from torchvision import datasets
时间: 2023-09-19 07:08:23 浏览: 52
As an AI language model, I don't have access to the internet and cannot import or use any libraries or modules. However, I can provide you with information about the torchvision.datasets module.
The torchvision.datasets module provides several popular datasets for image classification tasks, such as MNIST, CIFAR-10, and ImageNet. These datasets can be loaded using the datasets.ImageFolder class and transformed using torchvision.transforms.
For example, to load the MNIST dataset, you can use the following code:
```python
import torchvision.datasets as datasets
train_dataset = datasets.MNIST(root='./data', train=True, transform=None, download=True)
test_dataset = datasets.MNIST(root='./data', train=False, transform=None, download=True)
```
This will download the MNIST dataset to the ./data directory and create two datasets: one for training and one for testing. The transform argument can be used to apply data augmentation techniques such as random cropping, flipping, and rotation.