





import os
from shutil import copyfile
from typing import List, Optional, Tuple

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
       from .tokenization_pegasus import PegasusTokenizer
else:
       a__:      List[Any]									=		None


a__:      List[Any]									=		logging.get_logger(__name__)


a__:      Optional[Any]									=		'▁'

a__:      Tuple									=		{'vocab_file': 'spiece.model', 'tokenizer_file': 'tokenizer.json'}

a__:      List[Any]									=		{
    'vocab_file': {'google/pegasus-xsum': 'https://huggingface.co/google/pegasus-xsum/resolve/main/spiece.model'},
    'tokenizer_file': {
        'google/pegasus-xsum': 'https://huggingface.co/google/pegasus-xsum/resolve/main/tokenizer.json'
    },
}

a__:      Optional[Any]									=		{
    'google/pegasus-xsum': 512,
}




class     SCREAMING_SNAKE_CASE__ (						UpperCamelCase__      ):
 __SCREAMING_SNAKE_CASE							       =	VOCAB_FILES_NAMES
 __SCREAMING_SNAKE_CASE							       =	PRETRAINED_VOCAB_FILES_MAP
 __SCREAMING_SNAKE_CASE							       =	PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 __SCREAMING_SNAKE_CASE							       =	PegasusTokenizer
 __SCREAMING_SNAKE_CASE							       =	['''input_ids''', '''attention_mask''']



 def __init__(							self,__lowerCamelCase=None,__lowerCamelCase=None,__lowerCamelCase="<pad>",__lowerCamelCase="</s>",__lowerCamelCase="<unk>",__lowerCamelCase="<mask_2>",__lowerCamelCase="<mask_1>",__lowerCamelCase=None,__lowerCamelCase=103,**__lowerCamelCase,):
        A__											=						offset

        if additional_special_tokens is not None:
               if not isinstance(__lowerCamelCase,__lowerCamelCase ):
                      raise TypeError(
                          f"additional_special_tokens should be of type {type(__lowerCamelCase )}, but is"
                          f" {type(__lowerCamelCase )}" )

               A__											=						(
                   ([mask_token_sent] + additional_special_tokens)
                   if mask_token_sent not in additional_special_tokens and mask_token_sent is not None
                   else additional_special_tokens
               )
               # fill additional tokens with ..., <unk_token_102> in case not all additional tokens are already taken
               additional_special_tokens_extended += [
                   f"<unk_{i}>" for i in range(len(__lowerCamelCase ),self.offset - 1 )
               ]

               if len(set(__lowerCamelCase ) ) != len(__lowerCamelCase ):
                      raise ValueError(
                          '''Please make sure that the provided additional_special_tokens do not contain an incorrectly'''
                          f" shifted list of <unk_x> tokens. Found {additional_special_tokens_extended}." )
               A__											=						additional_special_tokens_extended
        else:
               A__											=						[mask_token_sent] if mask_token_sent is not None else []
               additional_special_tokens += [f"<unk_{i}>" for i in range(2,self.offset )]

        super().__init__(
            __lowerCamelCase,tokenizer_file=__lowerCamelCase,pad_token=__lowerCamelCase,eos_token=__lowerCamelCase,unk_token=__lowerCamelCase,mask_token=__lowerCamelCase,mask_token_sent=__lowerCamelCase,offset=__lowerCamelCase,additional_special_tokens=__lowerCamelCase,**__lowerCamelCase,)
        A__											=						vocab_file
        A__											=						False if not self.vocab_file else True



 def 				UpperCamelCase			(							self,__lowerCamelCase ):
        A__											=						set(self.all_special_ids )  # call it once instead of inside list comp
        all_special_ids.remove(self.unk_token_id )  # <unk> is only sometimes special

        if all_special_ids != set(range(len(self.additional_special_tokens ) + 3 ) ):
               raise ValueError(
                   '''There should be 3 special tokens: mask_token, pad_token, and eos_token +'''
                   f" {len(self.additional_special_tokens )} additional_special_tokens, but got {all_special_ids}" )

        return [1 if x in all_special_ids else 0 for x in seq]



 def 				UpperCamelCase			(							self,__lowerCamelCase,__lowerCamelCase = None,__lowerCamelCase = False ):
        if already_has_special_tokens:
               return self._special_token_mask(__lowerCamelCase )
        elif token_ids_a is None:
               return self._special_token_mask(__lowerCamelCase ) + [1]
        else:
               return self._special_token_mask(token_ids_a + token_ids_a ) + [1]



 def 				UpperCamelCase			(							self,__lowerCamelCase,__lowerCamelCase=None ):
        if token_ids_a is None:
               return token_ids_a + [self.eos_token_id]
        # We don't expect to process pairs, but leave the pair logic for API consistency
        return token_ids_a + token_ids_a + [self.eos_token_id]




 def 				UpperCamelCase			(							self,__lowerCamelCase,__lowerCamelCase = None ):
        if not self.can_save_slow_tokenizer:
               raise ValueError(
                   '''Your fast tokenizer does not have the necessary information to save the vocabulary for a slow '''
                   '''tokenizer.''' )

        if not os.path.isdir(__lowerCamelCase ):
               logger.error(f"Vocabulary path ({save_directory}) should be a directory" )
               return
        A__											=						os.path.join(
            __lowerCamelCase,(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file'''] )

        if os.path.abspath(self.vocab_file ) != os.path.abspath(__lowerCamelCase ):
               copyfile(self.vocab_file,__lowerCamelCase )

        return (out_vocab_file,)












from ..utils import DummyObject, requires_backends




class     SCREAMING_SNAKE_CASE__ (						metaclass=UpperCamelCase__      ):
 __SCREAMING_SNAKE_CASE							       =	['''keras_nlp''']



 def __init__(							self,*__lowerCamelCase,**__lowerCamelCase ):
        requires_backends(self,['''keras_nlp'''] )





