





'''simple docstring'''







from dataclasses import dataclass

snake_case_       :    List[str]          =					"0.1"
snake_case_       :    List[Any]          =					"Lucia Harcekova"


@dataclass
class    __a :
							__a   :				int
							__a   :				int
							__a   :				str

							def __repr__(							self							:       List[Any]				)   ->    str:







													"""simple docstring"""
													return F"""({self.offset}, {self.length}, {self.indicator})"""





class    __a :

							def __init__(							self							:       str    ,       __magic_name__							:       int = 13    ,       __magic_name__							:       int = 6				)   ->    None:







													"""simple docstring"""
													UpperCAmelCase_     : int         =					window_size
													UpperCAmelCase_     : str         =					lookahead_buffer_size
													UpperCAmelCase_     : Optional[Any]         =					self.window_size - self.lookahead_buffer_size

							def       UpperCAmelCase__		(							self							:       Any    ,       __magic_name__							:       str				)   ->    list[Token]:







													"""simple docstring"""
													UpperCAmelCase_     : Any         =					[]
													UpperCAmelCase_     : List[str]         =					''''''

													# 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)
																			UpperCAmelCase_     : str         =					self._find_encoding_token(__magic_name__    ,       __magic_name__				)

																			# 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(__magic_name__				) > self.search_buffer_size:
																									UpperCAmelCase_     : Tuple         =					search_buffer[-self.search_buffer_size :]

																			# update the text
																			UpperCAmelCase_     : Optional[Any]         =					text[token.length + 1 :]

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

													return output

							def       UpperCAmelCase__		(							self							:       Optional[int]    ,       __magic_name__							:       list[Token]				)   ->    str:







													"""simple docstring"""
													UpperCAmelCase_     : Union[str, Any]         =					''''''

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

													return output

							def       UpperCAmelCase__		(							self							:       Any    ,       __magic_name__							:       str    ,       __magic_name__							:       str				)   ->    Token:







													"""simple docstring"""

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

													# Initialise result parameters to default values
													UpperCAmelCase_  ,    UpperCAmelCase_     : Dict         =					0, 0

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

													for i, character in enumerate(__magic_name__				):
																			UpperCAmelCase_     : List[str]         =					len(__magic_name__				) - i
																			if character == text[0]:
																									UpperCAmelCase_     : Optional[int]         =					self._match_length_from_index(__magic_name__    ,       __magic_name__    ,       0    ,       __magic_name__				)
																									# 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:
																															UpperCAmelCase_  ,    UpperCAmelCase_     : Optional[int]         =					found_offset, found_length

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



							def       UpperCAmelCase__		(							self							:       str    ,       __magic_name__							:       str    ,       __magic_name__							:       str    ,       __magic_name__							:       int    ,       __magic_name__							:       int				)   ->    int:







													"""simple docstring"""
													if not text or text[text_index] != window[window_index]:
																			return 0
													return 1 + self._match_length_from_index(
													    __magic_name__    ,       window + text[text_index]    ,       text_index + 1    ,       window_index + 1				)


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

					testmod()
					# Initialize compressor class
					snake_case_       :    List[Any]          =					LZaaCompressor(window_size=13, lookahead_buffer_size=6)

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












'''simple docstring'''







from transformers import SqueezeBertTokenizer, SqueezeBertTokenizerFast
from transformers.testing_utils import require_tokenizers, slow

from ..bert.test_tokenization_bert import BertTokenizationTest


@require_tokenizers
class    __a (lowerCamelCase       ):
							__a   :				Any       =    SqueezeBertTokenizer
							__a   :				Dict       =    SqueezeBertTokenizerFast
							__a   :				Any       =    True

							def       UpperCAmelCase__		(							self							:       Union[str, Any]    ,       **__magic_name__							:       Dict				)   ->    int:







													"""simple docstring"""
													return SqueezeBertTokenizerFast.from_pretrained(self.tmpdirname    ,       **__magic_name__				)



							@slow
							def       UpperCAmelCase__		(							self							:       Union[str, Any]				)   ->    int:







													"""simple docstring"""
													UpperCAmelCase_     : List[str]         =					SqueezeBertTokenizer.from_pretrained('''squeezebert/squeezebert-mnli-headless'''				)

													UpperCAmelCase_     : Any         =					tokenizer.encode('''sequence builders'''    ,       add_special_tokens=__magic_name__				)
													UpperCAmelCase_     : Optional[Any]         =					tokenizer.encode('''multi-sequence build'''    ,       add_special_tokens=__magic_name__				)

													UpperCAmelCase_     : List[Any]         =					tokenizer.build_inputs_with_special_tokens(__magic_name__				)
													UpperCAmelCase_     : Any         =					tokenizer.build_inputs_with_special_tokens(__magic_name__    ,       __magic_name__				)

													assert encoded_sentence == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id]
													assert encoded_pair == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id] + text_a + [
													    tokenizer.sep_token_id
													]





