Welp, it's been a day with the new settings, and stats went up 140K for API calls 😢 ... going to check again tomorrow to see if any of that was spill over from yesterday
Actually looking at the counts today, they've barely changed. So I think this actually fixed it, and was just that the counts are only updated daily so I needed to get 48 hours out from when I made the change to see clean results to assure no spill over counts from previous days.
Ya . I don't see any links on the FAQ site pointing back to your main . SEO wise that'd help with relevancy .
Thanks, will do. Heck, for my use case, I only need like once every 10 minutes.
this one, right ? report_period_sec in ~/clearml.conf correct ?
Ya, sorry, I meant that if you needed more info on what was being run, it was in that screenshot ( showed instances/epochs/batch size, etc ) . But yes, it's since been disabled .
I am running this on a 3090 GPU locally, just been letting it run for about two weeks now I think. Just have the one GPU, ha ha. It's at epoch 368 out of the 1,000 I have it set to cap out on ( if it does not hit the default YOLO "patience" limit of 50 before then and self terminate ).
I did notice that the last 24 hours I dropped quite a bit, so my theory that the 140K might have some spillover from previous day might have been correct. Last 24 hours went from 1.24M to 1.32M, so about half as much as the day before, with the same training running.
I for one prefer Slack over Discord, so no complaints here.
@<1523701205467926528:profile|AgitatedDove14> looks like your faq.clear.ml site is missing from your main sites sitemap files, so might be good to add that in there and trigger a reindex in Google Search Console. Also missing the robots meta tag on that site, but it's not as important as the robots.txt file, which looks correct. Last tip is to add a link on the faq.clear.ml site back to clear.ml for search in...
well, in my case, if I am trying to make sure I do not go over the allotted usage, it matters, as I am already hitting the ceiling and I have no idea what is pushing this volume of data
FYI, I did not even know to look into this until I logged in and saw that I was being throttled because I had hit my monthly limit with API calls ( on my very first use of your platform ), and my last dozen or so epochs were just not even logged ( also a bummer ). I only had that one model in training, and thought there was no way I sent over a million API requests, so had to figure out where those were coming from, and tracked it down to that STDOUT, and was like ... wait, what?!?! Found th...
Just wish I could actually see somewhere what is being sent over API so I could know where to focus my efforts to refine this kind of stuff 😉
Maybe ClearML is using tensorboard in ways that I can fine tune? I saw there was a manual way if you were not using tensorboard to send over data, but the videos I saw from your team used this solution when demoing YOLOv8 on YouTube ( there were a few collab videos your team did with theirs, so I just followed their instructions ). But my gut is telling me that might be the issue for the remaining data being sent over that I have no insight into.
Since it's literally something we have to pay for ( which I signed up to do ) I would love to know what drives this cost
It was at 1.1M when I shut it down yesterday, and today it's at 1.24M
@<1523701087100473344:profile|SuccessfulKoala55> You are my hero !!! This is EXACTLY what I needed !!!
each epoch runs about 55 minutes, and that screenshot I posted earlier kind of show the logs for the rest of the info being output, if you wanted to check that out None
I appreciate your help @<1523701205467926528:profile|AgitatedDove14> 🙂
In future collab community videos and sample source for YoloV8, might be worthwhile to call that out as something folks might want to turn off unless they need it :) . Like I mentioned, I had no idea it was going to do that and sent your servers over 1.4M API hits unintentionally : (
Assuming GitHub, but just making sure you don't have another PM tool you'd rather use .
I would love to be able to fine tune this as needed, but in my profile I only see a Billings & Usage, and it states at the top that "Usage data is updated once every day" ... and even then, all the shows under "Platform Usage" is number of calls performed, not what those calls were.
FYI, found log_stdout in that same setting and default for that was true so set that to false so it would not log all stdout & stderr
My training is on roughly 50 classes as a subset of the Open Images Dataset for Segmentation
Is there a place in ClearML that shows Platform Usage? Like, what's actually taking up the API calls?
Scary to think how common that might be, could be interesting way to optimize your platform, detect excessive console logging and prompt user to confirm continued usage ( or link to docs on how to disable if they want to stop it )
So, might be in the minority here, but seems like capturing stdout and sending that over to clearml via API should be disabled by default. Like I get maybe capturing stderr, but stdout? In a training scenario, that's MILLIONS of API calls just in progress bar indicators, right? Like it might actually be better for the ClearML servers just in general to make the user turn that on if they want it, otherwise we're just blasting your servers. In my case, I did not even know it was sending that...
It'd be great if it just posted to clearml after each epoch is completed and the CSV with the results gets updated . I only care about using the dashboard to track completed progress . I can use my local computers terminal window to monitor current epoch training . No need to send that to clearml every second ;) Results once an hour or so is fine after each completes :)
I think we're good now :) Appreciate the help !!!
