Migrate to Pydantic v2 #1748
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Migrate to Pydantic v2 #1748
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jesse-c
commented
May 8, 2024
jesse-c
commented
May 8, 2024
jesse-c
commented
May 8, 2024
Closed
> Pydantic V1 Pydantic V2 > .. > parse_obj() model_validate() [1] [1] https://docs.pydantic.dev/latest/migration/#changes-to-pydanticbasemodel
> underscore_attrs_are_private — the Pydantic V2 behavior is now the same as if this was always set to True in Pydantic V1. [1] [1] https://docs.pydantic.dev/latest/migration/#changes-to-config
> In Pydantic V2, the performance gap between BaseModel.__init__ and BaseModel.model_construct has been narrowed considerably. For simple models, calling BaseModel.__init__ may even be faster. If you are using model_construct() for performance reasons, you may want to profile your use case before assuming that model_construct() is faster. [1] [1] https://docs.pydantic.dev/latest/concepts/models/#creating-models-without-validation
It was previously a `MagicMock` for the model's `predict` function response. This ensures that there's a dummy value available.
This class only has these 2 fields [1]. The class it's coming from has different ones [2]. [1] https://github.com/jesse-c/MLServer/blob/c4e3719fab419480ec87d1482deccb1c93ba16a6/mlserver/types/dataplane.py#L64-L66 [2] https://github.com/jesse-c/MLServer/blob/c4e3719fab419480ec87d1482deccb1c93ba16a6/mlserver/types/dataplane.py#L109
I've changed tasks as well avoid a `can_generate` error on the default chosen model for the question-answering task. ``` E ValueError: Asked to export a gpt2 model for the task question-answering, but the Optimum ONNX exporter only supports the tasks feature-extraction, feature-extraction-with-past, text-generation, text-generation-with-past, text-classification, token-classification for gpt2. Please use a supported task. Please open an issue at https://github.com/huggingface/optimum/issues if you would like the task question-answering to be supported in the ONNX export for gpt2. ```
mauicv
approved these changes
May 10, 2024
|
Ran some manual smoke tests with no issues. |
jesse-c
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May 13, 2024
) These were missed in #1748.
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We're going for a wholesale update to Pydantic v2. Whilst I've tried to be as minimal as possible [1], I've fixed some things that were exposed during the migration [2]. Since we plan on this being a minor release, I've avoided any breaking changes in MLServer's interfaces.
It's a hefty PR. Each commit is an attempt at a self-contained part of the migration, and thus is best reviewed commit-by-commit. In saying that, it is of course a holistic change and a long line of dominoes.
For many of the commits, I've linked to the relevant part of the Pydantic v2 (migration) docs.
There will be manual integration testing as well.
[1] There's some deprecation warnings for v3 that I've looked past
[2] Example: Some incorrect tests
FIXES #1419