




import json
from typing import List, Optional, Tuple

from tokenizers import pre_tokenizers, processors

from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_bart import BartTokenizer


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


lowerCamelCase    :		int			   =       {"vocab_file": "vocab.json", "merges_file": "merges.txt", "tokenizer_file": "tokenizer.json"}

# See all BART models at https://huggingface.co/models?filter=bart
lowerCamelCase    :		Union[str, Any]			   =       {
    "vocab_file": {
        "facebook/bart-base": "https://huggingface.co/facebook/bart-base/resolve/main/vocab.json",
        "facebook/bart-large": "https://huggingface.co/facebook/bart-large/resolve/main/vocab.json",
        "facebook/bart-large-mnli": "https://huggingface.co/facebook/bart-large-mnli/resolve/main/vocab.json",
        "facebook/bart-large-cnn": "https://huggingface.co/facebook/bart-large-cnn/resolve/main/vocab.json",
        "facebook/bart-large-xsum": "https://huggingface.co/facebook/bart-large-xsum/resolve/main/vocab.json",
        "yjernite/bart_eli5": "https://huggingface.co/yjernite/bart_eli5/resolve/main/vocab.json",
    },
    "merges_file": {
        "facebook/bart-base": "https://huggingface.co/facebook/bart-base/resolve/main/merges.txt",
        "facebook/bart-large": "https://huggingface.co/facebook/bart-large/resolve/main/merges.txt",
        "facebook/bart-large-mnli": "https://huggingface.co/facebook/bart-large-mnli/resolve/main/merges.txt",
        "facebook/bart-large-cnn": "https://huggingface.co/facebook/bart-large-cnn/resolve/main/merges.txt",
        "facebook/bart-large-xsum": "https://huggingface.co/facebook/bart-large-xsum/resolve/main/merges.txt",
        "yjernite/bart_eli5": "https://huggingface.co/yjernite/bart_eli5/resolve/main/merges.txt",
    },
    "tokenizer_file": {
        "facebook/bart-base": "https://huggingface.co/facebook/bart-base/resolve/main/tokenizer.json",
        "facebook/bart-large": "https://huggingface.co/facebook/bart-large/resolve/main/tokenizer.json",
        "facebook/bart-large-mnli": "https://huggingface.co/facebook/bart-large-mnli/resolve/main/tokenizer.json",
        "facebook/bart-large-cnn": "https://huggingface.co/facebook/bart-large-cnn/resolve/main/tokenizer.json",
        "facebook/bart-large-xsum": "https://huggingface.co/facebook/bart-large-xsum/resolve/main/tokenizer.json",
        "yjernite/bart_eli5": "https://huggingface.co/yjernite/bart_eli5/resolve/main/tokenizer.json",
    },
}

lowerCamelCase    :		int			   =       {
    "facebook/bart-base": 1_024,
    "facebook/bart-large": 1_024,
    "facebook/bart-large-mnli": 1_024,
    "facebook/bart-large-cnn": 1_024,
    "facebook/bart-large-xsum": 1_024,
    "yjernite/bart_eli5": 1_024,
}







class   A(						UpperCamelCase       ):



	'''simple docstring'''


	UpperCamelCase						       =						VOCAB_FILES_NAMES
	UpperCamelCase						       =						PRETRAINED_VOCAB_FILES_MAP
	UpperCamelCase						       =						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
	UpperCamelCase						       =						['''input_ids''', '''attention_mask''']
	UpperCamelCase						       =						BartTokenizer

	def __init__(    self :  int						,							A_ :  int=None						,							A_ :  str=None						,							A_ :  Union[str, Any]=None						,							A_ :  Any="replace"						,							A_ :  Dict="<s>"						,							A_ :  List[Any]="</s>"						,							A_ :  List[Any]="</s>"						,							A_ :  Optional[int]="<s>"						,							A_ :  Optional[Any]="<unk>"						,							A_ :  str="<pad>"						,							A_ :  Tuple="<mask>"						,							A_ :  int=False						,							A_ :  str=True						,							**A_ :  Tuple						,							)       ->     Optional[Any]:

							"""simple docstring"""






							super().__init__(
							    A_						,							A_						,							tokenizer_file=A_						,							errors=A_						,							bos_token=A_						,							eos_token=A_						,							sep_token=A_						,							cls_token=A_						,							unk_token=A_						,							pad_token=A_						,							mask_token=A_						,							add_prefix_space=A_						,							trim_offsets=A_						,							**A_						,							)

							lowerCamelCase_							=   json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()  )
							if pre_tok_state.get('add_prefix_space'						,							A_  ) != add_prefix_space:
													lowerCamelCase_							=   getattr(A_						,							pre_tok_state.pop('type'  )  )
													lowerCamelCase_							=   add_prefix_space
													lowerCamelCase_							=   pre_tok_class(**A_  )

							lowerCamelCase_							=   add_prefix_space

							# the pre_tokenizer is already updated in the GPT2TokenizerFast `__init__`
							lowerCamelCase_							=   'post_processor'
							lowerCamelCase_							=   getattr(self.backend_tokenizer						,							A_						,							A_  )
							if tokenizer_component_instance:
													lowerCamelCase_							=   json.loads(tokenizer_component_instance.__getstate__()  )

													# The lists 'sep' and 'cls' must be cased in tuples for the object `post_processor_class`
													if "sep" in state:
																			lowerCamelCase_							=   tuple(state['sep']  )
													if "cls" in state:
																			lowerCamelCase_							=   tuple(state['cls']  )

													lowerCamelCase_							=   False

													if state.get('add_prefix_space'						,							A_  ) != add_prefix_space:
																			lowerCamelCase_							=   add_prefix_space
																			lowerCamelCase_							=   True

													if state.get('trim_offsets'						,							A_  ) != trim_offsets:
																			lowerCamelCase_							=   trim_offsets
																			lowerCamelCase_							=   True

													if changes_to_apply:
																			lowerCamelCase_							=   getattr(A_						,							state.pop('type'  )  )
																			lowerCamelCase_							=   component_class(**A_  )
																			setattr(self.backend_tokenizer						,							A_						,							A_  )

	@property
	def     a__			(    self :  Optional[Any]  )       ->     str:

							"""simple docstring"""






							if self._mask_token is None:
													if self.verbose:
																			logger.error('Using mask_token, but it is not set yet.'  )
													return None
							return str(self._mask_token  )

	@mask_token.setter
	def     a__			(    self :  Union[str, Any]						,							A_ :  Any  )       ->     int:

							"""simple docstring"""






							lowerCamelCase_							=   AddedToken(A_						,							lstrip=A_						,							rstrip=A_  ) if isinstance(A_						,							A_  ) else value
							lowerCamelCase_							=   value

	def     a__			(    self :  List[str]						,							*A_ :  str						,							**A_ :  Any  )       ->     BatchEncoding:

							"""simple docstring"""






							lowerCamelCase_							=   kwargs.get('is_split_into_words'						,							A_  )

							if is_split_into_words and not self.add_prefix_space:
													raise ValueError(
													    f"""You need to instantiate {self.__class__.__name__} with add_prefix_space=True """
													    'to use it with pretokenized inputs.'  )

							return super()._batch_encode_plus(*A_						,							**A_  )

	def     a__			(    self :  Union[str, Any]						,							*A_ :  Optional[int]						,							**A_ :  Any  )       ->     BatchEncoding:

							"""simple docstring"""






							lowerCamelCase_							=   kwargs.get('is_split_into_words'						,							A_  )

							if is_split_into_words and not self.add_prefix_space:
													raise ValueError(
													    f"""You need to instantiate {self.__class__.__name__} with add_prefix_space=True """
													    'to use it with pretokenized inputs.'  )

							return super()._encode_plus(*A_						,							**A_  )

	def     a__			(    self :  str						,							A_ :  str						,							A_ :  Optional[str] = None  )       ->     Tuple[str]:

							"""simple docstring"""






							lowerCamelCase_							=   self._tokenizer.model.save(A_						,							name=A_  )
							return tuple(A_  )

	def     a__			(    self :  Union[str, Any]						,							A_ :  Optional[Any]						,							A_ :  Any=None  )       ->     str:

							"""simple docstring"""






							lowerCamelCase_							=   [self.bos_token_id] + token_ids_a + [self.eos_token_id]
							if token_ids_a is None:
													return output

							return output + [self.eos_token_id] + token_ids_a + [self.eos_token_id]





	def     a__			(    self :  Optional[Any]						,							A_ :  List[int]						,							A_ :  Optional[List[int]] = None  )       ->     List[int]:

							"""simple docstring"""






							lowerCamelCase_							=   [self.sep_token_id]
							lowerCamelCase_							=   [self.cls_token_id]

							if token_ids_a is None:
													return len(cls + token_ids_a + sep  ) * [0]
							return len(cls + token_ids_a + sep + sep + token_ids_a + sep  ) * [0]









from ..utils import DummyObject, requires_backends







class   A(						metaclass=UpperCamelCase       ):



 '''simple docstring'''


 UpperCamelCase						       =						['''keras_nlp''']

 def __init__(    self :  Optional[int]						,							*A_ :  Any						,							**A_ :  Dict  )       ->     Optional[int]:

       """simple docstring"""






       requires_backends(self						,							['keras_nlp']  )



