Hi all,
my data is stored in a three dimensional tensor (no of samples, length of timeseries, feature dimension).
Concatenating these different samples to one timeseries is in my case for methodological reasons not possible. Hence, I need a custom getitem method that accepts two indices: One to choose the sample and one to choose the index within that sample. What exactly do I have to change in addition? Do I have to write a custom collate_fn class as well? Which adjustments would be necessary there?
I have just realized that this would require to edit the _MapDatasetFetcher(_BaseDatasetFetcher) class since there is a function call:
data = [self.dataset[idx] for idx in possibly_batched_index
I.e., apparently it is not wanted that the dataset getitem method can use two indices. So do I even have a chance to implement my approach with two indices in the getitem method?
https://github.com/pytorch/pytorch/blob/master/torch/utils/data/_utils/fetch.pyhttps://github.com/pytorch/pytorch/blob/master/torch/utils/data/_utils/fetch.py 74