深度学习实例1_mnist识别手写数字——自学笔记

import torch
import numpy as np
from matplotlib import pyplot as plt
from torch.utils.data import DataLoader
from torchvision import transforms
from torchvision import datasets
import torch.nn.functional as F
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导入mnist数据集，包括训练集图片、训练集标签、测试集图片、测试集标签

官方网站：http://yann.lecun.com/exdb/mnist/

直接下载下来的数据是无法通过解压或者应用程序打开的，因为这些文件不是任何标准的图像格式而是以字节的形式进行存储的，所以必须编写程序来打开它。

# Step1：归一化，softmax归一化指数函数(https://blog.csdn.net/lz_peter/article/details/84574716),其中0.1307是mean均值和0.3081是std标准差
transform = transforms.Compose([transforms.ToTensor(), transforms.Normalize((0.1307,), (0.3081,))])
#数据归一化:使各种特征值处于同一数值级，减少方差大的特征影响，使得模型更准确，加快收敛速度

# Step2：下载/获取数据集，其中root为数据集存放路径，train=True即训练集否则为测试集。
train_dataset = datasets.MNIST(root='./data/mnist', train=True, download=True, transform=transform)
test_dataset = datasets.MNIST(root='./data/mnist', train=False, download=True, transform=transform)  # train=True训练集，=False测试集
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Downloading http://yann.lecun.com/exdb/mnist/train-images-idx3-ubyte.gz
Failed to download (trying next):
HTTP Error 403: Forbidden

Downloading https://ossci-datasets.s3.amazonaws.com/mnist/train-images-idx3-ubyte.gz
Downloading https://ossci-datasets.s3.amazonaws.com/mnist/train-images-idx3-ubyte.gz to ./data/mnist/MNIST/raw/train-images-idx3-ubyte.gz


100%|██████████| 9912422/9912422 [00:00<00:00, 16116778.16it/s]


Extracting ./data/mnist/MNIST/raw/train-images-idx3-ubyte.gz to ./data/mnist/MNIST/raw

Downloading http://yann.lecun.com/exdb/mnist/train-labels-idx1-ubyte.gz
Failed to download (trying next):
HTTP Error 403: Forbidden

Downloading https://ossci-datasets.s3.amazonaws.com/mnist/train-labels-idx1-ubyte.gz
Downloading https://ossci-datasets.s3.amazonaws.com/mnist/train-labels-idx1-ubyte.gz to ./data/mnist/MNIST/raw/train-labels-idx1-ubyte.gz


100%|██████████| 28881/28881 [00:00<00:00, 476945.98it/s]


Extracting ./data/mnist/MNIST/raw/train-labels-idx1-ubyte.gz to ./data/mnist/MNIST/raw

Downloading http://yann.lecun.com/exdb/mnist/t10k-images-idx3-ubyte.gz
Failed to download (trying next):
HTTP Error 403: Forbidden

Downloading https://ossci-datasets.s3.amazonaws.com/mnist/t10k-images-idx3-ubyte.gz
Downloading https://ossci-datasets.s3.amazonaws.com/mnist/t10k-images-idx3-ubyte.gz to ./data/mnist/MNIST/raw/t10k-images-idx3-ubyte.gz


100%|██████████| 1648877/1648877 [00:00<00:00, 4377326.53it/s]


Extracting ./data/mnist/MNIST/raw/t10k-images-idx3-ubyte.gz to ./data/mnist/MNIST/raw

Downloading http://yann.lecun.com/exdb/mnist/t10k-labels-idx1-ubyte.gz
Failed to download (trying next):
HTTP Error 403: Forbidden

Downloading https://ossci-datasets.s3.amazonaws.com/mnist/t10k-labels-idx1-ubyte.gz
Downloading https://ossci-datasets.s3.amazonaws.com/mnist/t10k-labels-idx1-ubyte.gz to ./data/mnist/MNIST/raw/t10k-labels-idx1-ubyte.gz


100%|██████████| 4542/4542 [00:00<00:00, 4205414.74it/s]

Extracting ./data/mnist/MNIST/raw/t10k-labels-idx1-ubyte.gz to ./data/mnist/MNIST/raw
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Step3：实例化一个dataset后，然后用Dataloader 包起来，即载入数据集。这里的batch_size为超参数，详见第五大节；shuffle=True即打乱数据集，这里我们打乱训练集进行训练，而对测试集进行顺序测试。

batch_size=64
train_loader &#
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