Hi,
I’m trying to understand the difference between a Dataset and DataLoader for a specific case. The DataLoader allows us to specify a sampler.
Lets say I’ve a sampler that looks like the following.
class MyAwesomeSampler(Sampler):
    def __init__(self, indices):
        self.indices = indices
    
    def __iter__(self):
        return iter(self.indices)

    def __len__(self):
        return len(self.indices)

and then I give plug an instance of MyAwesomeSampler to the input of DataLoader
How is this different from using Subset(mydataset, indices) where the indices are the same as above.
Does this make any difference in Dataset objects with data-augmentation (eg any of the image datasets in torchvision).