I tried to use several convolution layers as learnable filters or smoothers to process time series data. However, I found the some of the weights are still negative even after convergence. And this is definitely not a good property for a smoother, so I want to force the all the weights to be positive.
What I am currently doing is to build a weight tensor x with require_grads=True manually, and envelop it with a softplus function. Just curious if there is any more efficient way to handle it? Thank you!
