




"""simple docstring"""
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_mvp import MvpTokenizer


a_				:    List[str]										=     logging.get_logger(__name__)


a_				:    Optional[int]										=     {'''vocab_file''': '''vocab.json''', '''merges_file''': '''merges.txt''', '''tokenizer_file''': '''tokenizer.json'''}

# See all MVP models at https://huggingface.co/models?filter=mvp
a_				:    str										=     {
    '''vocab_file''': {
        '''RUCAIBox/mvp''': '''https://huggingface.co/RUCAIBox/mvp/resolve/main/vocab.json''',
    },
    '''added_tokens.json''': {
        '''RUCAIBox/mvp''': '''https://huggingface.co/RUCAIBox/mvp/resolve/main/added_tokens.json''',
    },
    '''merges_file''': {
        '''RUCAIBox/mvp''': '''https://huggingface.co/RUCAIBox/mvp/resolve/main/merges.txt''',
    },
    '''tokenizer_file''': {
        '''RUCAIBox/mvp''': '''https://huggingface.co/RUCAIBox/mvp/resolve/main/tokenizer.json''',
    },
}

a_				:    Optional[int]										=     {
    '''RUCAIBox/mvp''': 10_24,
}

class __lowercase(      lowercase__				):




     '''simple docstring'''


     __a						:						str     		= VOCAB_FILES_NAMES
     __a						:						Tuple     		= PRETRAINED_VOCAB_FILES_MAP
     __a						:						int     		= PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     __a						:						Optional[Any]     		= ['input_ids', 'attention_mask']
     __a						:						List[str]     		= MvpTokenizer
     def __init__(    self						,	__a=None						,	__a=None						,	__a=None						,	__a="replace"						,	__a="<s>"						,	__a="</s>"						,	__a="</s>"						,	__a="<s>"						,	__a="<unk>"						,	__a="<pad>"						,	__a="<mask>"						,	__a=False						,	__a=True						,	**__a						,	):
        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					:	Dict	       =				json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()     )
        if pre_tok_state.get('add_prefix_space'						,	__a     ) != add_prefix_space:
           __lowerCamelCase					:	Optional[Any]	       =				getattr(__a						,	pre_tok_state.pop('type'     )     )
           __lowerCamelCase					:	int	       =				add_prefix_space
           __lowerCamelCase					:	Any	       =				pre_tok_class(**__a     )

        __lowerCamelCase					:	str	       =				add_prefix_space

        # the pre_tokenizer is already updated in the GPT2TokenizerFast `__init__`
        __lowerCamelCase					:	Union[str, Any]	       =				'post_processor'
        __lowerCamelCase					:	str	       =				getattr(self.backend_tokenizer						,	__a						,	__a     )
        if tokenizer_component_instance:
           __lowerCamelCase					:	Union[str, Any]	       =				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	       =				tuple(state['sep']     )
           if "cls" in state:
              __lowerCamelCase					:	Dict	       =				tuple(state['cls']     )

           __lowerCamelCase					:	List[str]	       =				False

           if state.get('add_prefix_space'						,	__a     ) != add_prefix_space:
              __lowerCamelCase					:	Optional[Any]	       =				add_prefix_space
              __lowerCamelCase					:	List[Any]	       =				True

           if state.get('trim_offsets'						,	__a     ) != trim_offsets:
              __lowerCamelCase					:	Optional[int]	       =				trim_offsets
              __lowerCamelCase					:	str	       =				True

           if changes_to_apply:
              __lowerCamelCase					:	Dict	       =				getattr(__a						,	state.pop('type'     )     )
              __lowerCamelCase					:	Optional[int]	       =				component_class(**__a     )
              setattr(self.backend_tokenizer						,	__a						,	__a     )
     @property
     def     snake_case_				(    self     ):
        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     snake_case_				(    self						,	__a     ):
        __lowerCamelCase					:	List[str]	       =				AddedToken(__a						,	lstrip=__a						,	rstrip=__a     ) if isinstance(__a						,	__a     ) else value
        __lowerCamelCase					:	int	       =				value
     def     snake_case_				(    self						,	*__a						,	**__a     ):
        __lowerCamelCase					:	List[str]	       =				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     snake_case_				(    self						,	*__a						,	**__a     ):
        __lowerCamelCase					:	Optional[Any]	       =				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     snake_case_				(    self						,	__a						,	__a = None     ):
        __lowerCamelCase					:	Optional[Any]	       =				self._tokenizer.model.save(__a						,	name=__a     )
        return tuple(__a     )
     def     snake_case_				(    self						,	__a						,	__a=None     ):
        __lowerCamelCase					:	Optional[int]	       =				[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     snake_case_				(    self						,	__a						,	__a = None     ):
        __lowerCamelCase					:	List[Any]	       =				[self.sep_token_id]
        __lowerCamelCase					:	Dict	       =				[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]









"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple

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


if is_sentencepiece_available():
					from .tokenization_barthez import BarthezTokenizer
else:
					a_				:    List[str]										=     None

a_				:    Any										=     logging.get_logger(__name__)

a_				:    List[Any]										=     {'''vocab_file''': '''sentencepiece.bpe.model''', '''tokenizer_file''': '''tokenizer.json'''}

a_				:    int										=     {
    '''vocab_file''': {
        '''moussaKam/mbarthez''': '''https://huggingface.co/moussaKam/mbarthez/resolve/main/sentencepiece.bpe.model''',
        '''moussaKam/barthez''': '''https://huggingface.co/moussaKam/barthez/resolve/main/sentencepiece.bpe.model''',
        '''moussaKam/barthez-orangesum-title''': (
            '''https://huggingface.co/moussaKam/barthez-orangesum-title/resolve/main/sentencepiece.bpe.model'''
        ),
    },
    '''tokenizer_file''': {
        '''moussaKam/mbarthez''': '''https://huggingface.co/moussaKam/mbarthez/resolve/main/tokenizer.json''',
        '''moussaKam/barthez''': '''https://huggingface.co/moussaKam/barthez/resolve/main/tokenizer.json''',
        '''moussaKam/barthez-orangesum-title''': (
            '''https://huggingface.co/moussaKam/barthez-orangesum-title/resolve/main/tokenizer.json'''
        ),
    },
}

a_				:    Any										=     {
    '''moussaKam/mbarthez''': 10_24,
    '''moussaKam/barthez''': 10_24,
    '''moussaKam/barthez-orangesum-title''': 10_24,
}

a_				:    Union[str, Any]										=     '''▁'''

class __lowercase(      lowercase__				):




					'''simple docstring'''


					__a						:						Optional[Any]     		= VOCAB_FILES_NAMES
					__a						:						Optional[int]     		= PRETRAINED_VOCAB_FILES_MAP
					__a						:						List[str]     		= PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
					__a						:						Union[str, Any]     		= ['input_ids', 'attention_mask']
					__a						:						Optional[Any]     		= BarthezTokenizer
					def __init__(    self						,	__a=None						,	__a=None						,	__a="<s>"						,	__a="</s>"						,	__a="</s>"						,	__a="<s>"						,	__a="<unk>"						,	__a="<pad>"						,	__a="<mask>"						,	**__a						,	):
								# Mask token behave like a normal word, i.e. include the space before it
								__lowerCamelCase					:	Optional[Any]	       =				AddedToken(__a						,	lstrip=__a						,	rstrip=__a     ) if isinstance(__a						,	__a     ) else mask_token

								super().__init__(
								    __a						,	tokenizer_file=__a						,	bos_token=__a						,	eos_token=__a						,	unk_token=__a						,	sep_token=__a						,	cls_token=__a						,	pad_token=__a						,	mask_token=__a						,	**__a						,	)

								__lowerCamelCase					:	Tuple	       =				vocab_file
								__lowerCamelCase					:	List[str]	       =				False if not self.vocab_file else True
					def     snake_case_				(    self						,	__a						,	__a = None     ):

								if token_ids_a is None:
											return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
								__lowerCamelCase					:	Optional[Any]	       =				[self.cls_token_id]
								__lowerCamelCase					:	Dict	       =				[self.sep_token_id]
								return cls + token_ids_a + sep + sep + token_ids_a + sep
					def     snake_case_				(    self						,	__a						,	__a = None     ):
								__lowerCamelCase					:	Optional[int]	       =				[self.sep_token_id]
								__lowerCamelCase					:	int	       =				[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]





					def     snake_case_				(    self						,	__a						,	__a = 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(__a     ):
											logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''     )
											return
								__lowerCamelCase					:	List[Any]	       =				os.path.join(
								    __a						,	(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']     )

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

								return (out_vocab_file,)



