


'''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_bart import BartTokenizer


lowerCAmelCase    :     str					=						logging.get_logger(__name__)


lowerCAmelCase    :     Optional[Any]					=						{"""vocab_file""": """vocab.json""", """merges_file""": """merges.txt""", """tokenizer_file""": """tokenizer.json"""}

# See all BART models at https://huggingface.co/models?filter=bart
lowerCAmelCase    :     Dict					=						{
    """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    :     Dict					=						{
    """facebook/bart-base""": 10_24,
    """facebook/bart-large""": 10_24,
    """facebook/bart-large-mnli""": 10_24,
    """facebook/bart-large-cnn""": 10_24,
    """facebook/bart-large-xsum""": 10_24,
    """yjernite/bart_eli5""": 10_24,
}
class 	UpperCamelCase__					( UpperCamelCase__	):



     """simple docstring"""






     __magic_name__    			=    VOCAB_FILES_NAMES
     __magic_name__    			=    PRETRAINED_VOCAB_FILES_MAP
     __magic_name__    			=    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     __magic_name__    			=    ["input_ids", "attention_mask"]
     __magic_name__    			=    BartTokenizer







     def __init__( self      ,	snake_case__=None      ,	snake_case__=None      ,	snake_case__=None      ,	snake_case__="replace"      ,	snake_case__="<s>"      ,	snake_case__="</s>"      ,	snake_case__="</s>"      ,	snake_case__="<s>"      ,	snake_case__="<unk>"      ,	snake_case__="<pad>"      ,	snake_case__="<mask>"      ,	snake_case__=False      ,	snake_case__=True      ,	**snake_case__      ,	):

            '''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    :							Dict   			=       json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()   )
            if pre_tok_state.get('add_prefix_space'      ,	_a   ) != add_prefix_space:
                   _lowerCAmelCase    :							Tuple   			=       getattr(_a      ,	pre_tok_state.pop('type'   )   )
                   _lowerCAmelCase    :							Union[str, Any]   			=       add_prefix_space
                   _lowerCAmelCase    :							List[str]   			=       pre_tok_class(**_a   )

            _lowerCAmelCase    :							List[Any]   			=       add_prefix_space

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

                   _lowerCAmelCase    :							str   			=       False

                   if state.get('add_prefix_space'      ,	_a   ) != add_prefix_space:
                          _lowerCAmelCase    :							Any   			=       add_prefix_space
                          _lowerCAmelCase    :							Dict   			=       True

                   if state.get('trim_offsets'      ,	_a   ) != trim_offsets:
                          _lowerCAmelCase    :							List[Any]   			=       trim_offsets
                          _lowerCAmelCase    :							Union[str, Any]   			=       True

                   if changes_to_apply:
                          _lowerCAmelCase    :							List[str]   			=       getattr(_a      ,	state.pop('type'   )   )
                          _lowerCAmelCase    :							int   			=       component_class(**_a   )
                          setattr(self.backend_tokenizer      ,	_a      ,	_a   )







     @property
     def a	( self   ):

            '''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      ,	snake_case__   ):

            '''simple docstring'''

            _lowerCAmelCase    :							Union[str, Any]   			=       AddedToken(_a      ,	lstrip=_a      ,	rstrip=_a   ) if isinstance(_a      ,	_a   ) else value
            _lowerCAmelCase    :							Any   			=       value







     def a	( self      ,	*snake_case__      ,	**snake_case__   ):

            '''simple docstring'''

            _lowerCAmelCase    :							Optional[int]   			=       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      ,	*snake_case__      ,	**snake_case__   ):

            '''simple docstring'''

            _lowerCAmelCase    :							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()._encode_plus(*_a      ,	**_a   )







     def a	( self      ,	snake_case__      ,	snake_case__ = None   ):

            '''simple docstring'''

            _lowerCAmelCase    :							Union[str, Any]   			=       self._tokenizer.model.save(_a      ,	name=_a   )
            return tuple(_a   )







     def a	( self      ,	snake_case__      ,	snake_case__=None   ):

            '''simple docstring'''

            _lowerCAmelCase    :							Any   			=       [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      ,	snake_case__      ,	snake_case__ = None   ):

            '''simple docstring'''

            _lowerCAmelCase    :							List[Any]   			=       [self.sep_token_id]
            _lowerCAmelCase    :							Tuple   			=       [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'''







lowerCAmelCase    :     Optional[int]					=						[sum(int(c, 10) ** 2 for c in i.__str__()) for i in range(10_00_00)]






def 			lowercase				(_A					):







       """simple docstring"""







       _lowerCAmelCase    :							str   			=       0
       while number:
              # Increased Speed Slightly by checking every 5 digits together.
              sum_of_digits_squared += DIGITS_SQUARED[number % 1_0_0_0_0_0]
              number //= 1_0_0_0_0_0

       return sum_of_digits_squared


# There are 2 Chains made,
# One ends with 89 with the chain member 58 being the one which when declared first,
# there will be the least number of iterations for all the members to be checked.

# The other one ends with 1 and has only one element 1.

# So 58 and 1 are chosen to be declared at the starting.

# Changed dictionary to an array to quicken the solution
lowerCAmelCase    :     list[bool | None]					=						[None] * 10_00_00_00
lowerCAmelCase    :     List[str]					=						True
lowerCAmelCase    :     Union[str, Any]					=						False






def 			lowercase				(_A					):







       """simple docstring"""







       if CHAINS[number - 1] is not None:
              return CHAINS[number - 1]  # type: ignore

       _lowerCAmelCase    :							Any   			=       chain(next_number(_A					)					)
       _lowerCAmelCase    :							List[str]   			=       number_chain

       while number < 1_0_0_0_0_0_0_0:
              _lowerCAmelCase    :							Tuple   			=       number_chain
              number *= 1_0

       return number_chain






def 			lowercase				(_A = 1_0_0_0_0_0_0_0					):







       """simple docstring"""







       for i in range(1   ,						_A					):
              if CHAINS[i] is None:
                     chain(i + 1					)

       return CHAINS[:number].count(_A					)


if __name__ == "__main__":
       import doctest

       doctest.testmod()
       print(F'''{solution() = }''')

