How do you load MNIST images into Pytorch DataLoader?
The pytorch tutorial for data loading and processing is quite specific to one example, could someone help me with what the function should look like for a more generic simple loading of images?

Tutorial: http://pytorch.org/tutorials/beginner/data_loading_tutorial.html

My Data:

I have the MINST dataset as jpg's in the following folder structure. (I know I can just use the dataset class, but this is purely to see how to load simple images into pytorch without csv's or complex features).

The folder name is the label and the images are 28x28 png's in greyscale, no transformations required.

data
    train
        0
            3.png
            5.png
            13.png
            23.png
            ...
        1
            3.png
            10.png
            11.png
            ...
        2
            4.png
            13.png
            ...
        3
            8.png
            ...
        4
            ...
        5
            ...
        6
            ...
        7
            ...
        8
            ...
        9
            ...


Here's what I did for pytorch 0.4.1  (should still work in 1.3)

def load_dataset():
    data_path = 'data/train/'
    train_dataset = torchvision.datasets.ImageFolder(
        root=data_path,
        transform=torchvision.transforms.ToTensor()
    )
    train_loader = torch.utils.data.DataLoader(
        train_dataset,
        batch_size=64,
        num_workers=0,
        shuffle=True
    )
    return train_loader

for batch_idx, (data, target) in enumerate(load_dataset()):
    #train network

