earlyoom VS stylegan2-pytorch

> The system is not supposed to 'lock up' when you run out of physical RAM. If it does, something is wrong. It might become slower as pages are flushed to disk but it shouldn't be terrible unless you are really constrained and thrashing. If the Kernel still can't allocate memory, you should expect the OOMKiller to start removing processes. It should not just 'lock up'. Something is wrong.

I don't why but locking up is my usual experience for Desktop Linux for many years and distros, and I remember seeing at least one article explaining why. The only real solution is calling the OOMKiller early either with a daemon or SysRq.

> It should not take minutes. Should happen really quickly once thresholds are reached and allocations are attempted. What is probably happening is that the system has not run out of memory just yet but it is very close and is busy thrashing the swap. If this is happening frequently you may need to adjust your settings (vm.overcommit, vm.admin_reserve_kbytes, etc). Or even deploy something like EarlyOOM (https://github.com/rfjakob/earlyoom). Or you might just need more RAM, honestly.

Yeah. Exactly. But as the thread says, why aren't those things set up automatically?

It's not that simple: some defaults may differ, and some features may arrive at different times (if ever). For example, earlyoom has been enabled on Workstation since F32, but the KDE Plasma spin got it one release later.

Most answers will answer your question, but you can do better and avoid the freezes in the first place. IME almost every time the system froze up and didn't come back in a few seconds it was out of memory. The obvious solution is to add memory, but you can use Early OOM to kill hungry processes if you're running out of memory instead.

It sounds like you're running out of memory though, so if your OS's OOM killer isn't working as well as it should, you can try earlyoom as an alternative.

Swap is indeed supposed to prevent this AFAIK. You can though try some tools like EarlyOOM and see if it helps : https://github.com/rfjakob/earlyoom

export default function ChannelListBottomBar(): JSX.Element { const { client } = useChatContext(); const [micActive, setMicActive] = useState(false); const [audioActive, setAudioActive] = useState(false); return (

{client.user?.image && (

div> )}

{client.user?.name} span> {client.user?.online ? 'Online' : 'Offline'} span> p> button>

setMicActive((currentValue) => !currentValue)} > button> setAudioActive((currentValue) => !currentValue)} > button> button> div> ); }

I wonder if we will ever get a realism model which can produce normal faces like https://thispersondoesnotexist.com instead of like super symmetrical faces of models

this has been in circulation since a while AI images took off, and they certainly weren't convincing before they did. You know the old "try to name one thing in this image" macro? Pretty sure that was AI generated, there was also thispersondoesnotexist.com which was always pretty good but of course it is

Not the workflow for these images, but if you easily want to spice up your gens with a bit more natural look, try using images from thispersondoesnotexist.com with IPAdapter face model.

...then they just use the app on generated images of not real people (potentially based on specific inputs to remind you of a real person).

Also we can generate very realistic faces with AI, https://thispersondoesnotexist.com/ (old example), fully 3D faces are doable at this point. So in another 5-10 years a low profile model like him wouldn't even be hired for this, they would just generate a digital face model. Unionizing will only speed up studios adoption of digital replacements.

It looks like they all use a profile picture made with https://thispersondoesnotexist.com/