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Support "unknown" model type #188

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mike0sv opened this issue Apr 6, 2022 · 3 comments
Open

Support "unknown" model type #188

mike0sv opened this issue Apr 6, 2022 · 3 comments
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ml-framework ML Framework support p2-medium Medium priority serialization Dumping and loading Python objects

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@mike0sv
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mike0sv commented Apr 6, 2022

For unsupported model types we can add a "mock" model_type.
This way we'll enable users to use different mlem commands that dont need to load actual model like clone.
RN, the process is python model obj -> getting model type with analyzer (methods, requirements, io)-> producing artifacts from ModelIO -> saving metadata
For unknown models, users can do analyzers work manually like this
python model object -> user saves model manually -> generates empty metadata from files like ModelMeta.from_files(...) -> optionally fills metadata manually (adding requirements and stuff) -> saves metadata

@aguschin aguschin added serialization Dumping and loading Python objects ml-framework ML Framework support labels May 31, 2022
@mike0sv mike0sv added this to the Q3 milestone Jun 1, 2022
@aguschin aguschin added the p1-high High priority label Nov 9, 2022
@aguschin
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aguschin commented Nov 9, 2022

@mike0sv, is this still an issue? This related to that discord question we had recently.

@aguschin aguschin removed this from the Q3 milestone Nov 9, 2022
@mike0sv
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mike0sv commented Nov 10, 2022

It's more of a feature proposal than an issue. Don't think it's relevant to that question either, it's basically about an API to manually create MlemModel objects more easily. Rn you can also do this of course, but in very unfriendly way

@mike0sv
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mike0sv commented Nov 10, 2022

I'd say it's p2 or even p3 btw

@aguschin aguschin added p2-medium Medium priority and removed p1-high High priority labels Nov 10, 2022
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Labels
ml-framework ML Framework support p2-medium Medium priority serialization Dumping and loading Python objects
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