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).