Open rom1504 opened 3 years ago
I don't know where you got the 0/None but normally it should set the augmentation probability automatically. This should be the code that does it:
if not exists(self.aug_prob) and num_samples < 1e5:
self.aug_prob = min(0.5, (1e5 - num_samples) * 3e-6)
print(f'autosetting augmentation probability to {round(self.aug_prob * 100)}%')
So this means that if you have less than 100,000 samples it sets the augmentation probability to (100,000 - num_samples) * 0.0003%
but never higher than 50%. For example: If you have 10,000 samples the augmentation probability will be set to 27%.
Where this formula comes from and how well it works, I do not know. (But it seems reasonable enough.)
The default seems to be 0/None Shouldn't 0.25 be better ? (referring to https://github.com/lucidrains/stylegan2-pytorch/#low-amounts-of-training-data )