



from dataclasses import dataclass

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




@dataclass
class  snake_case__						:






     """simple docstring"""


     _SCREAMING_SNAKE_CASE            =     42
     _SCREAMING_SNAKE_CASE            =     42
     _SCREAMING_SNAKE_CASE            =     42






     def __repr__(	self  :  Any )       ->str:
            return F'''({self.offset}, {self.length}, {self.indicator})'''




class  snake_case__						:






     """simple docstring"""


     def __init__(	self  :  str,			_snake_case  :  int = 1_3,			_snake_case  :  int = 6 )       ->None:
            snake_case__							:     Tuple            =     window_size
            snake_case__							:     List[Any]            =     lookahead_buffer_size
            snake_case__							:     Optional[int]            =     self.window_size - self.lookahead_buffer_size






     def        lowercase_       (	self  :  int,			_snake_case  :  str )       ->list[Token]:
            snake_case__							:     List[Any]            =     []
            snake_case__							:     Tuple            =     ''

            # 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)
                   snake_case__							:     Dict            =     self._find_encoding_token(_snake_case,			_snake_case )

                   # 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(_snake_case ) > self.search_buffer_size:
                          snake_case__							:     int            =     search_buffer[-self.search_buffer_size :]

                   # update the text
                   snake_case__							:     Union[str, Any]            =     text[token.length + 1 :]

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

            return output






     def        lowercase_       (	self  :  Any,			_snake_case  :  list[Token] )       ->str:
            snake_case__							:     Union[str, Any]            =     ''

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

            return output






     def        lowercase_       (	self  :  int,			_snake_case  :  str,			_snake_case  :  str )       ->Token:

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

            # Initialise result parameters to default values
            snake_case__     ,    snake_case__							:     Any            =     0, 0

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

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

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






     def        lowercase_       (	self  :  List[Any],			_snake_case  :  str,			_snake_case  :  str,			_snake_case  :  int,			_snake_case  :  int )       ->int:
            if not text or text[text_index] != window[window_index]:
                   return 0
            return 1 + self._match_length_from_index(
                _snake_case,			window + text[text_index],			text_index + 1,			window_index + 1 )


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

 testmod()
 # Initialize compressor class
 a_       :Union[str, Any]				  =				LZaaCompressor(window_size=13, lookahead_buffer_size=6)

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











import os
import unittest

from transformers.models.bertweet.tokenization_bertweet import VOCAB_FILES_NAMES, BertweetTokenizer

from ...test_tokenization_common import TokenizerTesterMixin




class  snake_case__						(	lowerCAmelCase_    ,					unittest.TestCase					):






     """simple docstring"""


     _SCREAMING_SNAKE_CASE            =     BertweetTokenizer
     _SCREAMING_SNAKE_CASE            =     False






     def        lowercase_       (	self  :  List[str] )       ->Union[str, Any]:
            super().setUp()

            # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
            snake_case__							:     List[Any]            =     ['I', 'm', 'V@@', 'R@@', 'r', 'e@@']
            snake_case__							:     Tuple            =     dict(zip(_snake_case,			range(len(_snake_case ) ) ) )
            snake_case__							:     int            =     ['#version: 0.2', 'a m</w>']
            snake_case__							:     Dict            =     {'unk_token': '<unk>'}

            snake_case__							:     Tuple            =     os.path.join(self.tmpdirname,			VOCAB_FILES_NAMES['vocab_file'] )
            snake_case__							:     Tuple            =     os.path.join(self.tmpdirname,			VOCAB_FILES_NAMES['merges_file'] )
            with open(self.vocab_file,			'w',			encoding='utf-8' ) as fp:
                   for token in vocab_tokens:
                          fp.write(F'''{token} {vocab_tokens[token]}\n''' )
            with open(self.merges_file,			'w',			encoding='utf-8' ) as fp:
                   fp.write('\n'.join(_snake_case ) )






     def        lowercase_       (	self  :  List[Any],			**_snake_case  :  List[Any] )       ->Optional[Any]:
            kwargs.update(self.special_tokens_map )
            return BertweetTokenizer.from_pretrained(self.tmpdirname,			**_snake_case )






     def        lowercase_       (	self  :  Optional[Any],			_snake_case  :  Tuple )       ->Union[str, Any]:
            snake_case__							:     List[str]            =     'I am VinAI Research'
            snake_case__							:     str            =     'I <unk> m V<unk> <unk> <unk> I Re<unk> e<unk> <unk> <unk> <unk>'
            return input_text, output_text






     def        lowercase_       (	self  :  str )       ->int:
            snake_case__							:     Dict            =     BertweetTokenizer(self.vocab_file,			self.merges_file,			**self.special_tokens_map )
            snake_case__							:     List[str]            =     'I am VinAI Research'
            snake_case__							:     str            =     'I a@@ m V@@ i@@ n@@ A@@ I R@@ e@@ s@@ e@@ a@@ r@@ c@@ h'.split()
            snake_case__							:     Optional[int]            =     tokenizer.tokenize(_snake_case )
            self.assertListEqual(_snake_case,			_snake_case )

            snake_case__							:     Tuple            =     tokens + [tokenizer.unk_token]

            snake_case__							:     Dict            =     [4, 3, 5, 6, 3, 3, 3, 4, 7, 9, 3, 9, 3, 3, 3, 3, 3]
            self.assertListEqual(tokenizer.convert_tokens_to_ids(_snake_case ),			_snake_case )






