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How can I train on multiple datasets ( or a single dataset with multiple class of images) simultaneously while making sure different classes are not mixed in the memory bank (image flow) during training ?
Should I do something like following for example:
Put 5 images of dataset A(1 prompt image and 4 training images) calculate the gradients, and then empty the memory bank
Put 5 images of dataset B calculate gradients (do gradient accumulation), empty the memory bank
do optimiser and then repeat
?
The text was updated successfully, but these errors were encountered:
Hi Thank you for sharing your code.
How can I train on multiple datasets ( or a single dataset with multiple class of images) simultaneously while making sure different classes are not mixed in the memory bank (image flow) during training ?
Should I do something like following for example:
Put 5 images of dataset A(1 prompt image and 4 training images) calculate the gradients, and then empty the memory bank
Put 5 images of dataset B calculate gradients (do gradient accumulation), empty the memory bank
do optimiser and then repeat
?
The text was updated successfully, but these errors were encountered: