



from dataclasses import dataclass

snake_case     :    List[str]						=    '''0.1'''
snake_case     :    Any						=    '''Lucia Harcekova'''




@dataclass
class 				lowerCAmelCase__	:
					__A  :     int
					__A  :     int
					__A  :     str







					def __repr__(							self   :  Tuple):
											return F'({self.offset}, {self.length}, {self.indicator})'




class 				lowerCAmelCase__	:







					def __init__(							self   :  Optional[int]      ,		_A   :  Optional[Any] = 13      ,		_A   :  List[str] = 6):
											A__						:				List[str]         =			window_size
											A__						:				Dict         =			lookahead_buffer_size
											A__						:				str         =			self.window_size - self.lookahead_buffer_size







					def 			_lowercase      (							self   :  Any      ,		_A   :  Optional[Any]):
											A__						:				str         =			[]
											A__						:				Any         =			""

											# while there are still characters in text to compress
											while text:
																	# find the next encoding phrase
																	# - triplet with offset, length, indicator (the next encoding character)
																	A__						:				List[str]         =			self._find_encoding_token(lowercase__      ,		lowercase__)

																	# update the search buffer:
																	# - add new characters from text into it
																	# - check if size exceed the max search buffer size, if so, drop the
																	#   oldest elements
																	search_buffer += text[: token.length + 1]
																	if len(lowercase__) > self.search_buffer_size:
																							A__						:				Union[str, Any]         =			search_buffer[-self.search_buffer_size :]

																	# update the text
																	A__						:				List[str]         =			text[token.length + 1 :]

																	# append the token to output
																	output.append(lowercase__)

											return output







					def 			_lowercase      (							self   :  Dict      ,		_A   :  Union[str, Any]):
											A__						:				Optional[int]         =			""

											for token in tokens:
																	for _ in range(token.length):
																							output += output[-token.offset]
																	output += token.indicator

											return output







					def 			_lowercase      (							self   :  Optional[int]      ,		_A   :  Tuple      ,		_A   :  Any):

											if not text:
																	raise ValueError("We need some text to work with.")

											# Initialise result parameters to default values
											A__     ,							A__						:				Union[str, Any]         =			0, 0

											if not search_buffer:
																	return Token(lowercase__      ,		lowercase__      ,		text[length])

											for i, character in enumerate(lowercase__):
																	A__						:				int         =			len(lowercase__) - i
																	if character == text[0]:
																							A__						:				int         =			self._match_length_from_index(lowercase__      ,		lowercase__      ,		0      ,		lowercase__)
																							# if the found length is bigger than the current or if it's equal,
																							# which means it's offset is smaller: update offset and length
																							if found_length >= length:
																													A__     ,							A__						:				Optional[int]         =			found_offset, found_length

											return Token(lowercase__      ,		lowercase__      ,		text[length])







					def 			_lowercase      (							self   :  Optional[int]      ,		_A   :  str      ,		_A   :  Optional[int]      ,		_A   :  List[str]      ,		_A   :  Tuple):
											if not text or text[text_index] != window[window_index]:
																	return 0
											return 1 + self._match_length_from_index(
											    lowercase__      ,		window + text[text_index]      ,		text_index + 1      ,		window_index + 1)


if __name__ == "__main__":
		from doctest import testmod

		testmod()
		# Initialize compressor class
		snake_case     :    Any						=    LZaaCompressor(window_size=1_3, lookahead_buffer_size=6)

		# Example
		snake_case     :    str						=    '''cabracadabrarrarrad'''
		snake_case     :    Optional[int]						=    lzaa_compressor.compress(TEXT)
		print(lzaa_compressor.compress('ababcbababaa'))
		snake_case     :    Dict						=    lzaa_compressor.decompress(compressed_text)
		assert decompressed_text == TEXT, "The LZ77 algorithm returned the invalid result."







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:
					snake_case_   :	Optional[int]							      =None


snake_case_   :	List[str]							      =logging.get_logger(__name__)

snake_case_   :	Optional[int]							      ={'''vocab_file''': '''sentencepiece.bpe.model''', '''tokenizer_file''': '''tokenizer.json'''}

snake_case_   :	Union[str, 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'''
        ),
    },
}

snake_case_   :	int							      ={
    '''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        a__      (	lowerCAmelCase__		):
		UpperCAmelCase_							:       int 					= VOCAB_FILES_NAMES
		UpperCAmelCase_							:       str 					= PRETRAINED_VOCAB_FILES_MAP
		UpperCAmelCase_							:       Union[str, Any] 					= PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
		UpperCAmelCase_							:       int 					= ['input_ids', 'attention_mask']
		UpperCAmelCase_							:       Optional[int] 					= XLMRobertaTokenizer






		def __init__(      self							, lowercase__=None							, lowercase__=None							, lowercase__="<s>"							, lowercase__="</s>"							, lowercase__="</s>"							, lowercase__="<s>"							, lowercase__="<unk>"							, lowercase__="<pad>"							, lowercase__="<mask>"							, **lowercase__							, )				->				List[str]:
				# Mask token behave like a normal word, i.e. include the space before it
				__A    =							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__							, )

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






		def 					_lowerCamelCase					(      self							, lowercase__							, lowercase__ = None						)				->				List[int]:

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






		def 					_lowerCamelCase					(      self							, lowercase__							, lowercase__ = None						)				->				List[int]:
				__A    =							[self.sep_token_id]
				__A    =							[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							, lowercase__							, lowercase__ = None						)				->				Tuple[str]:
				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
				__A    =							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,)

