paddlenlp/transformers/albert/tokenizer.py
def build_inputs_with_special_tokens(self, token_ids_0, token_ids_1=None):
        """
        Build model inputs from a sequence or a pair of sequence for sequence classification tasks by concatenating and
        adding special tokens.

        An Albert sequence has the following format:

        - single sequence:      ``[CLS] X [SEP]``
        - pair of sequences:        ``[CLS] A [SEP] B [SEP]``

        Args:
            token_ids_0 (List[int]):
                List of IDs to which the special tokens will be added.
            token_ids_1 (List[int], optional):
                Optional second list of IDs for sequence pairs. Defaults to None.

        Returns:
            List[int]: List of input_id with the appropriate special tokens.
        """
        return self.tokenizer.build_inputs_with_special_tokens(
            token_ids_0, token_ids_1=token_ids_1)

        Build model inputs from a sequence or a pair of sequence for sequence classification tasks by concatenating and
        adding special tokens.

        An Albert sequence has the following format:

        - single sequence:      ``[CLS] X [SEP]``
        - pair of sequences:        ``[CLS] A [SEP] B [SEP]``

        Args:
            token_ids_0 (List[int]):
                List of IDs to which the special tokens will be added.
            token_ids_1 (List[int], optional):
                Optional second list of IDs for sequence pairs. Defaults to None.

        Returns:
            List[int]: List of input_id with the appropriate special tokens.
        
Build model inputs from a sequence or a pair of sequence for sequence classification tasks by concatenating and
adding special tokens.

An Albert sequence has the following format.


Build model inputs from a sequence or a pair of sequence for sequence classification tasks by concatenating and adding special tokens . An Albert sequence has the following format .
def build_inputs_with_special_tokens(self, token_ids_0, token_ids_1=None):
        return self.tokenizer.build_inputs_with_special_tokens(
            token_ids_0, token_ids_1=token_ids_1)
def build_inputs_with_special_tokens ( self , token_ids_0 , token_ids_1 = None ) : return self . tokenizer . build_inputs_with_special_tokens ( token_ids_0 , token_ids_1 = token_ids_1 )
Build model inputs from a sequence or a pair of sequence for sequence classification tasks by concatenating and
adding special tokens.
Build model inputs from a sequence or a pair of sequence for sequence classification tasks by concatenating and adding special tokens .
"""
        Build model inputs from a sequence or a pair of sequence for sequence classification tasks by concatenating and
        adding special tokens.

        An Albert sequence has the following format:

        - single sequence:      ``[CLS] X [SEP]``
        - pair of sequences:        ``[CLS] A [SEP] B [SEP]``

        Args:
            token_ids_0 (List[int]):
                List of IDs to which the special tokens will be added.
            token_ids_1 (List[int], optional):
                Optional second list of IDs for sequence pairs. Defaults to None.

        Returns:
            List[int]: List of input_id with the appropriate special tokens.
        """
List of input_id with the appropriate special tokens.
List of input_id with the appropriate special tokens .
List[int]
self
token_ids_0
List of IDs to which the special tokens will be added.
List of IDs to which the special tokens will be added .
token_ids_1
Optional second list of IDs for sequence pairs. Defaults to None.
Optional second list of IDs for sequence pairs . Defaults to None .
None