Error in local implementation

[sehau]

Excuse me, I got an error when reproducing locally. When training with bottle, the error description is "ValueError: Only one class present in y_true. ROC AUC score is not defined in that case." When training with capsule, the error description is "ValueError: Predictions should be of shape (batch_size, n_classes) or (batch_size, )."

Is my dataset configuration wrong?

[gathierry]

Did you modify the code? Did you try categories other than the two you mentioned? And if possible, could you paste the full traceback message?

[sehau]

Sorry, maybe I modified the code to get an error.

After I re-run it, there is no error, only in some categories there will be a running warning with only one type of label. E.g/data/anaconda3/envs/pytorch/lib/python3.6/site-packages/ignite/metrics/epoch_metric.py:76: RuntimeWarning: Probably, there can be a problem with "compute_fn": Only one class present in y_true. ROC AUC score is not defined in that case.. RuntimeWarning)

It's fine now, but there's a bug in the example that I need to point out.

In # train python main.py --cfg configs/resnet18.yaml --data path/to/mvtec-ad -cat [category], --cfg should be -cfg.

Thanks for your answer and have a nice day.

[sehau]

Did you modify the code? Did you try categories other than the two you mentioned? And if possible, could you paste the full traceback message?

By the way, inpython main.py --cfg configs/resnet18.yaml --data path/to/mvtec-ad -cat [category] --eval -ckpt _fastflow_experiment_checkpoints/exp[index]/[epoch#].pt, should ‘--cfgbe-cfg`？

[gathierry]

Yes, it is a typo in readme. It should be -cfg or --config thanks for pointing that out. I already update the readme file