Transformer Class on dataset
We can be pretty flexible and not impose any constraints for transforms.

Moreover, this library is designed to support datasets bigger than memory. The datasets are loaded from the disk via memory mapping, without filling up RAM. Even processing functions like `map` work in a batched fashion to not fill up your RAM. So this shouldn't be an issue
Just wondering if you have intenttion to create

TransformerClass :
    dataset --> dataset

and make determnistic transformation (ie not fit).






Transformer Class on dataset 
 Just wondering if you have intenttion to create

TransformerClass :
    dataset --> dataset

and make determnistic transformation (ie not fit).





 
 We can be pretty flexible and not impose any constraints for transforms.

Moreover, this library is designed to support datasets bigger than memory. The datasets are loaded from the disk via memory mapping, without filling up RAM. Even processing functions like `map` work in a batched fashion to not fill up your RAM. So this shouldn't be an issue