What are PyTorch dataset classes?

What are PyTorch dataset classes?

PyTorch dataset classes are used to represent and manage datasets in PyTorch. They help in loading, transforming, and accessing data efficiently.

Can you give me an example of how to create a custom dataset class?

Sure! You can create a custom dataset class by inheriting from torch.utils.data.Dataset and implementing the __len__ and __getitem__ methods.

What libraries do I need to import to create a dataset class?

You need to import torch and torch.utils.data. You might also want to import other libraries for data manipulation, like pandas or numpy.

How do I use the DataLoader with my custom dataset?

You can use the DataLoader class from torch.utils.data by passing your custom dataset instance to it, along with parameters like batch size.