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It is currently not clear how to adapt the input data transformation and augmentation system to multi-modal data when the modalities can not be put together in a single tensor (e.g., when the patches are of different sizes, etc.).
This case happens quite often in practice and should be handled properly.
If there are some randomized transforms (typically with data augmentation), the modalities can not be processed totally separately otherwise different transforms will be applied to each of them.
To solve this, we might need to use functional transforms to handle the seed of the randomizers manually.
The text was updated successfully, but these errors were encountered:
It is currently not clear how to adapt the input data transformation and augmentation system to multi-modal data when the modalities can not be put together in a single tensor (e.g., when the patches are of different sizes, etc.).
This case happens quite often in practice and should be handled properly.
If there are some randomized transforms (typically with data augmentation), the modalities can not be processed totally separately otherwise different transforms will be applied to each of them.
To solve this, we might need to use functional transforms to handle the seed of the randomizers manually.
The text was updated successfully, but these errors were encountered: