paddlenlp/transformers/t5/tokenizer.py
def batch_decode(self,
                     sequences,
                     skip_special_tokens=False,
                     clean_up_tokenization_spaces=True):
        """
        Convert a list of lists of token ids into a list of strings by calling decode.

        Args:
            sequences (Union[List[int], List[List[int]], Tensor]):
                List of tokenized input ids.
            skip_special_tokens (bool, optional):
                Whether or not to remove special tokens in the decoding. Defaults to `False`.
            clean_up_tokenization_spaces (bool, optional):
                Whether or not to clean up the tokenization spaces. Defaults to `True`.

        Returns:
            List[str]: The list of decoded sentences.
        """
        return [
            self.decode(
                seq,
                skip_special_tokens=skip_special_tokens,
                clean_up_tokenization_spaces=clean_up_tokenization_spaces)
            for seq in sequences
        ]

        Convert a list of lists of token ids into a list of strings by calling decode.

        Args:
            sequences (Union[List[int], List[List[int]], Tensor]):
                List of tokenized input ids.
            skip_special_tokens (bool, optional):
                Whether or not to remove special tokens in the decoding. Defaults to `False`.
            clean_up_tokenization_spaces (bool, optional):
                Whether or not to clean up the tokenization spaces. Defaults to `True`.

        Returns:
            List[str]: The list of decoded sentences.
        
Convert a list of lists of token ids into a list of strings by calling decode.
Convert a list of lists of token ids into a list of strings by calling decode .
def batch_decode(self,
                     sequences,
                     skip_special_tokens=False,
                     clean_up_tokenization_spaces=True):
        return [
            self.decode(
                seq,
                skip_special_tokens=skip_special_tokens,
                clean_up_tokenization_spaces=clean_up_tokenization_spaces)
            for seq in sequences
        ]
def batch_decode ( self , sequences , skip_special_tokens = False , clean_up_tokenization_spaces = True ) : return [ self . decode ( seq , skip_special_tokens = skip_special_tokens , clean_up_tokenization_spaces = clean_up_tokenization_spaces ) for seq in sequences ]
Convert a list of lists of token ids into a list of strings by calling decode.
Convert a list of lists of token ids into a list of strings by calling decode .
"""
        Convert a list of lists of token ids into a list of strings by calling decode.

        Args:
            sequences (Union[List[int], List[List[int]], Tensor]):
                List of tokenized input ids.
            skip_special_tokens (bool, optional):
                Whether or not to remove special tokens in the decoding. Defaults to `False`.
            clean_up_tokenization_spaces (bool, optional):
                Whether or not to clean up the tokenization spaces. Defaults to `True`.

        Returns:
            List[str]: The list of decoded sentences.
        """
The list of decoded sentences.
The list of decoded sentences .
List[str]
self
sequences
List of tokenized input ids.
List of tokenized input ids .
skip_special_tokens
Whether or not to remove special tokens in the decoding. Defaults to `False`.
Whether or not to remove special tokens in the decoding . Defaults to ` False ` .
`False`
clean_up_tokenization_spaces
Whether or not to clean up the tokenization spaces. Defaults to `True`.
Whether or not to clean up the tokenization spaces . Defaults to ` True ` .
`True`