AgitatedDove41 , this is the old documentation indeed. It's deprecated and shouldn't be used 🙂
New documentation has everything in it, and more!
StickySheep96 , Is it possible you raised the server locally on your machine and not the EC2 instance?
Can you add a log?
I mean code wise. Also where is it saved locally?
And how is the model being saved?
CrookedWalrus33 , you can set in the Task.init
, set the output_uri = True
. This should upload to the fileserver since by default models are saved locally
Hi SuperiorCockroach75 , can you please elaborate? What is taking to execute?
Hi, How did you deploy?
What is your scenario? Can you elaborate?
Hi @<1536881167746207744:profile|EnormousGoose35> , you can integrate ClearML into your existing code with the two simple lines of
from clearml import Task
task = Task.init(...)
To see how it works and looks 🙂
What do you mean by drop of many GB? Can you please elaborate on what happens exactly?
I know that elastic can sometimes create disk corruptions and requires regular backups..
How are you reporting / generating them now?
get_parameter
returns the value of a parameter as documented:
https://clear.ml/docs/latest/docs/references/sdk/task#get_parameter
Maybe try https://clear.ml/docs/latest/docs/references/sdk/task#get_parameters
Hi CostlyElephant1 , where is the data stored? on the fileserver or some s3 bucket or other solution?
You can add it to your pip configuration so it will always be taken into account
I think this is covered in the enterprise version
AlertCrow40 Hi!
How are you trying to connect to your jupyter notebook, can you provide a snippet? What version of clearml are you using?
RattyLouse61 , I think you can save the yml conda env file as an artifact, this way it would also be accessible by other tasks 🙂
Hi AbruptCow41 ,
I think you need to call Task.init
before creating the argparser args
Hi FreshParrot56 , I'm not sure there is a way to stop it. However you do need to archive and then delete it.
I don't think such a feature exists currently but you could put in a feature request on GitHub 🙂
Hi @<1535069219354316800:profile|PerplexedRaccoon19> , not sure what you mean. Can you please share the full log, a screenshot of the two experiments and some snippet that re-creates this for you?
Hi @<1540142651142049792:profile|BurlyHorse22> , it looks like an error in your code that is bringing the traceback. What is happening during the traceback?
clearml-session is part of the clearml package 🙂
Great to hear, and now you also have the latest version 🙂
And just to make sure, you're running everything on the same machine, correct?
AgitatedDove41 , you can run as many instances as you'd like 🙂
Please read this to see how it's done with AWS. I don't believe you need much DevOps knowledge 🙂
Hi RobustFlamingo1 ,
Can you point to where the website suggests that K8S is a requirement?
I use the ClearML-Agent on a local machine without any K8S. It is certainly not a requirement. From what I understand you can run it on K8S as well.
So to answer your question:
You can definitely use ClearML Orchestration (ClearML-Agent) with OR without K8S
I hope this helps 🙂
Hi IrritableJellyfish76 , yes. It is available only for Scale & Enterprise versions