What is the recommended way to draw a single random batch with replacement from a DataLoader nowadays?
A very similar question has been asked here, but I don’t understand how to actually extract the data points. I would expect something like:
x_batch, y_batch = train_loader.sample(batch_size=64, replacement=True)
I normally use this:
train_loader = DataLoader(train_dataset, batch_size=64, ...)
iterator = iter(train_loader)
x_batch, y_batch = iterator.next()
How do I properly incorporate random sampling with replacement with this method?
I tried the following, but it does not work:
rand_sampler = torch.utils.data.RandomSampler(train_set, num_samples=64, replacement=True)
train_sampler = torch.utils.data.DataLoader(train, batch_size=64, sampler=rand_sampler)
When I try to do what you suggested, I get the following error:
> iterator = iter(train_sampler)
*** TypeError: 'function' object is not subscriptable
Your code works for me.
You might need to pass
train_set instead of