added embedding rules, MonteCarlo(uncertainty) prediction and removed running of the tests on draf requests

Removed condition from trainer on duplicated callbacks. Tab2Vec optionally returns pandas dataframes. Added unit tests for new functionalities and all notebooks follow now black coding style. All this relates to PR #55

code cleaned + added workaround for ¨ImportError: libGL.so.1: cannot open shared object file: No such file or directory ``` apt-get update apt-get install ffmpeg libsm6 libxext6  -y ```¨

* added RayTuneReporter callback
* adjusted history so it reports metrics per class in case of multiple values per metric. eg. multiple classes

* added notebook and 1 report for metrics

Added docs. Re-design Additive Atttention accoring to their code. Add a few details on the docs and fix a typo

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Added a proper implementation of transformer models when needed and re-organised the transformers module for clarity

First commit towards the perceiver. Changed modularity so that embeddings are consistent accross models. Adding the perceiver also forced me to change the structure of the TabTransformer and SAINT

Added cont norm options for all tabular models. Optimize cat embed for transformer models. Adjusted tab preprocessors for transformer models.

Fixed a series of breaking changes related to the metrics returning arrays. Adapted docs to the new functionalities

I kept almost all previous code as it was, I just added functionality for custom dataloaders and possibility to use torchmetrics

Refined documentation. Added some test for saving model. Added an example notebook. Ready to test installations and publish v1 to pypi

Added test for new trainer methods. Back to documentation style more in line with some popular packages like pytorch