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Support modular designs for embedding and backbone module.
The currently supported modules are:
Embedding modules: identity feature_tokenizer (from Revisiting Deep Learning Models for Tabular Data)
Backbone modules: mlp transformer
Enhancements
Split reconstruction head for DAE and VIME: Implement separate reconstruction heads for categorical and continuous features, enhancing the handling of heterogeneous data.