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szc19990412 / TransMIL

TransMIL: Transformer based Correlated Multiple Instance Learning for Whole Slide Image Classification
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Handling large bags during inference #17

Closed harshith2794 closed 1 year ago

harshith2794 commented 2 years ago

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 commented 1 year ago

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.