Always update metadata in arrow schema
We store a redundant copy of the features in the metadata of the schema of the arrow table. This is used to recover the features when doing `Dataset.from_file`. These metadata are updated after each transfor, that changes the feature types.

For each function that transforms the feature types of the dataset, I added a step in the tests to make sure the metadata in the arrow schema are up to date.

I also added a line to update the metadata directly in the Dataset.__init__ method.
This way even a dataset instantiated with __init__ will have a table with the right metadata.

cc @mariosasko 