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GrumpyPenguin23
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23 Questions, 149 Answers
  Active since 10 January 2023
  Last activity 2 years ago

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8 × Eureka!
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Back with another episode of the CLEAR show! Considering the feedback was no turtle πŸ˜‰ we took care of that. See how easy it is to start a worker on a google...
4 years ago
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CloudyHamster42 do you want to move our discussion from FB here?
4 years ago
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4 years ago
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Friendly reminder that exists
4 years ago
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Hi everyone - quick show of hands, is anyone here interested in trains related memes?
4 years ago
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Eventually yes πŸ˜„ and sooner if you submit a feature request, much sooner if you suhmit a pull request πŸ˜†
4 years ago
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Hi Everyone. A nice gist showing how to plug ClearML into sagemaker - i.e. the system env parameters that need to be set https://gist.github.com/YogevKr/de85...
4 years ago
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November poll! Choose our new product name! https://twitter.com/allegroAI/status/1324743895364915200 AND/OR https://docs.google.com/forms/d/1t6QncHM6_PHHNFNl...
4 years ago
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PS - this one was made with you in my mind and heart https://youtu.be/r2BMMDzfyA0
3 years ago
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Dear community! I'm trying out a new way to make clearml-related content. I'd like your opinion on whether this is something you would consider watching (pro...
4 years ago
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3 years ago
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Notice Pytorch Lightning users: PL issue 249 is in fact a non issue starting from Lightning 1.0. No need for any special loggers for the time being, just the...
4 years ago
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Hi,
Hi, ,release notes time! Trains 0.16.4 and Agent 0.16.2 are out! πŸ‘ πŸ‘ πŸ‘ πŸ‘ πŸ‘ πŸ‘ πŸ‘ πŸ‘ πŸ‘ πŸ‘ πŸ‘ πŸ‘ πŸ‘ πŸ‘ First we would like to thank all of you that starr...
4 years ago
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Kudos JuicyFox94 on the effort! If we could clone you and reproduce you as easily as we do to our experiments... ☸️ πŸ… https://twitter.com/lstmeow/status/135...
4 years ago
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3 years ago
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Dear , We are happy to announce that we will be officially changing the Trains product name. The official announcement will be made in January, but we wanted...
4 years ago
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Just a quick note for everyone here, I'm giving a webinar tomorrow, pretty basic ClearML stuff but we end up with a pipeline like this πŸ™‚ So if you know anyo...
3 years ago
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Hey, quick show of hands, who's seen T Guerre in our videos yet?
3 years ago
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4 years ago
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One of you (name is safe and sound with me πŸ˜‰ ) realised that the new name, ClearML, reminded him of some other family of products. He designed an alternativ...
4 years ago
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The party continues on reddit. I'm sure there will be questions from non-users, I hope you could all join in and answer! https://www.reddit.com/r/MachineLear...
3 years ago
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Hey y'all, if you want to discuss clearml in meme form, note that we have a new channel for that:
4 years ago
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Heads up - our workspace is now renamed to clearml, the channel renaming is happening now. BTW there is also a formal blog post for the launch https://tinyur...
4 years ago
3 years ago
0 Hello, I'Ve Installed The Self-Deployed Server On A Raspberrypi 4 According To The Process

Hi ManiacalPuppy53 glad to see that you got over the mongo problem by advancing to PI4 πŸ™‚

4 years ago
4 years ago
0 My Agent Is Not Fully Utilized. I Wonder Anyhow I Could Run Multi-Task On A Same Agent Without Queuing?

HugePelican43 as AgitatedDove14 says, that's a slippery slope to out-of-memory land. If you have Nvidia A100 you can use multiple agents in MIG mode, sort of like containerized hardware if you never heard of it.
Other than that I do not recommend. Max out utilisation for each task instead.

3 years ago
0 My Agent Is Not Fully Utilized. I Wonder Anyhow I Could Run Multi-Task On A Same Agent Without Queuing?

Hi, I was just answering your previous question. can you explain a bit what you mean by "under utilized"? e.g. do you have 2 gpus and are using only one of them for a task?
or are maxing out resources but do not get to 100% utilization (which might be a data pipeline issue)

3 years ago
0 Hello All, I Am Using Community Server And I Could Not Find Feature Store On My Ui. Any Configuration To Make It Appear? Thanks

I guess the product offering is not so clear yet (pun intended) the self-deployed option is completely free and open source. The enterprise offering is something entirely different
https://clear.ml/pricing/
The "feature store" you see in the free tier is what I am alluding to

3 years ago
0 Another Question, Im Working With Dynamic Resource Allocation System, Is There A Way To See What Type Of Gpus Were Used For The Experiment?

Hi Elron, I think the easiest way is to print the results of !nvidia-smi or use the framework interface to get these and log them as a clearml artifact. for example -
https://pytorch.org/docs/stable/cuda.html

3 years ago
0 Hello All, I Am Using Community Server And I Could Not Find Feature Store On My Ui. Any Configuration To Make It Appear? Thanks

First of all I'd like to thank you for pointing out that our messaging is confusing. We'll fix that.

To the point: Nice interface and optimized db access for feature stores is part of our paid, enterprise offering.

Managing data/features as part of your pipelines and getting version-controlled features == offline feature store

The latter is doable with the current ClearML open source tools, and I intend to show it very soon. But right now you won't have a different pane for DataOps, it'll...

3 years ago
0 Hi, There'S Something I Don'T Find Too Logical When Using Clearml And Its Agents. I Will Need To Run My Code Once On My Client Computer This Is Without Gpus. And Then I Will Need To Run It Via The Ui On Clearml Server That Has Gpus. Why Can'T I Configure

Hi SubstantialElk6 , have a look at Task.execute_remotely, and it's especially for that. For instance in the recent webinar, I used pytorch-cpu on my laptop and task.execute_remotely. the agent automatically installs the GPU version. Example https://github.com/abiller/events/blob/webinars/webinars/flower_detection_rnd/A1_dataset_input.py

3 years ago
0 Hi, Is There A Way To Create A Draft Experiment Manually? That Is - Give It A Some File To Run, Or, Better Yet, A Function To Run Which Will Be The Start Of The Experiment? In W&B, For Example It Is Possible To Simply Write (Their

OddAlligator72 I think you got sidetracked into the wrong corner here, lets decompose what you are asking for please, tell me if I am getting somewhere near what you mean:
you have an experiment you already ran you want to change the parameters in it and run it again if possible you only want to run a single function in the file attached to that experiment

4 years ago
0 Lstmeow Is Back! Bots/Gals/Guys Feel Free To

Thanks @<1523701205467926528:profile|AgitatedDove14> , also I think you're missing a few pronouns there πŸ˜‰

4 years ago
0 Hi, Do You Have A Channel For Dev/Contributors On Your Github Repos? I See Only A

Hi, it is under construction, but it is going to be there.

4 years ago
0 Hey Guys, I Just Published (My Second Over All) Article On Medium

WickedGoat98 I gave you a slight twitter push πŸ˜‰ if I were I would make sure that the app credentials you put on your screen shot are revoked πŸ™ πŸ˜‡

4 years ago
0 I Have Several Models To Log As Artifact And I Am Using Outputmodel To Do That Model = Outputmodel(Task) Model.Update_Weights(File) Here 'File' Is My Model In The Ui It Is Showing Me The Models As A 'Draft' Now If I Try Again To Log Models One More Time

and should it work across your workspace, i.e. does not matter if task id changed? just always keep a single model with the same filename? i'm really worried this could break a lot of the reproducible/repeateable flow for your process.

4 years ago
0 I Have Several Models To Log As Artifact And I Am Using Outputmodel To Do That Model = Outputmodel(Task) Model.Update_Weights(File) Here 'File' Is My Model In The Ui It Is Showing Me The Models As A 'Draft' Now If I Try Again To Log Models One More Time

script runs, tries to register 4 models, each one of them is exactly found in the path, size/timestamp is different. then it will update the old 4 models with the new details and erase all the other fields

4 years ago
0 I Have Several Models To Log As Artifact And I Am Using Outputmodel To Do That Model = Outputmodel(Task) Model.Update_Weights(File) Here 'File' Is My Model In The Ui It Is Showing Me The Models As A 'Draft' Now If I Try Again To Log Models One More Time

so what I am describing is exactly this - once you try to create an output model from the same task, if the name already exists - do not create a new model, just update the timestamp on the old one

4 years ago
0 I Have Several Models To Log As Artifact And I Am Using Outputmodel To Do That Model = Outputmodel(Task) Model.Update_Weights(File) Here 'File' Is My Model In The Ui It Is Showing Me The Models As A 'Draft' Now If I Try Again To Log Models One More Time

what a turn of events πŸ˜‰ so lets summarize again:
upkeep script - for each task, find out if there are several models created by it with the same name if so, make some log so that devops can erase files DESTRUCTIVELY delete all the models from the trains-server that are in DRAFT mode, except the last one

4 years ago
0 Hi, I Am New Here. I Was Wondering Where Can I Configure Which Machines Trains (Or Trains-Agent?) Use For Queueing Tasks, And How Do I Create Such Queues. Thanks.

Welcome! The machines are the ones you install and run the trains-agent daemon on, and creating the queues can be done via the trains-agent cli or the webapp UI

4 years ago
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