Hi RotundSquirrel78 , can you try clearing local cache? For me everything is showing properly
EmbarrassedSpider34 , you can use the API to remove tasks from a queue
https://clear.ml/docs/latest/docs/references/api/queues#post-queuesremove_task
@<1570220858075516928:profile|SlipperySheep79> , you can use top or htop to see running processes on your machine...
is it normal that it's slower than my device even though the agent is much more powerful than my device? or because it is just a simple code
I'm not sure I understand. Can you elaborate please?
Also, can you please specify all the versions of agent/sdk/backend you're using?
Hi @<1749602841338580992:profile|ImpressionableSparrow64> , the S3 configuration (Credentials) is always done on the client side. You don't need to configure anything server side. Also good that you configured the agent.
You need to use a docker image that already has the cuda package installed. Also don't forget to run the agent in --docker mode 🙂
Thanks for the info! This happened when you had 2 spot instances running something, correct?
Can you please open a GitHub issue to follow up on this issue?
@<1554275773496430592:profile|DeliciousRaven95> , in general the data in datasets is bundled and zipped, you can add visualization manually on to of it. Is what what you're referring to?
SkinnyPanda43 , did Gabriel's tip help?
Hi @<1562610699555835904:profile|VirtuousHedgehong97> , I think you can mount some shared folder between the ec2 instances to use as cache. ClearML hashes data so it can know if what it has in it's cache is relevant or not.
I'm not sure, maybe @<1523701087100473344:profile|SuccessfulKoala55> might have an idea 🙂
Hi @<1785841629471444992:profile|CluelessSheep59> , looks OK. Give it a try and see what happens 🙂
Hi @<1715175986749771776:profile|FuzzySeaanemone21> , what if you try to register them as https?
Python 2 is no longer supported, I'd suggest finding an AMI that already has python3 built in (Or install it using the init script, not suggested though) and also CUDA enabled to avoid that installation to support cuda images
Hi DrabCockroach54 , in the open source version there are no roles. You can set up users & passwords using this:
https://clear.ml/docs/latest/docs/deploying_clearml/clearml_server_config/#web-login-authentication
I am not sure there is a simple way to delete users - I think you would need to edit MongoDB manually, which I would not recommend
but I want to change what is shown by the GUI so that would need to be a setting on the server itself?
Can you please elaborate?
You can add it manually to the requirements
So If I manually add a dataset (many excels), in a folder, and copy that folder to NFC
How would you do that?
Hi @<1533619716533260288:profile|SmallPigeon24> , can you provide a snippet that reproduces this? Do you have some more information? What do you mean skip it?
I'm not sure if I'm missing something, but why not use that environment in pycharm then?
Hi JitteryCoyote63 , I don't believe this is possible. Might want to open a GitHub feature request for this.
I'm curious, what is the use case? Why not use some default python docker image as default on agent level and then when you need a specific image put into the experiment configuration?
Try removing the region, it might be confusing it
Hi @<1523701842515595264:profile|PleasantOwl46> , I'm afraid that such a capability doesn't really exist in ClearML. You could technically populate an experiment using the API.
I'm however curious - what is your use case for this?
Hi @<1654294828365647872:profile|GorgeousShrimp11> , can you provide a log for such a task? What is the status change in the INFO section?
ThankfulHedgehong21 , server 1.6.0 is available. Can you try with it as well?