Is it
CLEARML_CONFIG_FILE
? (I had to dig this from the GH code
)
Yes it is !
https://clear.ml/docs/latest/docs/faq#clearml-configuration
(I will make sure we add it to https://clear.ml/docs/latest/docs/configs/env_vars#server-connection as well 🙂 )
Also, how would one ensure immutability ?
I guess this is the big question, assuming we "know" a file was changed, this will invalidate all versions using it, this is exactly why the current implementation stores an immutable copy. Or are you suggesting a smarter "sync" function ?
GrievingTurkey78 yes, you are correct on both.
Will the sweep functionality work?
Yes it should, that said, it will not use the trains-agent so you are limited to the machine running the sweep.
If you want to do HPO on multi-node, checkout this example 🙂
https://github.com/allegroai/trains/blob/master/examples/optimization/hyper-parameter-optimization/hyper_parameter_optimizer.py
Hi @<1523702932069945344:profile|CheerfulGorilla72>
This is a property on the Model object
model.published
Not sure why we do not have it here...
None
(I'll ask them to fix that)
sdk.conf will add it to the default loaded values (as I think you deduced).
can copy paste the sdk.conf here? (maybe something is missing there?)
ResponsiveCamel97
BTW: any reason not to allow this flexibility ?
I have install a python environment by virtualenv tool, let's say
/home/frank/env
and python is
/home/frank/env/bin/python3.
How to reuse the virtualenv by setting clearml agent?
So the agent is already caching the entire venv for you, nothing to worry about, just make sure you have this line in clearml:
https://github.com/allegroai/clearml-agent/blob/249b51a31bee97d63f41c6d5542e657962008b68/docs/clearml.conf#L131
No need to provide it an existing...
Hi @<1730033904972206080:profile|FantasticSeaurchin8>
You mean in the UI , or when reporting on the SDK?
Is this information stored anywhere or do I need to explicitly log this data somehow?
On the creating Task along side all the other reports.
Basically each model stores its creating Task (Task ID), using the Task ID you can query all the metrics reported by the task
Another issue that might be the case, might be that I'm on ubuntu some of the packages might've been for windows thus the different versions not existing
Usually this is not the case, the version number match (implementation wise it might be a different file, but it is almost always a matching version)
Hi @<1547028116780617728:profile|TimelyRabbit96>
It should process the new request A (this is a multi threading / async implementation)
Is this consistent with what you are seeing ?
Hi QuaintPelican38 can you manually access the machine based on the IP it registered
(Look under the DevOps project, you'll see a running Task "interactive session" under the configuration tab, user properties you should find the IP
If that's the case check the free space in the monitoring of the experiment, you will find the free space in GB logged
the other repos i have are constantly worked on and changing too
Not only it will be cloned automatically, the git diff of the sub-modules are stored as well 🙂
GreasyPenguin66 you can pass:AZURE_STORAGE_ACCOUNT AZURE_STORAGE_KEYAs the default azure access/secret 🙂
BTW updating the values in grafana is basically configuration of the heatmap graph, so it is fairly easy to do, just not.automatic
Thanks GentleSwallow91
That's a good tip, where in the docs would you add it?
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
Working on it as we speak 🙂 probably a day worst case 2. This is quite strange and we are not sure where is the fault, as nothing in the code itself changed...
It does work about 50% of the times
EcstaticGoat95 what do you mean by "work about 50%" ? do you mean the other 50% it hangs ?
Hi @<1689808977149300736:profile|CharmingKoala14> , let me double check that
When you have a bit of experience, please suggest a path forward, it will be great to integrate
Hmm I see your point.
Any chance you can open a github issue with a small code snippet to make sure we can reproduce and fix it?
Pseudo-ish code:
create pipelinepipeline = Task.create(..., task_type="controller") pipeline.mark_started() print(pipeline.id)2. launch step A (pass arguments via command line argument / os environment)
` task = Task.init(...)
pipeline_id = os.environ['MY_MAIN_PIPELINE']
pipeline_task = Task.get_task(task_id=pipeline_id)
send some metrics / reports etc.
pipeline_task.get_logger().report_scalar(...)
pipeline_task.get_logger().report_text(...) `wdyt? (obvioudly you need to somehow pass th...