Converting our DatasetProviders to native torch.Dataset objects involve creating new torch.Tensors that can easily surpass available memory.
There are some strategies we can investigate to robustly minimize this issue, but it mainly involves using minibatches and compatible mechanisms. This requires Dataloader adapters, which would allow to convert to tensor only on __getindex__ access.
Converting our
DatasetProviders
to nativetorch.Dataset
objects involve creating newtorch.Tensors
that can easily surpass available memory.There are some strategies we can investigate to robustly minimize this issue, but it mainly involves using minibatches and compatible mechanisms. This requires Dataloader adapters, which would allow to convert to tensor only on
__getindex__
access.