* Fixed F1Score Import

* Linted example file with Black Linter

* update

* renamed var and removed from for loops

* refactored var

…apitalone#954)

A method signature that uses *args: Any, **kwargs: Any is compatible
with any set of arguments in mypy, despite being an LSP violation. This
lets us assert that subclasses of BaseDataProcessor should have some
process() method with an arbitrary signature.

We also add to the return type of BaseDataPreprocessor so that it is
inclusive of all of its subclasses.

Co-authored-by: JGSweets <[email protected]>

Inside the BaseDataProcessor class definition, references to
__subclasses are automatically replaced with
_BaseDataProcessor__subclasses. This remains the case even in static
methods _register_subclass() and get_class(). Same with BaseModel and
its __subclasses field. So we do not have to write out the full name
mangled identifiers inside the class definitions.

Also, mypy doesn't seem to be able to handle the return type of
BaseDataProcessor.get_class() being a typevar, so that was changed to
type[BaseDataProcessor]. This does not affect the functionality of
get_class() since it always returns a subclass of BaseDataProcessor.

The mypy errors addressed here occur because variables label_mapping
(in CharPreprocessor), unstructured_labels, and unstructured_label_set
(in StructCharPreprocessor.process()) have optional types when they're
used. This is fixed by checking that they are not None prior to the
operation, which mypy recognizes as removing the None type from them.

This should have no effect on functionality because we are already
checking that labels is not None, and the variables above all depend on
labels such that they are None only if labels is None.

capitalone#965)

* Changed release option to only release branches named \'release/<version-tag>\'.

* Reverted types

In the changed code, we had a mypy error because numpy ndarrays are not
compatible with random.Random.shuffle() (expected argument type is
MutableSequence[Any])

We fix this by first instantiating priority_order as a list, then
shuffling it, then creating an ndarray from it afterwards.