Daniel Falbel

You might want to wrap the computation of the OOB loss in a `with_no_grad` context, so you don't keep the graph history for it. ``` with_no_grad({ y_pred_oob=model(x_train[oob_index,])[[1]] loss_oob=criterion(y_pred_oob,y_train[oob_index]) }) ```...

I can't think on anything that could cause differences between old macs and new macs. I'm interested in that problem though, is there any way you could provide a reproducible...

Hi @dominikj2, your understanding but you are hitting a few bugs and missing features. A few of them have already been fixed in the dev version and will come to...

This looks like a bug in the `state_dict()` implementation. Sorry about that, we will fix as soon as possible.

I wonder if the tutorial in the main website https://torch.mlverse.org/start/guess_the_correlation/ could serve for this? We could make a demo shiny app bundling the model for predictions on new plots.

Hi @strimmerlab The idea behind auto installation is that the users, when installing torch for the first time doesn't have to deal with any additional installation steps. I understand that...

I agree with you. So IIUC we have two possible solutions: 1. Install the binary dependencies in a post installation script that would run at the same time as `install.packages`....

It's tricky because the `Makevars` file is not run if you install the binaries from CRAN on macOS or Windows that are already built. And we also can't include the...

Another thing that we could do in the future is consider depending on system libraries like: - https://packages.debian.org/sid/libtorch-dev - https://formulae.brew.sh/formula/libtorch We would still need to figure out how to host...

For 1) IMHO the download is fine since it's only done once (the first time you clone the repo and run buildlantern) and it's definetly what we want on the...