Eager Eagle

I’ve known Zed for almost a year now, but it still lacks a lot of what VS Code offers. Especially when it comes to customization.

> Welp, that precisely recreated it -- even identical shas! Looking at
> the b4 output, I do see a suspicious "39 commits" listed for some reason.

Well, that's the point where the user, in theory, goes "this is weird, why is
it 39 commits," and does Ctrl-C, but I'm happy to accept blame here -- we
should be more careful with this operation and bail out whenever we recognize
that something has gone wrong. To begin with, we'll output a listing of all
the commits that will be rewritten, just to make it more obvious when things
are about to go wrong.

> So, I assume the "git-filter-repo" invocation is what mangled it. I will
> try to dig into what b4 actually asked it to do in the morning...

Thanks for looking into this. Linus, this is accurate and I am 100% convinced
that there was no malicious intent. My apologies for being part of the mess
through the tooling.

I will reinstate Kees's account so he can resume his work.

-K

Repo: https://github.com/IRS-Public/direct-file

I change them all to bind mounts. Managed volumes is where data goes to die, if it’s not in my file tree I’ll forget it.

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The if block is still in the global scope, so writing the code in it is a great way to find yourself scratching your head with a weird bug 30 minutes later.

everyone knows viruses are allergic to apps

nice, I have some games that use denuvo in my wishlist: I’ll make sure to kick them from there.

and for anyone wondering, this profile seems to track games using it:

https://store.steampowered.com/curator/26095454-Denuvo-Games/

it’s 2025, what popular distro makes it not easy?

IMO tensorflow always had a worse API than PyTorch. There’s even the legendary issue “I fucking hate tensorflow”, now unfortunately censored as spam lol.

Tensorflow died because devs never bothered improving that. While PyTorch always had an increasing number of features and high level capabilities, TF has always felt like a lower level tool that only made sense choosing if you needed to run models for inference in other platforms. PyTorch Lightning on top of it was a great touch for researchers.