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 had no idea it was going to do that and sent your servers over 1.4M API hits unintentionally
Yeah, that is way too much, I think relates to the frequency it updates the console 😞
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
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
140K calls a day, how often are you sending scalars ? how long is it running? how many experiments are running ?
might be a feature request then, as ya, having transparency into something we are charged for would be nice. At this point, I have zero idea what is driving this usage and just want to make sure the costs for training do not bloat too much. I personally am just using ClearML as a central dashboard for a few people. I don't need it to be live data, I just need a rough overview of progress. Even if it only posted updates to ClearML once an hour, that is honestly fine.
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 )
If you do not have a lot of workers, that I would guess console outputs
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.
I think we're good now :) Appreciate the help !!!
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 : (
well from 2 to 30sec is a factor of 15, I think this is a good start 🙂
is number of calls performed, not what those calls were.
oh, yes this is just a measure of how many API calls are sent.
It does not really matter which ones
Came to ClearML since it had slick dashboard and showed me the info that mattered. Loved that I could share the results of each epoch so we could make sure things were headed in the correct direction.
hmmm, this is just a personal project, honestly was just hoping this would let me take the results of each epoch and put it in a central dashboard. Having this generate 1M+ api calls and only being like 1/4 of the way though training is a bit much. Current pricing is $1/100K API calls at the PRO tear, which I am on ... so it would be like another $50 just in API calls at this pace 😞 Would love to just cap it at a fixed amount for a month for API calls.
I'm not sure on the frequency it updates though
(Not sure it actually has that information)
I appreciate your help @<1523701205467926528:profile|AgitatedDove14> 🙂
I guess last followup question, is there a way to cap costs? Like if this is running at this scale, I am not sure I can use ClearML for my purpose if I am just going to get overage charged repeatedly ( which I am already looking like I will be doing ).
Thanks, will do. Heck, for my use case, I only need like once every 10 minutes.
So, might be in the minority here, but seems like capturing stdout and sending that over to clearml via API should be disabled by default. Like I get maybe capturing stderr, but stdout? In a training scenario, that's MILLIONS of API calls just in progress bar indicators, right? Like it might actually be better for the ClearML servers just in general to make the user turn that on if they want it, otherwise we're just blasting your servers. In my case, I did not even know it was sending that over until I got into digging where these API calls were coming from, and saw the CONSOLE tab in clearml that had every single line of stdout captured.
Hi @<1572395184505753600:profile|GleamingSeagull15>
Try adjusting:
None
to 30 sec
It will reduce the number of log reports (i.e. API calls)
Hmm if this is case, you can add some prints in here:
None
the service/action will tell you what you are sending
wdyt?
each epoch runs about 55 minutes, and that screenshot I posted earlier kind of show the logs for the rest of the info being output, if you wanted to check that out None
My training is on roughly 50 classes as a subset of the Open Images Dataset for Segmentation
I guess last followup question, is there a way to cap costs?
Scale tier ? (I know it is not per usage, but it is probably more than 15$ per user 🙂 )
Would love to just cap it at a fixed amount for a month for API calls.
Try the timeout configuration, I think this shoud solve all your issues, and will be fairly easy to set for everyone
In case of scalars it is easy to see (maximum number of iterations is a good starting point
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 ).
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