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Is There A Way To Save The Models Completely On The Clearml Server? It Seems That Clearml Server Does Not Store The Models Or Artifacts Itself, But They Are Stored Somewhere Else (E.G., Aws S3-Bucket) Or On My Local Machine And Clearml Server Is Only Sto

Is there a way to save the models completely on the ClearML server?

It seems that ClearML Server does not store the models or artifacts itself, but they are stored somewhere else (e.g., AWS S3-bucket) or on my local machine and ClearML Server is only storing configuration parameters and previews (e.g., when the artifact is a pandas dataframe). Is that right?

  
  
Posted 2 years ago
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Answers 45


I wouldn't put past ClearML automation (a lot of stuff depend on certain suffixes), but I don't think that's the case here hmm

  
  
Posted 2 years ago

Do you mean "exactly" as in "you finally got it" or in the sense of "yes, that was easy to miss"?

  
  
Posted 2 years ago

Well you could start by setting the output_uri to True in Task.init .

  
  
Posted 2 years ago

@<1523701083040387072:profile|UnevenDolphin73> : I see. I did not make the connection that output_uri=True is what I was missing. I thought this was the default. But the default is actually "None", which is different than "True".

  
  
Posted 2 years ago

We'll try to add referenced to that in other places as well 👍

  
  
Posted 2 years ago

@<1523701070390366208:profile|CostlyOstrich36>

My training outputs a model as a zip file. The way I save and load the zip file to make up my model is custom made (no library is directly used), because we invented the entire modelling ourselves. What I did so far:

output_model = OutputModel(task=..., config_dict={...}, name=f"...")
output_model.update_weights("C:\io__path\...", is_package=True)

and I am trying to load the model in a different Python process with

mymodel = task.models['output'][0]
mymodel = mymodel.get_local_copy(extract_archive=True, raise_on_error=True)

and I get in the clearml cache a . training.pt file, which seems to be some kind of archive. Inside I have two files named data.pkl and version and a folder with the two files named 86922176 and 86934640 .

I am not sure how to proceed after trying to use pickle, zip and joblib. I am kind of at a loss. I suspect, my original zip file might be somehow inside, but I am not sure.

Sure, we could simply use the generic artifacts sdk, but I would like to use the available terminological methods and functions.

How should I proceed?

  
  
Posted 2 years ago

From the one you sent - None

  
  
Posted 2 years ago

It is documented at None ... super deep in the code. If you don't know that output_uri in TASK's (!) init is relevant, you would never know...

  
  
Posted 2 years ago

I am not sure if it the fact the name of the file ends with .model is an issue - but that would be somewhat crazy design...

  
  
Posted 2 years ago

We're certainly working hard on improving the documentation (and I do apologize for the frustrating experience)

  
  
Posted 2 years ago

Exactly 🙂

  
  
Posted 2 years ago

@<1523701083040387072:profile|UnevenDolphin73> : How do you figure? In the past, my colleagues and I just shared the .zip file via email / MS Teams and it worked. So I don't think so.

  
  
Posted 2 years ago

But we do use S3

  
  
Posted 2 years ago

@<1523701087100473344:profile|SuccessfulKoala55> : I referenced this conversation in the issue None

  
  
Posted 2 years ago

But, I guess @<1523701070390366208:profile|CostlyOstrich36> wrote that in a different chat, right?

  
  
Posted 2 years ago
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