Open zweigguan opened 6 years ago
Hey @Guanziwei, sorry for late reply.
Here are my answers to these six questions.
And beta/gamma variables are also for batch normalization layer, but they are trainable. So it's necessary to train on beta/gamma on your own dataset.
evaluate.py
and run it.Hey @hellochick
I'm new to all of this and please forgive my lack of knowledge. So I have a dataset with the following structure:
/jpgs/
How do I make it work with your training algorithm?
I have already asked the same six questions under the issue #9. Because these six questions are too long and I think maybe many other people have met the same questions as I have. So I opened this new issue. Dear @hellochick, thank you very much for opening the source code of your implementation! I have few questions. Your response is very important to me!
python train.py --update-mean-var
and freeze beta/gamma first. After some period, start to train beta/gamma variable using codepython train.py --train-beta-gamma
? How can I know when to stop training? In which way we can see the loss function's value?--update-mean-var
and--train-beta-gamma
means? Which layers do they freeze in the training process?