



"""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_albert import AlbertTokenizer
else:
	__snake_case							:     Optional[int]   =					None

__snake_case							:     int   =					logging.get_logger(__name__)
__snake_case							:     Union[str, Any]   =					{'vocab_file': 'spiece.model', 'tokenizer_file': 'tokenizer.json'}

__snake_case							:     List[str]   =					{
    'vocab_file': {
        'albert-base-v1': 'https://huggingface.co/albert-base-v1/resolve/main/spiece.model',
        'albert-large-v1': 'https://huggingface.co/albert-large-v1/resolve/main/spiece.model',
        'albert-xlarge-v1': 'https://huggingface.co/albert-xlarge-v1/resolve/main/spiece.model',
        'albert-xxlarge-v1': 'https://huggingface.co/albert-xxlarge-v1/resolve/main/spiece.model',
        'albert-base-v2': 'https://huggingface.co/albert-base-v2/resolve/main/spiece.model',
        'albert-large-v2': 'https://huggingface.co/albert-large-v2/resolve/main/spiece.model',
        'albert-xlarge-v2': 'https://huggingface.co/albert-xlarge-v2/resolve/main/spiece.model',
        'albert-xxlarge-v2': 'https://huggingface.co/albert-xxlarge-v2/resolve/main/spiece.model',
    },
    'tokenizer_file': {
        'albert-base-v1': 'https://huggingface.co/albert-base-v1/resolve/main/tokenizer.json',
        'albert-large-v1': 'https://huggingface.co/albert-large-v1/resolve/main/tokenizer.json',
        'albert-xlarge-v1': 'https://huggingface.co/albert-xlarge-v1/resolve/main/tokenizer.json',
        'albert-xxlarge-v1': 'https://huggingface.co/albert-xxlarge-v1/resolve/main/tokenizer.json',
        'albert-base-v2': 'https://huggingface.co/albert-base-v2/resolve/main/tokenizer.json',
        'albert-large-v2': 'https://huggingface.co/albert-large-v2/resolve/main/tokenizer.json',
        'albert-xlarge-v2': 'https://huggingface.co/albert-xlarge-v2/resolve/main/tokenizer.json',
        'albert-xxlarge-v2': 'https://huggingface.co/albert-xxlarge-v2/resolve/main/tokenizer.json',
    },
}

__snake_case							:     Any   =					{
    'albert-base-v1': 512,
    'albert-large-v1': 512,
    'albert-xlarge-v1': 512,
    'albert-xxlarge-v1': 512,
    'albert-base-v2': 512,
    'albert-large-v2': 512,
    'albert-xlarge-v2': 512,
    'albert-xxlarge-v2': 512,
}

__snake_case							:     Optional[Any]   =					'▁'



class     A__     (						__SCREAMING_SNAKE_CASE							):




	'''simple docstring'''





	SCREAMING_SNAKE_CASE					   =			VOCAB_FILES_NAMES
	SCREAMING_SNAKE_CASE					   =			PRETRAINED_VOCAB_FILES_MAP
	SCREAMING_SNAKE_CASE					   =			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
	SCREAMING_SNAKE_CASE					   =			AlbertTokenizer

	def __init__(  self:	Any ,    _SCREAMING_SNAKE_CASE:	Union[str, Any]=None ,    _SCREAMING_SNAKE_CASE:	Optional[int]=None ,    _SCREAMING_SNAKE_CASE:	Optional[int]=True ,    _SCREAMING_SNAKE_CASE:	Any=True ,    _SCREAMING_SNAKE_CASE:	Optional[Any]=False ,    _SCREAMING_SNAKE_CASE:	int="[CLS]" ,    _SCREAMING_SNAKE_CASE:	Dict="[SEP]" ,    _SCREAMING_SNAKE_CASE:	Optional[int]="<unk>" ,    _SCREAMING_SNAKE_CASE:	List[Any]="[SEP]" ,    _SCREAMING_SNAKE_CASE:	str="<pad>" ,    _SCREAMING_SNAKE_CASE:	int="[CLS]" ,    _SCREAMING_SNAKE_CASE:	Optional[Any]="[MASK]" ,    **_SCREAMING_SNAKE_CASE:	int ,    )       -> List[Any]:

				"""simple docstring"""

				__lowerCAmelCase   :						Dict				= (
				    AddedToken(_SCREAMING_SNAKE_CASE ,    lstrip=_SCREAMING_SNAKE_CASE ,    rstrip=_SCREAMING_SNAKE_CASE ,    normalized=_SCREAMING_SNAKE_CASE)
				    if isinstance(_SCREAMING_SNAKE_CASE ,    _SCREAMING_SNAKE_CASE)
				    else mask_token
				)

				super().__init__(
				    _SCREAMING_SNAKE_CASE ,    tokenizer_file=_SCREAMING_SNAKE_CASE ,    do_lower_case=_SCREAMING_SNAKE_CASE ,    remove_space=_SCREAMING_SNAKE_CASE ,    keep_accents=_SCREAMING_SNAKE_CASE ,    bos_token=_SCREAMING_SNAKE_CASE ,    eos_token=_SCREAMING_SNAKE_CASE ,    unk_token=_SCREAMING_SNAKE_CASE ,    sep_token=_SCREAMING_SNAKE_CASE ,    pad_token=_SCREAMING_SNAKE_CASE ,    cls_token=_SCREAMING_SNAKE_CASE ,    mask_token=_SCREAMING_SNAKE_CASE ,    **_SCREAMING_SNAKE_CASE ,    )

				__lowerCAmelCase   :						Tuple				= do_lower_case
				__lowerCAmelCase   :						str				= remove_space
				__lowerCAmelCase   :						str				= keep_accents
				__lowerCAmelCase   :						List[str]				= vocab_file
				__lowerCAmelCase   :						str				= False if not self.vocab_file else True

	def 							_SCREAMING_SNAKE_CASE     (  self:	int ,    _SCREAMING_SNAKE_CASE:	List[int] ,    _SCREAMING_SNAKE_CASE:	Optional[List[int]] = None)       -> List[int]:

				"""simple docstring"""

				__lowerCAmelCase   :						List[Any]				= [self.sep_token_id]
				__lowerCAmelCase   :						str				= [self.cls_token_id]
				if token_ids_a is None:
							return cls + token_ids_a + sep
				return cls + token_ids_a + sep + token_ids_a + sep

	def 							_SCREAMING_SNAKE_CASE     (  self:	Union[str, Any] ,    _SCREAMING_SNAKE_CASE:	List[int] ,    _SCREAMING_SNAKE_CASE:	Optional[List[int]] = None)       -> List[int]:

				"""simple docstring"""

				__lowerCAmelCase   :						Tuple				= [self.sep_token_id]
				__lowerCAmelCase   :						Union[str, Any]				= [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) * [0] + len(token_ids_a + sep) * [1]







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

				"""simple docstring"""

				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(_SCREAMING_SNAKE_CASE):
							logger.error(F"""Vocabulary path ({save_directory}) should be a directory""")
							return
				__lowerCAmelCase   :						List[Any]				= os.path.join(
				    _SCREAMING_SNAKE_CASE ,    (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"])

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

				return (out_vocab_file,)




"""simple docstring"""






def     _lowercase       (						__snake_case = 3      ,__snake_case = 7      ,__snake_case = 1_000_000			)		->     int:
			__lowerCAmelCase   :						Optional[Any]				= 0
			__lowerCAmelCase   :						List[str]				= 1

			for current_denominator in range(1      ,limit + 1			):
						__lowerCAmelCase   :						Optional[int]				= current_denominator * numerator // denominator
						if current_denominator % denominator == 0:
									current_numerator -= 1
						if current_numerator * max_denominator > current_denominator * max_numerator:
									__lowerCAmelCase   :						Union[str, Any]				= current_numerator
									__lowerCAmelCase   :						int				= current_denominator
			return max_numerator


if __name__ == "__main__":
	print(solution(numerator=3, denominator=7, limit=1_000_000))