






'''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_xlm_roberta import XLMRobertaTokenizer
else:
					lowerCamelCase_					:			int     						=				None


lowerCamelCase_					:			Dict     						=				logging.get_logger(__name__)

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

lowerCamelCase_					:			List[str]     						=				{
    '''vocab_file''': {
        '''xlm-roberta-base''': '''https://huggingface.co/xlm-roberta-base/resolve/main/sentencepiece.bpe.model''',
        '''xlm-roberta-large''': '''https://huggingface.co/xlm-roberta-large/resolve/main/sentencepiece.bpe.model''',
        '''xlm-roberta-large-finetuned-conll02-dutch''': (
            '''https://huggingface.co/xlm-roberta-large-finetuned-conll02-dutch/resolve/main/sentencepiece.bpe.model'''
        ),
        '''xlm-roberta-large-finetuned-conll02-spanish''': (
            '''https://huggingface.co/xlm-roberta-large-finetuned-conll02-spanish/resolve/main/sentencepiece.bpe.model'''
        ),
        '''xlm-roberta-large-finetuned-conll03-english''': (
            '''https://huggingface.co/xlm-roberta-large-finetuned-conll03-english/resolve/main/sentencepiece.bpe.model'''
        ),
        '''xlm-roberta-large-finetuned-conll03-german''': (
            '''https://huggingface.co/xlm-roberta-large-finetuned-conll03-german/resolve/main/sentencepiece.bpe.model'''
        ),
    },
    '''tokenizer_file''': {
        '''xlm-roberta-base''': '''https://huggingface.co/xlm-roberta-base/resolve/main/tokenizer.json''',
        '''xlm-roberta-large''': '''https://huggingface.co/xlm-roberta-large/resolve/main/tokenizer.json''',
        '''xlm-roberta-large-finetuned-conll02-dutch''': (
            '''https://huggingface.co/xlm-roberta-large-finetuned-conll02-dutch/resolve/main/tokenizer.json'''
        ),
        '''xlm-roberta-large-finetuned-conll02-spanish''': (
            '''https://huggingface.co/xlm-roberta-large-finetuned-conll02-spanish/resolve/main/tokenizer.json'''
        ),
        '''xlm-roberta-large-finetuned-conll03-english''': (
            '''https://huggingface.co/xlm-roberta-large-finetuned-conll03-english/resolve/main/tokenizer.json'''
        ),
        '''xlm-roberta-large-finetuned-conll03-german''': (
            '''https://huggingface.co/xlm-roberta-large-finetuned-conll03-german/resolve/main/tokenizer.json'''
        ),
    },
}

lowerCamelCase_					:			List[str]     						=				{
    '''xlm-roberta-base''': 512,
    '''xlm-roberta-large''': 512,
    '''xlm-roberta-large-finetuned-conll02-dutch''': 512,
    '''xlm-roberta-large-finetuned-conll02-spanish''': 512,
    '''xlm-roberta-large-finetuned-conll03-english''': 512,
    '''xlm-roberta-large-finetuned-conll03-german''': 512,
}
class  _SCREAMING_SNAKE_CASE				(		SCREAMING_SNAKE_CASE						):


			'''simple docstring'''





			__a				:				List[Any]         =       VOCAB_FILES_NAMES
			__a				:				Tuple         =       PRETRAINED_VOCAB_FILES_MAP
			__a				:				Union[str, Any]         =       PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			__a				:				int         =       ["input_ids", "attention_mask"]
			__a				:				str         =       XLMRobertaTokenizer






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

									'''simple docstring'''







									UpperCamelCase__       =			AddedToken(lowercase			,   lstrip=lowercase			,   rstrip=lowercase      ) if isinstance(lowercase			,   lowercase      ) else mask_token

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

									UpperCamelCase__       =			vocab_file
									UpperCamelCase__       =			False if not self.vocab_file else True






			def 					A   ( self				:    List[str]			,   lowercase				:    List[int]			,   lowercase				:    Optional[List[int]] = None      )				->     List[int]:

									'''simple docstring'''







									if token_ids_a is None:
															return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
									UpperCamelCase__       =			[self.cls_token_id]
									UpperCamelCase__       =			[self.sep_token_id]
									return cls + token_ids_a + sep + sep + token_ids_a + sep






			def 					A   ( self				:    str			,   lowercase				:    List[int]			,   lowercase				:    Optional[List[int]] = None      )				->     List[int]:

									'''simple docstring'''







									UpperCamelCase__       =			[self.sep_token_id]
									UpperCamelCase__       =			[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 					A   ( self				:    List[str]			,   lowercase				:    str			,   lowercase				:    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(lowercase      ):
															logger.error(f"Vocabulary path ({save_directory}) should be a directory."      )
															return
									UpperCamelCase__       =			os.path.join(
									    lowercase			,   (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]      )

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

									return (out_vocab_file,)








'''simple docstring'''


def 						__magic_name__(			_A       ):
						'''simple docstring'''





						UpperCamelCase__       =			len(_A       )

						# Set the gap value to be decreased by a factor of 1.3
						# after each iteration
						UpperCamelCase__       =			1.3

						# Continue sorting until the gap is 1
						while gap > 1:
												# Decrease the gap value
												UpperCamelCase__       =			int(gap / shrink       )

												# Sort the elements using insertion sort
												for i in range(_A    ,   len(_A       )       ):
																		UpperCamelCase__       =			collection[i]
																		UpperCamelCase__       =			i
																		while j >= gap and collection[j - gap] > temp:
																								UpperCamelCase__       =			collection[j - gap]
																								j -= gap
																		UpperCamelCase__       =			temp

						return collection


if __name__ == "__main__":
					import doctest

					doctest.testmod()
