Util fixes #202
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Util fixes #202
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This pull request includes several changes to add new functionality, and enhance custom metric logging during training and validation. The most important changes include adding a new
encodemethod, enabling custom metric logging in thelightning_wrapper.pyfile and improving thepredictandevaluatefunctionality in the sklearn base classes to include batching during prediction/evaluation.New Functionality:
mambular/base_models/basemodel.py: Added a newencodemethod to generate contextualized embeddings.mambular/base_models/lightning_wrapper.py: Added a newpredict_stepmethod for making predictions on mini batches.mambular/base_models/lightning_wrapper.py: Introduced custom metrics for training, validation, and testing steps, allowing users to specify their own metrics.mambular/data_utils/dataset.py]: Changed order of getitem method and allowed for not providing labelsmambular/data_utils/datamodule.py]: Improved preprocessing new data and directly returning MambularDatasets. See sklearn base classes for clearer and cleaner predicting on unseen data.These changes collectively improve the maintainability and functionality of the package.