`mlem.api.save`: ML frameworks and Data formats support

[aguschin]

This is an epic to collect all ML frameworks / Data formats we would like to support, when you call mlem.api.save(mymodel, "model") or mlem.api.save(mydataset, "dataset").

ML frameworks:

• [x] Python functions (could be any function, but is treated as a ML model by MLEM. Specific framework support below means MLEM uses built-in framework serialization methods when possible)
• [x] Sklearn Models
• [x] Pytorch (including Keras)
• [x] Catboost
• [x] XGBoost
• [x] LightGBM
• [x] Tensorflow 2.0 (including Keras)
• [x] Onnx
• [x] Sparse matrices in scipy https://github.com/iterative/mlem/issues/540
• [x] Sklearn Transformers https://github.com/iterative/mlem/issues/514
• [x] Sklearn's CountVectorizer
• [x] Sklearn's IsolationForest
• [ ] Chainer
• [ ] MXNet
• [ ] Huggingface Transformers https://github.com/iterative/mlem/issues/265
• [ ] fast.ai
• [ ] Pytorch Lightning

Data formats:

• [x] Simple Python types (str, int, float, dict, etc)
• [x] Pandas
• [x] Numpy
• [x] Lightgbm
• [x] XGBoost

Please feel free to post a comment if you need something we don't support yet :)

[madhur-tandon]

we support lightgbm as well, updated the description.

[Snehashish-s]

I am getting a "mlem.core.errors.HookNotFound: No suitable ModelHook for object of type "IsolationForest" " exception when saving Isolationforest model, any way it can be solved ?

[aguschin]

Hi @Snehashish-s, rn MLEM doesn't support this, but it's pretty trivial to add by adding OutlierMixin to this line https://github.com/iterative/mlem/blob/main/mlem/contrib/sklearn.py#L31. Would you like contribute this and add a test?

[aguschin]

@Snehashish-s, I just supported IsolationForest in https://github.com/iterative/mlem/releases/tag/0.4.14