Comments (4)
Due to the prune_ckpt.py
declaring the arg parsed in the global scope, when importing it the main arguments are overridden.
Comment out these lines from prune_ckpt.py
:
# parser = argparse.ArgumentParser(description='Pruning')
# parser.add_argument('--ckpt', type=str, default=None, help='path to model ckpt')
# args = parser.parse_args()
# ckpt = args.ckpt
Better yet: it may be wise to move the pruner method in a separate file - in ldm
- and then use it from there in prune_ckpt.py
- so that we avoid these hacks.
from dreambooth-stable-diffusion.
Nope - that seems to be called only during errors... Need to dig deeper into this one.
from dreambooth-stable-diffusion.
Ah! Turns out you can just be nice and ask ModelCheckpoint to "save_weights_only": True
. Testing it out now to see if it does what the docs say it should do.
from dreambooth-stable-diffusion.
It does, it makes the checkpoint 4GB, still pruning it will make it closer to 2.5GB. Looking for hooking into the ModelCheckpoint class and see if we can extend it.
from dreambooth-stable-diffusion.
Related Issues (20)
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