Handling large bags during inference

[harshith2794]

Hi,
I was wondering how large slides were handled during inference and training. Was there any limit on the bag-size to prevent OOMs? If so can you clarify how the predictions from multiple bags were aggregated.

Thanks in advance.

[szc19990412]

During training and testing, we adopted the batch size=1 scheme. At the same time, the half-precision floating-point training of the pytorch lightning framework helps TransMIL to process 20 times WSI features.