Hi there!
I’ve just read the ResNet paper and I decided to implement a version that works on tabular data.
The only hold-up is figuring out how to map the input to a residual block down to the same size as the block’s output. I figured a nice way to do this might be to use some form of pooling. I thought maybe MaxPool1d might do the trick, but I looked at the docs and saw that this is still a pooling method designed for a 3d tensor.
Before I try to go create some silly version of my own, is there anything built into PyTorch that does this for you?