
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:
							lowercase__						:List[str]					    =       None


lowercase__						:Tuple					    =       logging.get_logger(__name__)

lowercase__						:int					    =       {"vocab_file": "sentencepiece.bpe.model", "tokenizer_file": "tokenizer.json"}

lowercase__						:List[Any]					    =       {
    "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"
        ),
    },
}

lowercase__						:Any					    =       {
    "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 							lowercase						(   SCREAMING_SNAKE_CASE__						):
							lowercase_			:			Any			   =VOCAB_FILES_NAMES
							lowercase_			:			Union[str, Any]			   =PRETRAINED_VOCAB_FILES_MAP
							lowercase_			:			List[Any]			   =PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							lowercase_			:			int			   =['''input_ids''', '''attention_mask''']
							lowercase_			:			Tuple			   =XLMRobertaTokenizer




							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
												lowercase		      =		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__  ,sep_token=A__  ,cls_token=A__  ,unk_token=A__  ,pad_token=A__  ,mask_token=A__  ,**A__  ,)

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




							def 					A__ (							self  ,A__  ,A__ = None):

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




							def 					A__ (							self  ,A__  ,A__ = None):
												lowercase		      =		[self.sep_token_id]
												lowercase		      =		[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  ,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
												lowercase		      =		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,)






def 			UpperCamelCase       (				lowerCAmelCase__ = 30						):
					'''simple docstring'''
					lowercase		      =		exponent + 2
					lowercase		      =		(1 + 5**0.5) / 2
					lowercase		      =		(phi**fibonacci_index - (phi - 1) ** fibonacci_index) / 5**0.5

					return int(lowerCAmelCase__						)


if __name__ == "__main__":
							print(F'{solution() = }')




