Deep Learning with PyTorch Quick Start Guide

DataLoader

We will see that in a deep learning model, we may not always want to load images one at a time or load them in the same order each time. For this, and other reasons, it is often better to use the torch.utils.data.DataLoader object. DataLoader provides a multipurpose iterator to sample the data in a specified way, such as in batches, or shuffled. It is also a convenient place to assign workers in multiprocessor environments. 

In the following example, we sample the dataset in batches of four samples each:

Here DataLoader returns a tuple of two tensors. The first tensor contains the image data of all four images in the batch. The ...