def count_vocab_items(self, token: Token, counter: Dict[(str, Dict[(str, int)])]):
    '\n        The :class:`Vocabulary` needs to assign indices to whatever strings we see in the training\n        data (possibly doing some frequency filtering and using an OOV, or out of vocabulary,\n        token).  This method takes a token and a dictionary of counts and increments counts for\n        whatever vocabulary items are present in the token.  If this is a single token ID\n        representation, the vocabulary item is likely the token itself.  If this is a token\n        characters representation, the vocabulary items are all of the characters in the token.\n        '
    raise NotImplementedError
The :class:`Vocabulary` needs to assign indices to whatever strings we see in the training
data (possibly doing some frequency filtering and using an OOV, or out of vocabulary,
token).  This method takes a token and a dictionary of counts and increments counts for
whatever vocabulary items are present in the token.  If this is a single token ID
representation, the vocabulary item is likely the token itself.  If this is a token
characters representation, the vocabulary items are all of the characters in the token.
def count_vocab_items(self, token: Token, counter: Dict[(str, Dict[(str, int)])]):
    '\n        The :class:`Vocabulary` needs to assign indices to whatever strings we see in the training\n        data (possibly doing some frequency filtering and using an OOV, or out of vocabulary,\n        token).  This method takes a token and a dictionary of counts and increments counts for\n        whatever vocabulary items are present in the token.  If this is a single token ID\n        representation, the vocabulary item is likely the token itself.  If this is a token\n        characters representation, the vocabulary items are all of the characters in the token.\n        '
    raise NotImplementedError