Open zoelovecoffee opened 1 year ago
Thanks for your attention.
A step means a step of optimization, and training_samples = batch_size * step
.
We don't explicitly have a parameter to stop the training process and it can infinitely run.
So "FFHQ128-130M-z512-64M" with batch_size = 128
means you need train it until step $\ge$ (64000000/128) and munually stop it.
Thank you for answering my question, it helps a lot!
Hi, when running your code
representation_learning_trainer.py
, I was confused about thestep
parameter. For example, to train "FFHQ128-130M-z512-64M" withbatch_size = 128
, how does the step parameter related to "64M" training samples: as FFHQ contains 70000 images, does it indicate (64000000/70000) times of iterations, and doesstep
parameter stand for number of training epoch?Could you let me know if I have any misunderstanding. Thank you:)