From 7e8fea0a3bf0abb4bbdf64fd93992107095e00d6 Mon Sep 17 00:00:00 2001 From: typingbugs Date: Tue, 24 Oct 2023 16:35:58 +0800 Subject: [PATCH] =?UTF-8?q?=E5=AE=9E=E9=AA=8C2=E4=BB=BB=E5=8A=A13code?= =?UTF-8?q?=E5=AE=8C=E6=88=90?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- Lab2/前馈神经网络实验.ipynb | 60 ++++++++++++++++++++++--------------- requirements.txt | 11 +++---- 2 files changed, 42 insertions(+), 29 deletions(-) diff --git a/Lab2/前馈神经网络实验.ipynb b/Lab2/前馈神经网络实验.ipynb index 88c9a52..e7db924 100644 --- a/Lab2/前馈神经网络实验.ipynb +++ b/Lab2/前馈神经网络实验.ipynb @@ -22,13 +22,13 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "实验环境：\r\n", - "- OS：Ubuntu 22.04 (Kernel: 6.2.0-34-generic)\r\n", - "- CPU：12th Gen Intel(R) Core(TM) i7-12700H\r\n", - "- GPU：NVIDIA GeForce RTX 3070 Ti Laptop\r\n", - "- cuda: 12.2\r\n", - "- conda: miniconda 23.9.0\r\n", - "- python：3.10.13\r\n", + "实验环境：\n", + "- OS：Ubuntu 22.04 (Kernel: 6.2.0-34-generic)\n", + "- CPU：12th Gen Intel(R) Core(TM) i7-12700H\n", + "- GPU：NVIDIA GeForce RTX 3070 Ti Laptop\n", + "- cuda: 12.2\n", + "- conda: miniconda 23.9.0\n", + "- python：3.10.13\n", "- pytorch：2.1.0" ] }, @@ -36,12 +36,24 @@ "cell_type": "code", "execution_count": 1, "metadata": {}, - "outputs": [], + "outputs": [ + { + "ename": "ModuleNotFoundError", + "evalue": "No module named 'matplotlib'", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mModuleNotFoundError\u001b[0m Traceback (most recent call last)", + "\u001b[1;32m/home/kejingfan/Codedir/School-DeepLearningCourse-Lab/Lab2/前馈神经网络实验.ipynb Cell 3\u001b[0m line \u001b[0;36m8\n\u001b[1;32m 6\u001b[0m \u001b[39mfrom\u001b[39;00m \u001b[39mtorch\u001b[39;00m \u001b[39mimport\u001b[39;00m nn\n\u001b[1;32m 7\u001b[0m \u001b[39mfrom\u001b[39;00m \u001b[39mtorchvision\u001b[39;00m \u001b[39mimport\u001b[39;00m datasets, transforms\n\u001b[0;32m----> 8\u001b[0m \u001b[39mimport\u001b[39;00m \u001b[39mmatplotlib\u001b[39;00m\u001b[39m.\u001b[39;00m\u001b[39mpyplot\u001b[39;00m \u001b[39mas\u001b[39;00m \u001b[39mplt\u001b[39;00m\n", + "\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'matplotlib'" + ] + } + ], "source": [ "import time\n", "import numpy as np\n", "import torch\n", - "from torch.nn.functional import one_hot, softmax\n", + "from torch.nn.functional import *\n", "from torch.utils.data import Dataset, DataLoader\n", "from torch import nn\n", "from torchvision import datasets, transforms\n", @@ -70,21 +82,21 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "首先生成数据集。\r\n", - "\r\n", - "一共有3个数据集：\r\n", - "\r\n", - "1. 回归任务数据集。\r\n", - " - 生成单个数据集。\r\n", - " - 数据集的大小为$10000$且训练集大小为$7000$，测试集大小为$3000$。\r\n", - " - 数据集的样本特征维度$p$为$500$，且服从如下的高维线性函数：$y = 0.028 + \\sum_{p}^{i=1}0.0056 x_i + \\epsilon $。\r\n", - "2. 二分类任务数据集。\r\n", - " - 共生成两个数据集。\r\n", - " - 两个数据集的大小均为$10000$且训练集大小为$7000$，测试集大小为$3000$。\r\n", - " - 两个数据集的样本特征$x$的维度均为$200$，且分别服从均值互为相反数且方差相同的正态分布。\r\n", - " - 两个数据集的样本标签分别为$0$和$1$。\r\n", - "3. MNIST手写体数据集。\r\n", - " - 该数据集包含$60,000$个用于训练的图像样本和$10,000$个用于测试的图像样本。\r\n", + "首先生成数据集。\n", + "\n", + "一共有3个数据集：\n", + "\n", + "1. 回归任务数据集。\n", + " - 生成单个数据集。\n", + " - 数据集的大小为$10000$且训练集大小为$7000$，测试集大小为$3000$。\n", + " - 数据集的样本特征维度$p$为$500$，且服从如下的高维线性函数：$y = 0.028 + \\sum_{p}^{i=1}0.0056 x_i + \\epsilon $。\n", + "2. 二分类任务数据集。\n", + " - 共生成两个数据集。\n", + " - 两个数据集的大小均为$10000$且训练集大小为$7000$，测试集大小为$3000$。\n", + " - 两个数据集的样本特征$x$的维度均为$200$，且分别服从均值互为相反数且方差相同的正态分布。\n", + " - 两个数据集的样本标签分别为$0$和$1$。\n", + "3. MNIST手写体数据集。\n", + " - 该数据集包含$60,000$个用于训练的图像样本和$10,000$个用于测试的图像样本。\n", " - 图像是固定大小（$28\\times 28$像素），其值为$0$到$1$。为每个图像都被平展并转换为$784$（$28 \\times 28$）个特征的一维numpy数组。 " ] }, diff --git a/requirements.txt b/requirements.txt index c02bc74..9c6529c 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,8 +1,9 @@ -black==23.9.1 -ipdb==0.13.13 -jupyter==1.0.0 -numpy==1.26.0 +black +ipdb +jupyter +numpy torch==2.1.0 torchaudio==2.1.0 torchvision==0.16.0 -tqdm==4.66.1 \ No newline at end of file +tqdm +matplotlib \ No newline at end of file