* fix, feat: Fixed inference processing data. Add transformation attribute.
* feat: Added transformations step, refractored the loop to make more sense (divided the train and inference loop).
* feat: Truncated models over time and transformations over time. Fixed some typing aswell.
* fix: Fixed a number of out of array problems.
* feat: Inference now works!
* fix(Steps): runtime error not checking for None
* fix(Steps): preloaded transformers are not optional anymore, sped up training by temporary increasing the retrain_every
* fix(CI): disable ray memory monitoring
* refactor(Inference): removed truncate_models and replaced it with filling X with NaN until inference should start
* feat(Inference): added index_from parameter
* fix(Tests): walk_forward test
* refactor(Pipeline): only predict one asset
* refactor(Inference): removed select_models step, inference code moved to run_inference.py so it matches convention (similar to run_pipeline.py)
* fix(Evaluation): adjust transaction costs
* fix(Config): adjusted retrain_every
Co-authored-by: Daniel Szemerey <szemereydaniel@gmail.com>
Co-authored-by: Mark Aron Szulyovszky <mark.szulyovszky@gmail.com>
Daniel Szemerey