We have the following, works fine (we also use internal zip packaging for our models):

model = OutputModel(task=self.task, name=self.job_name, tags=kwargs.get('tags', self.task.get_tags()), framework=framework)
model.connect(task=self.task, name=self.job_name)
model.update_weights(weights_filename=cc_model.save())

Exactly 🙂

Hi @<1523704157695905792:profile|VivaciousBadger56> , you can configure Task.init(..., output_uri=True) and this will save the models to the clearml file server

FWIW It’s also listed in other places @<1523704157695905792:profile|VivaciousBadger56> , e.g. None says:

In order to make sure we also automatically upload the model snapshot (instead of saving its local path), we need to pass a storage location for the model files to be uploaded to.
For example, upload all snapshots to an S3 bucket…

Unbelievable! That worked.

From the one you sent - None

I have already been trying to contribute (have three pull requests), but honestly I feel it is a bit weird, that I need to update a documentation about something I do not understand, while I actually try to evaluate if ClearML is the right tool for our company...

@<1523701083040387072:profile|UnevenDolphin73> : I do not see any way to download the model manually from the web app either. All I see is the link to the file on my harddrive (see shreenshot).

The second process says there is not file at all. I think, all that happened is that the update_weights only uploaded the location of the .zip file (which we denote as a .model file) on my harddrive, but not the file itself.

@<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".

It should store it on the fileserver, perhaps you're missing a configuration option somewhere?

@<1523704157695905792:profile|VivaciousBadger56> It seems like whatever you pickled in the zip file relies on some additional files that are not pickled.

Heh, good @<1523704157695905792:profile|VivaciousBadger56> 😁
I was just repeating what @<1523701070390366208:profile|CostlyOstrich36> suggested, credits to him

But we do use S3

@<1523701087100473344:profile|SuccessfulKoala55> Also, I think that - in this case, but also in other cases - the issue is not just the documentation, but also the design of the SDK.

@<1523701083040387072:profile|UnevenDolphin73>