Token offsets computation fails when input is truncated

[Valahaar]

Describe the bug
Title. In classy/data/dataset/hf/classification.py#L89 we invoke self.tokenize (#L109) which correctly truncates the input.

The issue arises due to tuple(tok_encoding.word_to_tokens(wi)) for wi in range(len(tokens)): when a token is not included in the input due to truncation, word_to_tokens returns None, and tuple(None) raises a TypeError, which triggers the catch condition and makes the function return None, which cannot be unpacked in input_ids, token_offsets = self.tokenize(token_sample.tokens), resulting in another unhandled exception that finally crashes classy.

To Reproduce
In the token classification setting, input a sentence that has too many tokens (or reduce truncation to obtain the same effect).

Expected behaviour
I think there is a way to know how many of the original tokens were kept, and we can iterate over them instead of len(tokens), otherwise we can just iterate until word_to_tokens(wi) is not None. Comments?