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25 × Eureka!ExcitedSeaurchin87 can I assume in parallel means threads ?
Also, is this a single Dataset version download? at least in theory option (3) is the new default in the latest clearml version. wdyt?
Okay fixed, you will be able to override it with output_uri=False (which is ignored on remote execution if you have a project default or Task output uri set in the UI).
Make sense ?
How did you define the decorator of "train_image_classifier_component" ?
Did you define:@PipelineDecorator.component(return_values=['run_model_path', 'run_tb_path'], ...Notice two return values
AttractiveCockroach17
Can you print the configuration to console when you start he run (you will get a local print and then later the remote print), are they the same? Are the 3 runs the same (local / remote print)
Hi BlandPuppy7 , is this Trains related, are you trying to integrate it, and need help?
New python executable in /home/smjahad/.clearml/venvs-builds/3.6/bin/python2
This is the output of venv create this is odd.
Could it be that by accident you did:pip install cleamrl-agentand notpip3 install clearml-agentand now it is running on python2 (which would explain the error) ?
I would uninstall/reinstall on python3 to verify
I see, so basically pull a fixed set of configuration for everyone from the server.
Currently only the scale/enterprise version supports such a feature 😞
ReassuredTiger98 yes this is odd:
also:Warning, could not locate PyTorch torch==1.12 matching CUDA version 115, best candidate 1.12.0.dev20220407Seems like it found a matching version and did not use it...
Let me check that
ReassuredTiger98 quick update, the issue was located, next RC will already contain a fix.
In the mean time, you can avoid it by using limiting pip version:
https://github.com/allegroai/clearml-agent/blob/715f102f6d98a44131d5bee909ee779b456c6229/docs/clearml.conf#L67pip_version: "<20.2"
ReassuredTiger98 when you look for task "dca2e3ded7fc4c28b342f912395ab9bc" there are no artifacts ?
Could you add some prints? this should have worked...
In the installed packages section it includes
pywin32 == 303
even though that is not in my requirements.txt.
So for some reason it is being detected (meaning your code base actually imports it in code)
But you can just remove it, either by manually editing the cloned Task (right click, reset, then you can edit the section), or via codeTask.ignore_requirements("pywin32") task = Task.init(...)
Hmm Okay, I think the takeaway is that we should print "missing notebook package" 🙂
GreasyPenguin14 could you test with the 0.17.5rc4 ?
Also what's the PyCharm / OS?
It might be broken for me, as I said the program works without the offline mode but gets interrupted and shows the results from above with offline mode.
How could I reproduce this issue ?
But there might be another issue in between of course - any idea how to debug?
I think I missed this one, what exactly is the issue ?
Hi FunnyTurkey96
Let me check what's the status here
(BTW: Is this for a specific Task or for a specific Project?)
DeliciousKoala34 any chance you are using PyCharm 2022 ?
Clearml 1.13.1
Could you try the latest (1.16.2)? I remember there was a fix specific to Datasets
BTW: if you feel like pushing forward with integration I'll be more than happy to help PRing new capabilities, even before the "official" release
Anyhow if the StorageManager.upload was fast, the upload_artifact is calling that exact function. So I don't think we actually have an issue here. What do you think?
You're suggesting that the false is considered a string and not a bool?
The clearml-server always stores the values as strings (serializing them), the casting is done when passed back to the code in runtime. The issue here is there is actually no "way" to tell the argparser this is a boolean (basically any value that will be passed is treated as string). What I think we should do is fix the casting function so that if this is exatcly the same value we use the default value (i.e. boole...
Is it being used to ssh to the instance?
It is used for the SSH client so it "knows" the SSH server (does that make sense) ?
This will allow them to experiment outside of clearml and only switch to it when they are in an OK state. This will also helpnot to pollute clearml spaces with half backed ideas
What's the value of runnign outside of an experiment management context ? don't you want to log it?
There is no real penalty here, no?!
HighOtter69
By default if you are continuing an experiment it will start from the last iteration of the previous run. you can reset it with:task.set_initial_iteration(0)
GiganticTurtle0 I'm not sure I follow, what do you mean by indexing the arguments? Can you post a short usage example ?
Hi ReassuredTiger98
Good point, since the user actually "running" the code is the agent, all the api calls are registered under its name, including the Model creation.
This is a good point, though ...
I know the enterprise tiers add "impersonate" as part of the security layer, meaning that the agent is Not actually running the code but the creating "user" is, which solve this problem. I'm not sure what actually can be done without this feature... thoughts?
Its stored on the Task, you can see it under the execution tab in the UI
Hi @<1684735407637401600:profile|WonderfulJellyfish65>
BTW, the training script connects to apiserver via the internal IP address
That is a big issue, because as you noticed the links to data =generated by the code will have the internal IP ...
You basically need every component to use the same address (url)