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Since the d_loss = fake-real+gp, how to decide the value of LAMBDA to get a reasonable gradient penalty.
I mean, if fake=-10, real=10, is gp=10 appropriate?or the gp should be smaller(e.g. gp=5)?
The text was updated successfully, but these errors were encountered:
i have the same question about it, did you solve this problem? at the start of my train, the wass loss is very small, about 0.01, so how should i set the lambda?
Penalty coefficient All experiments in this paper use λ = 10, which we found to work well across a variety of architectures and datasets ranging from toy tasks to large ImageNet CNNs.
Since the d_loss = fake-real+gp, how to decide the value of LAMBDA to get a reasonable gradient penalty.
I mean, if fake=-10, real=10, is gp=10 appropriate?or the gp should be smaller(e.g. gp=5)?
The text was updated successfully, but these errors were encountered: