T15:30:58.260725Z" + "end_time": "2025-06-12T02:34:26.619937Z", + "start_time": "2025-06-12T02:34:26.608636Z" } }, "cell_type": "code", @@ -81,13 +81,13 @@ ] } ], - "execution_count": 13 + "execution_count": 3 }, { "metadata": { "ExecuteTime": { - "end_time": "2025-06-11T15:33:27.945096Z", - "start_time": "2025-06-11T15:33:27.939574Z" + "end_time": "2025-06-12T02:34:28.340829Z", + "start_time": "2025-06-12T02:34:28.333276Z" } }, "cell_type": "code", @@ -111,18 +111,211 @@ ] } ], - "execution_count": 18 + "execution_count": 4 }, { - "metadata": {}, + "metadata": { + "ExecuteTime": { + "end_time": "2025-06-12T02:34:37.031549Z", + "start_time": "2025-06-12T02:34:36.991394Z" + } + }, "cell_type": "code", - "outputs": [], - "execution_count": null, "source": [ "x = torch.rand(2, 3, 5)\n", + "print(x.shape)\n", + "print(x)" + ], + "id": "774add1439f9aa94", + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "torch.Size([2, 3, 5])\n", + "tensor([[[0.1437, 0.3582, 0.4219, 0.4514, 0.6537],\n", + " [0.0089, 0.5737, 0.0201, 0.7728, 0.1827],\n", + " [0.6573, 0.1262, 0.0877, 0.2302, 0.0151]],\n", + "\n", + " [[0.0757, 0.7126, 0.4238, 0.0535, 0.0578],\n", + " [0.4909, 0.5616, 0.7342, 0.7925, 0.8879],\n", + " [0.3011, 0.1606, 0.2856, 0.8165, 0.4100]]])\n" + ] + } + ], + "execution_count": 6 + }, + { + "metadata": { + "ExecuteTime": { + "end_time": "2025-06-12T02:34:48.128975Z", + "start_time": "2025-06-12T02:34:48.116080Z" + } + }, + "cell_type": "code", + "source": [ + "# 矩阵转秩\n", + "x = x.permute(2, 1, 0)\n", + "print(x.shape)\n", + "print(x)" + ], + "id": "ceb1debce1c62ffd", + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "torch.Size([5, 3, 2])\n", + "tensor([[[0.1437, 0.0757],\n", + " [0.0089, 0.4909],\n", + " [0.6573, 0.3011]],\n", + "\n", + " [[0.3582, 0.7126],\n", + " [0.5737, 0.5616],\n", + " [0.1262, 0.1606]],\n", + "\n", + " [[0.4219, 0.4238],\n", + " [0.0201, 0.7342],\n", + " [0.0877, 0.2856]],\n", + "\n", + " [[0.4514, 0.0535],\n", + " [0.7728, 0.7925],\n", + " [0.2302, 0.8165]],\n", + "\n", + " [[0.6537, 0.0578],\n", + " [0.1827, 0.8879],\n", + " [0.0151, 0.4100]]])\n" + ] + } + ], + "execution_count": 7 + }, + { + "metadata": { + "ExecuteTime": { + "end_time": "2025-06-12T02:36:03.393949Z", + "start_time": "2025-06-12T02:36:03.381874Z" + } + }, + "cell_type": "code", + "source": [ + "x = torch.rand(2, 3, 4)\n", + "x = x.transpose(1, 0)\n", "print(x.shape)" ], - "id": "774add1439f9aa94" + "id": "e56528fc1753cf04", + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "torch.Size([3, 2, 4])\n" + ] + } + ], + "execution_count": 8 + }, + { + "metadata": { + "ExecuteTime": { + "end_time": "2025-06-12T02:49:57.093978Z", + "start_time": "2025-06-12T02:49:57.088700Z" + } + }, + "cell_type": "code", + "source": [ + "x = torch.rand(4, 4)\n", + "x = x.view(2, 8)\n", + "x = x.permute(1, 0)\n", + "# x.view(4,4) # 不能直接用view，因为view需要连续的内存\n", + "x.reshape(4, 4)" + ], + "id": "74df80d1396ec1d3", + "outputs": [ + { + "data": { + "text/plain": [ + "torch.Size([2, 8])" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "execution_count": 13 + }, + { + "metadata": { + "ExecuteTime": { + "end_time": "2025-06-12T03:34:30.576671Z", + "start_time": "2025-06-12T03:34:30.569216Z" + } + }, + "cell_type": "code", + "source": [ + "# 增减维度\n", + "x = torch.rand(2, 1, 3)\n", + "print(x)\n", + "x = x.squeeze(1) # 去掉维度为1的维度\n", + "\n", + "print(x.shape)\n", + "print(x)\n", + "\n" + ], + "id": "f5009aa3b8b1335c", + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "tensor([[[0.0287, 0.7995, 0.4072]],\n", + "\n", + " [[0.4378, 0.6384, 0.2777]]])\n", + "torch.Size([2, 3])\n", + "tensor([[0.0287, 0.7995, 0.4072],\n", + " [0.4378, 0.6384, 0.2777]])\n" + ] + } + ], + "execution_count": 29 + }, + { + "metadata": { + "ExecuteTime": { + "end_time": "2025-06-12T03:42:20.284801Z", + "start_time": "2025-06-12T03:42:20.271042Z" + } + }, + "cell_type": "code", + "source": [ + "# 增减维度\n", + "x = torch.rand(2, 1, 3)\n", + "print(x)\n", + "x = x.unsqueeze() # 去掉维度为1的维度\n", + "\n", + "print(x.shape)\n", + "print(x)\n", + "\n" + ], + "id": "dc138eb85bed2f3e", + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "tensor([[[0.4243, 0.1581, 0.4620]],\n", + "\n", + " [[0.8510, 0.5490, 0.7694]]])\n", + "torch.Size([2, 1, 1, 3])\n", + "tensor([[[[0.4243, 0.1581, 0.4620]]],\n", + "\n", + "\n", + " [[[0.8510, 0.5490, 0.7694]]]])\n" + ] + } + ], + "execution_count": 30 } ], "metadata": { diff --git a/main.py b/main.py index 0a8866d..97ae2e5 100644 --- a/main.py +++ b/main.py @@ -1,4 +1,4 @@ import torch import numpy as np -torch.__version__ \ No newline at end of file +print(torch.__version__) \ No newline at end of file