code: 
  
  
  """simple docstring"""
  from typing import TYPE_CHECKING
  
  from ...utils import (
      OptionalDependencyNotAvailable,
      _LazyModule,
      is_flax_available,
      is_sentencepiece_available,
      is_tf_available,
      is_tokenizers_available,
      is_torch_available,
  )
  
  
  UpperCAmelCase   =	{
      """configuration_big_bird""": ["""BIG_BIRD_PRETRAINED_CONFIG_ARCHIVE_MAP""", """BigBirdConfig""", """BigBirdOnnxConfig"""],
  }
  
  try:
   if not is_sentencepiece_available():
    raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
   pass
  else:
   UpperCAmelCase   =	["""BigBirdTokenizer"""]
  
  try:
   if not is_tokenizers_available():
    raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
   pass
  else:
   UpperCAmelCase   =	["""BigBirdTokenizerFast"""]
  
  try:
   if not is_torch_available():
    raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
   pass
  else:
   UpperCAmelCase   =	[
       """BIG_BIRD_PRETRAINED_MODEL_ARCHIVE_LIST""",
       """BigBirdForCausalLM""",
       """BigBirdForMaskedLM""",
       """BigBirdForMultipleChoice""",
       """BigBirdForPreTraining""",
       """BigBirdForQuestionAnswering""",
       """BigBirdForSequenceClassification""",
       """BigBirdForTokenClassification""",
       """BigBirdLayer""",
       """BigBirdModel""",
       """BigBirdPreTrainedModel""",
       """load_tf_weights_in_big_bird""",
   ]
  
  try:
   if not is_flax_available():
    raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
   pass
  else:
   UpperCAmelCase   =	[
       """FlaxBigBirdForCausalLM""",
       """FlaxBigBirdForMaskedLM""",
       """FlaxBigBirdForMultipleChoice""",
       """FlaxBigBirdForPreTraining""",
       """FlaxBigBirdForQuestionAnswering""",
       """FlaxBigBirdForSequenceClassification""",
       """FlaxBigBirdForTokenClassification""",
       """FlaxBigBirdModel""",
       """FlaxBigBirdPreTrainedModel""",
   ]
  
  if TYPE_CHECKING:
   from .configuration_big_bird import BIG_BIRD_PRETRAINED_CONFIG_ARCHIVE_MAP, BigBirdConfig, BigBirdOnnxConfig
  
   try:
    if not is_sentencepiece_available():
     raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
    pass
   else:
    from .tokenization_big_bird import BigBirdTokenizer
  
   try:
    if not is_tokenizers_available():
     raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
    pass
   else:
    from .tokenization_big_bird_fast import BigBirdTokenizerFast
  
   try:
    if not is_torch_available():
     raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
    pass
   else:
    from .modeling_big_bird import (
        BIG_BIRD_PRETRAINED_MODEL_ARCHIVE_LIST,
        BigBirdForCausalLM,
        BigBirdForMaskedLM,
        BigBirdForMultipleChoice,
        BigBirdForPreTraining,
        BigBirdForQuestionAnswering,
        BigBirdForSequenceClassification,
        BigBirdForTokenClassification,
        BigBirdLayer,
        BigBirdModel,
        BigBirdPreTrainedModel,
        load_tf_weights_in_big_bird,
    )
  
   try:
    if not is_flax_available():
     raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
    pass
   else:
    from .modeling_flax_big_bird import (
        FlaxBigBirdForCausalLM,
        FlaxBigBirdForMaskedLM,
        FlaxBigBirdForMultipleChoice,
        FlaxBigBirdForPreTraining,
        FlaxBigBirdForQuestionAnswering,
        FlaxBigBirdForSequenceClassification,
        FlaxBigBirdForTokenClassification,
        FlaxBigBirdModel,
        FlaxBigBirdPreTrainedModel,
    )
  
  else:
   import sys
  
   UpperCAmelCase   =	_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)
  
  
style_context: 
  
  
  """simple docstring"""
  from dataclasses import dataclass
  
  UpperCAmelCase   =	"""0.1"""
  UpperCAmelCase   =	"""Lucia Harcekova"""
  
  
  
  
  @dataclass
  class   lowercase__							:
     __UpperCAmelCase       					=				42
     __UpperCAmelCase       					=				42
     __UpperCAmelCase       					=				42
  
  
  
  
  
     def __repr__(       self)     ->     str:
        return F'({self.offset}, {self.length}, {self.indicator})'
  
  
  
  
  
  
  
  class   lowercase__							:
  
  
  
  
  
     def __init__(       self			,      SCREAMING_SNAKE_CASE = 13			,      SCREAMING_SNAKE_CASE = 6)     ->     None:
        _lowerCamelCase  :				Optional[Any]      =		window_size
        _lowerCamelCase  :				List[str]      =		lookahead_buffer_size
        _lowerCamelCase  :				List[Any]      =		self.window_size - self.lookahead_buffer_size
  
  
  
  
  
     def 		UpperCamelCase_     (       self			,      SCREAMING_SNAKE_CASE)     ->     list[Token]:
        _lowerCamelCase  :				Union[str, Any]      =		[]
        _lowerCamelCase  :				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)
           _lowerCamelCase  :				List[Any]      =		self._find_encoding_token(SCREAMING_SNAKE_CASE			,      SCREAMING_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(SCREAMING_SNAKE_CASE) > self.search_buffer_size:
              _lowerCamelCase  :				int      =		search_buffer[-self.search_buffer_size :]
  
           # update the text
           _lowerCamelCase  :				Tuple      =		text[token.length + 1 :]
  
           # append the token to output
           output.append(SCREAMING_SNAKE_CASE)
  
        return output
  
  
  
  
  
     def 		UpperCamelCase_     (       self			,      SCREAMING_SNAKE_CASE)     ->     str:
        _lowerCamelCase  :				str      =		""""""
  
        for token in tokens:
           for _ in range(token.length):
              output += output[-token.offset]
           output += token.indicator
  
        return output
  
  
  
  
  
     def 		UpperCamelCase_     (       self			,      SCREAMING_SNAKE_CASE			,      SCREAMING_SNAKE_CASE)     ->     Token:
  
        if not text:
           raise ValueError("""We need some text to work with.""")
  
        # Initialise result parameters to default values
        _lowerCamelCase      ,						_lowerCamelCase  :				List[str]      =		0, 0
  
        if not search_buffer:
           return Token(SCREAMING_SNAKE_CASE			,      SCREAMING_SNAKE_CASE			,      text[length])
  
        for i, character in enumerate(SCREAMING_SNAKE_CASE):
           _lowerCamelCase  :				Tuple      =		len(SCREAMING_SNAKE_CASE) - i
           if character == text[0]:
              _lowerCamelCase  :				Any      =		self._match_length_from_index(SCREAMING_SNAKE_CASE			,      SCREAMING_SNAKE_CASE			,      0			,      SCREAMING_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:
                 _lowerCamelCase      ,						_lowerCamelCase  :				Optional[int]      =		found_offset, found_length
  
        return Token(SCREAMING_SNAKE_CASE			,      SCREAMING_SNAKE_CASE			,      text[length])
  
  
  
  
  
     def 		UpperCamelCase_     (       self			,      SCREAMING_SNAKE_CASE			,      SCREAMING_SNAKE_CASE			,      SCREAMING_SNAKE_CASE			,      SCREAMING_SNAKE_CASE)     ->     int:
        if not text or text[text_index] != window[window_index]:
           return 0
        return 1 + self._match_length_from_index(
            SCREAMING_SNAKE_CASE			,      window + text[text_index]			,      text_index + 1			,      window_index + 1)
  
  
  if __name__ == "__main__":
   from doctest import testmod
  
   testmod()
   # Initialize compressor class
   UpperCAmelCase   =	LZaaCompressor(window_size=13, lookahead_buffer_size=6)
  
   # Example
   UpperCAmelCase   =	"""cabracadabrarrarrad"""
   UpperCAmelCase   =	lzaa_compressor.compress(TEXT)
   print(lzaa_compressor.compress("""ababcbababaa"""))
   UpperCAmelCase   =	lzaa_compressor.decompress(compressed_text)
   assert decompressed_text == TEXT, "The LZ77 algorithm returned the invalid result."
  
  