Torch Dataloader gives torch.Tensor as ouput

[ptrblck]

I think the main problem is:

@MikeTensor

My return from the CustomDataset would be a pandas.DF (which doesn’t work with the collate_fn).
If I use the list as return, the collate-fn makes very ugly-unreadable tensors out of it.

as stacked tensors are expected.
You should be able to directly return the pd.DataFrames, but then your model would most likely not accept it (or you would transform the input to proper tensors in your forward which also sounds quite late).

@MikeTensor

Maybe this is naiv, but wouldn’t it be easier to convert the image and target (list) (my returns of the DL) manually with one or two lines of code?

Yes, I would recommend transforming the data into a tensor inside the __getitem__ so that the default collate function could then create batches from these samples.
Would this work or does it not fit your use case?