

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:
							__UpperCamelCase						:   Optional[Any]							   =	None


__UpperCamelCase						:   Any							   =	logging.get_logger(__name__)

__UpperCamelCase						:   Dict							   =	{'''vocab_file''': '''sentencepiece.bpe.model''', '''tokenizer_file''': '''tokenizer.json'''}

__UpperCamelCase						:   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'''
        ),
    },
}

__UpperCamelCase						:   Union[str, Any]							   =	{
    '''xlm-roberta-base''': 5_1_2,
    '''xlm-roberta-large''': 5_1_2,
    '''xlm-roberta-large-finetuned-conll02-dutch''': 5_1_2,
    '''xlm-roberta-large-finetuned-conll02-spanish''': 5_1_2,
    '''xlm-roberta-large-finetuned-conll03-english''': 5_1_2,
    '''xlm-roberta-large-finetuned-conll03-german''': 5_1_2,
}







class        SCREAMING_SNAKE_CASE      (	lowerCamelCase__ ):






					"""simple docstring"""



					lowercase__       				= VOCAB_FILES_NAMES
					lowercase__       				= PRETRAINED_VOCAB_FILES_MAP
					lowercase__       				= PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
					lowercase__       				= ["input_ids", "attention_mask"]
					lowercase__       				= XLMRobertaTokenizer







					def __init__( self    :       List[Any]     ,lowercase_    :       Tuple=None     ,lowercase_    :       Optional[int]=None     ,lowercase_    :       Union[str, Any]="<s>"     ,lowercase_    :       Optional[int]="</s>"     ,lowercase_    :       str="</s>"     ,lowercase_    :       Any="<s>"     ,lowercase_    :       List[str]="<unk>"     ,lowercase_    :       int="<pad>"     ,lowercase_    :       int="<mask>"     ,**lowercase_    :       str     ,):
						# Mask token behave like a normal word, i.e. include the space before it
						lowerCAmelCase__			:		Tuple						       =			AddedToken(SCREAMING_SNAKE_CASE_     ,lstrip=SCREAMING_SNAKE_CASE_     ,rstrip=SCREAMING_SNAKE_CASE_	) if isinstance(SCREAMING_SNAKE_CASE_     ,SCREAMING_SNAKE_CASE_	) else mask_token

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

						lowerCAmelCase__			:		Union[str, Any]						       =			vocab_file
						lowerCAmelCase__			:		Tuple						       =			False if not self.vocab_file else True







					def  __lowerCAmelCase				( self    :       Optional[Any]     ,lowercase_    :       List[int]     ,lowercase_    :       Optional[List[int]] = 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__			:		str						       =			[self.sep_token_id]
						return cls + token_ids_a + sep + sep + token_ids_a + sep







					def  __lowerCAmelCase				( self    :       Dict     ,lowercase_    :       List[int]     ,lowercase_    :       Optional[List[int]] = None	):
						lowerCAmelCase__			:		List[str]						       =			[self.sep_token_id]
						lowerCAmelCase__			:		str						       =			[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  __lowerCAmelCase				( self    :       Union[str, Any]     ,lowercase_    :       str     ,lowercase_    :       Optional[str] = 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(SCREAMING_SNAKE_CASE_	):
							logger.error(F'Vocabulary path ({save_directory}) should be a directory.'	)
							return
						lowerCAmelCase__			:		Optional[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"""





class        SCREAMING_SNAKE_CASE      :






					"""simple docstring"""



					def __init__( self    :       List[Any]	):
						lowerCAmelCase__			:		List[str]						       =			[0, 1]







					def  __lowerCAmelCase				( self    :       str     ,lowercase_    :       int	):
						if (difference := index - (len(self.sequence	) - 2)) >= 1:
							for _ in range(lowercase_	):
								self.sequence.append(self.sequence[-1] + self.sequence[-2]	)
						return self.sequence[:index]

def 						__SCREAMING_SNAKE_CASE						(   ):
	print(
	    '''Fibonacci Series Using Dynamic Programming\n'''		,  '''Enter the index of the Fibonacci number you want to calculate '''		,  '''in the prompt below. (To exit enter exit or Ctrl-C)\n'''		,  sep=''''''		,  )
	lowerCAmelCase__			:		Optional[int]						       =			Fibonacci()

	while True:
		lowerCAmelCase__			:		str						       =			input('''>> '''				)
		if prompt in {"exit", "quit"}:
			break

		try:
			lowerCAmelCase__			:		int						       =			int(A_				)
		except ValueError:
			print('''Enter a number or \'exit\''''				)
			continue

		print(fibonacci.get(A_				)				)


if __name__ == "__main__":
							main()




