assert len(data_loader) > 0，AssertionError about coop HOT 12 OPEN

more details on how you run the code?

from coop.

run the code with:bash scripts/coop/main.sh imagenet rn50_ep50 end 16 1 False
and imagenet are configured according to datasets.md

from coop.

you can check the source code here https://github.com/KaiyangZhou/Dassl.pytorch/blob/master/dassl/data/data_manager.py#L38

the error you got, assert len(data_loader) > 0, means the data loader has zero length and hence no minibatches were loaded

it might happen when drop_last=True and batch_size is bigger than the dataset size

anyway, I'd suggest you take a look at your dataset and put some stop points like import pdb; pdb.set_trace() in the data_manager.py

what I'm sure about is you don't need to change any source code of dassl in order to get this CoOp code running

from coop.

Thank you for your reply. I rechecked the contents of the Imagenet dataset. There are 1000 files in the train folder that are consistent with the remarks of datasets.md. There is no error. What is the content of the Val folder? I use a 6.7g Val with 50000 pictures.

from coop.

A standard imagenet dataset has a train folder and a val folder. Isn't it?

from coop.

Good, thank you. It seems that my Val version is wrong. Thank you for your reply

from coop.

Good, thank you. It seems that my Val version is wrong. Thank you for your reply

I meet the same problem. Did you fix it now?

from coop.

classifying pictures can solve the problem

from coop.

classifying pictures can solve the problem

I meet the same problem, but after I classified the val fold, it still does not work.

from coop.

classifying pictures can solve the problem

I meet the same problem, but after I classified the val fold, it still does not work.

Did you fix it now?

from coop.

classifying pictures can solve the problem

I meet the same problem, but after I classified the val fold, it still does not work.

Did you fix it now?

I solve it. The reason is that the preprocessed.pkl was created, but no information was written. This causes datasets/imagenet.py to not execute correctly.

from coop.

classifying pictures can solve the problem

I meet the same problem, but after I classified the val fold, it still does not work.

Did you fix it now?

I solve it. The reason is that the preprocessed.pkl was created, but no information was written. This causes datasets/imagenet.py to not execute correctly.

whoa, thanks for solving the problem, this helps a lot!

from coop.