import torch
from torch import nn
from torch.utils.data import DataLoader
from torchvision import datasets  #这里指定当前数据集为torchvision
from torchvision.transforms import ToTensor, Lambda, Compose
import matplotlib.pyplot as plt

1. DataLoader

是Pytorch用来加载数据的常用的类，返回一个可遍历的数据集对象

传入参数：

• dataset (Dataset) – dataset from which to load the data.

• batch_size (int, optional) – how many samples per batch to load (default: 1).

• shuffle (bool, optional) – set to True to have the data reshuffled at every epoch (default: False)

2. torchvision

是一个包，里面包含了很多常用的视觉数据集。类似的还有torchtext, torchaudio,...

# Download training data from open datasets.
training_data = datasets.FashionMNIST(
    root="data",
    train=True,
    download=True,
    transform=ToTensor(),
)

# Download test data from open datasets.
test_data = datasets.FashionMNIST(
    root="data",
    train=False,
    download=True,
    transform=ToTensor(),
)

1. torchvision.datasets里的所有datasets（这里是FashionMNIST）都是torch.utils.data.Dataset的子类，因为这些子类都写了__getitem__和__len__，所以可以被传入torch.utils.data.DataLoader。

 2. FashionMNIST的属性有：

• root (string) – Root directory of dataset where FashionMNIST/processed/training.pt and FashionMNIST/processed/test.pt exist.

• train (bool, optional) – If True, creates dataset from training.pt, otherwise from test.pt.

• download (bool, optional) – If true, downloads the dataset from the internet and puts it in root directory. If dataset is already downloaded, it is not downloaded again.

• transform (callable, optional) – A function/transform that takes in an PIL image and returns a transformed version. E.g, transforms.RandomCrop

Pytorch 第一个程序