add more flexibility in fast_wordpiece_tokenizer_model_builder pretokeniztion

there's only one pararmeter to control pretokeniztion on (white space, punctuation, chinese chars). and there is situation where you want to pretokenize in punctuation and white space only. I suggest adding two bool parameters one for punctuation and one for chinese.
furthermore, an approach for generalization is to add an array of pairs parameter, where it contains ranges of chars to pretokenize on it.

[Edit] I was working in a task for keras_nlp where this problem emerged. it's better to handle this problem here rather than in keras_nlp.

Start by locating fast_wordpiece_tokenizer_model_builder and reviewing how its current pretokenization parameter handles whitespace, punctuation, and Chinese characters. Clarify whether the intended scope is separate punctuation and Chinese switches or a generalized array of character ranges; done means the selected pretokenization boundaries are configurable and covered by tests.