Hello! I have a question regarding the implementation of gradient function of WGAN-GP (https://github.com/ddbourgin/numpy-ml/blob/master/numpy_ml/neural_nets/losses/losses.py#L497). I'm not sure why epsilon is added toX_interp_norm. I'm getting the same gradient except for the epsilon term. Also, the gradient is computed with respect to GradInterp, shouldn't the gradient be computed with respect to the mixed image x'?
I could be wrong about some of this. Looking forward to hearing from you.
Hello! I have a question regarding the implementation of gradient function of WGAN-GP (https://github.com/ddbourgin/numpy-ml/blob/master/numpy_ml/neural_nets/losses/losses.py#L497). I'm not sure why
epsilon
is added toX_interp_norm
. I'm getting the same gradient except for the epsilon term. Also, the gradient is computed with respect toGradInterp
, shouldn't the gradient be computed with respect to the mixed imagex'
?I could be wrong about some of this. Looking forward to hearing from you.