There's also a blog post 🙂
https://medium.com/pytorch/accelerate-your-hyperparameter-optimization-with-pytorchs-ecosystem-tools-bc17001b9a49

Yes! you can call this

Am I doing something differently from you?

Seems like it. Is that an issue?

To add to Natan's answer, you can run on the services docker anything depending on the HW. We don't recommend training with it as the server's machine might get overloaded. What you can do is simple stuff like cleanup or any other routines 🙂

Yeah, it's still there for compatibility but it should be removed at some point

It's decorators. It's functions as steps, It's the ability to add metric tracking for pipelines. It's a better way to move artifacts between steps (way less boilerplate code). It's pipeline instance versioning (for the upcoming UI changes), it's better step parallelizations (If steps are not dependent on each other, they will automatically be parallelized) and I've probably missed some features....

Hi CourageousKoala93 , not 100% sure I understand what graphmode is, I see it's a legacy option maybe from TF1? If you can put a small snippet so I can try it on my side that'll be helpful!

ZanyPig66 , the 2 agents can run from the same ubuntu account and use the same clearml.conf. if you want each to have its own configuration file just add --config-file PATH_TO_CONF_FILE and it would take another config file. Makes sense?

Hi TenseOstrich47
You can also check this video out on our youtube channel:
https://youtu.be/gPBuqYx_c6k
It's still branded as trains (our old brand) but it applies to clearml just the same!

Hey Tim! So what natanM gave you is a fair place to start (albeit probably not up-to date on either side). There are a few product overviews online (but they are outdated like a month after they're written so...)
As for pricing, we are going to release our new website with updated pricing that will make it more transparent AND easier to compare 🙂

And I use....I think python 3.8

LOL Love this Thread and sorry I didn't answer earlier!

VivaciousPenguin66 EnviousStarfish54 I totally agree with you. We do have answers to "how do you do X or Y" but we don't have workflows really.

What would be a logical place to start? Would something like "training a Yolo V3 person detector on COCO dataset and how you enable continuous training (let's say adding PASCAL dataset afterwords) be something interesting?

The only problem is the friction between atomic and big picture. In...

Happy our intention was still clear

I didn't run inside a docker

You can also open github issues, it helps us prioritise features according to how much comments \ upvotes they receive.

Hi Doron, as a matter of fact yup 🙂 The next version would include a similar feature. Plan is to have it released middle of December so stay tuned 😄

ReassuredTiger98 I think it works for me 🙂
I added this to the requirements (You can put the extra-index-url in the clearml.conf), and I've enabled the torch nightly flag:
--extra-index-url https://download.pytorch.org/whl/nightly/cu117
clearml
torch == 1.14.0.dev20221205+cu117
torchvision == 0.15.0.dev20221205+cpu

JitteryCoyote63 Welcome to the wonderful world of coding where some stuff doesn't work and you don't know why and some stuff works and you don't know why 😂

HI SquareFish25 , We also have a few webinars discussing these topics (more theoretical and what can be achieved using pipelines), check https://youtu.be/_5Re2GpcRp8 and https://youtu.be/yGg-exQHUfE out!

BTW! can you elaborate on the need for elevated privileges? What can't he do that you want him to?

Hi SmugTurtle78 , sorry for answer in slow-mo 😉 I'm not 100% sure I got the question... you want a a global security group and network for the entire autoscaler instead of per-instance type?

Hi Binoy, At the moment, we only support this featured in our enterprise offering. We're now adding more volume to our paid tier and this is indeed a candidate feature to be added. Stay tuned 🙂

SubstantialElk6 Yes! We should have it up, together with the previous one uploaded soon!

Hi DepressedFish57 , as Martin said either the next version or the next-next version will have this feature 😄 We'll update here when it's out 🙂

As for the git, I'm no git expert but having your own git server is doable. I can't tell you what it means in terms of how does it work in your organization though as every one has their own limitations and rules. And as I said, you can use SVN but the connection between it and ClearML won't be as good as with git.

Hi GentleSwallow91 let me try and answer your questions 😄

The serving service controller is basically, the main Task that controls the serving functionality itself. AFAIK: clearml-serving-alertmanager - a container that runs the alertmanager by prometheus ( https://prometheus.io/docs/alerting/latest/alertmanager/ ) clearml-serving-inference - the container that runs inference code clearml-serving-statistics - I believe that it runs software that reports to the prometheus reporting ...

I think there was a slight mixup between our automatic logging (let's say, when you report images to tensorboard and ClearML just automatically captuers it and logs it) to explicitly reporting images (with the Logger object)

Hi MelancholyElk85 , documentation is a soft spot for us, we're trying to be better but we aren't always 🙂 https://github.com/allegroai/clearml/blob/master/examples/pipeline/pipeline_from_decorator.py this is an example, if you check the pipeline folder you'll see others (like pipeline_from_function.py