


from dataclasses import dataclass

__lowerCamelCase   	=  '''0.1'''
__lowerCamelCase   	=  '''Lucia Harcekova'''


@dataclass
class 	a__						:
       lowerCamelCase__:  int
       lowerCamelCase__:  int
       lowerCamelCase__:  str

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


class 	a__						:

       def __init__( self   :  List[Any]   ,				lowerCamelCase_   :  int = 1_3   ,				lowerCamelCase_   :  int = 6     ):
            a_     :  List[Any]				      =     window_size
            a_     :  Optional[Any]				      =     lookahead_buffer_size
            a_     :  Union[str, Any]				      =     self.window_size - self.lookahead_buffer_size

       def     UpperCAmelCase( self   :  str   ,				lowerCamelCase_   :  str     ):
            a_     :  Tuple				      =     []
            a_     :  Dict				      =     """"""

            # 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_     :  Optional[Any]				      =     self._find_encoding_token(lowerCamelCase_   ,				lowerCamelCase_     )

                 # 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(lowerCamelCase_     ) > self.search_buffer_size:
                      a_     :  Dict				      =     search_buffer[-self.search_buffer_size :]

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

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

            return output

       def     UpperCAmelCase( self   :  List[str]   ,				lowerCamelCase_   :  list[Token]     ):
            a_     :  str				      =     """"""

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

            return output

       def     UpperCAmelCase( self   :  Any   ,				lowerCamelCase_   :  str   ,				lowerCamelCase_   :  str     ):

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

            # Initialise result parameters to default values
            a_      ,      a_     :  Optional[Any]				      =     0, 0

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

            for i, character in enumerate(lowerCamelCase_     ):
                 a_     :  Dict				      =     len(lowerCamelCase_     ) - i
                 if character == text[0]:
                      a_     :  Union[str, Any]				      =     self._match_length_from_index(lowerCamelCase_   ,				lowerCamelCase_   ,				0   ,				lowerCamelCase_     )
                      # 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[Any]				      =     found_offset, found_length

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

       def     UpperCAmelCase( self   :  List[str]   ,				lowerCamelCase_   :  str   ,				lowerCamelCase_   :  str   ,				lowerCamelCase_   :  int   ,				lowerCamelCase_   :  int     ):
            if not text or text[text_index] != window[window_index]:
                 return 0
            return 1 + self._match_length_from_index(
                lowerCamelCase_   ,				window + text[text_index]   ,				text_index + 1   ,				window_index + 1     )


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

       testmod()
       # Initialize compressor class
       __lowerCamelCase   	=  LZaaCompressor(window_size=13, lookahead_buffer_size=6)

       # Example
       __lowerCamelCase   	=  '''cabracadabrarrarrad'''
       __lowerCamelCase   	=  lzaa_compressor.compress(TEXT)
       print(lzaa_compressor.compress('''ababcbababaa'''))
       __lowerCamelCase   	=  lzaa_compressor.decompress(compressed_text)
       assert decompressed_text == TEXT, "The LZ77 algorithm returned the invalid result."







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__lowerCamelCase   	=  {'''configuration_visual_bert''': ['''VISUAL_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''VisualBertConfig''']}

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       __lowerCamelCase   	=  [
           '''VISUAL_BERT_PRETRAINED_MODEL_ARCHIVE_LIST''',
           '''VisualBertForMultipleChoice''',
           '''VisualBertForPreTraining''',
           '''VisualBertForQuestionAnswering''',
           '''VisualBertForRegionToPhraseAlignment''',
           '''VisualBertForVisualReasoning''',
           '''VisualBertLayer''',
           '''VisualBertModel''',
           '''VisualBertPreTrainedModel''',
       ]


if TYPE_CHECKING:
       from .configuration_visual_bert import VISUAL_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP, VisualBertConfig

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_visual_bert import (
                  VISUAL_BERT_PRETRAINED_MODEL_ARCHIVE_LIST,
                  VisualBertForMultipleChoice,
                  VisualBertForPreTraining,
                  VisualBertForQuestionAnswering,
                  VisualBertForRegionToPhraseAlignment,
                  VisualBertForVisualReasoning,
                  VisualBertLayer,
                  VisualBertModel,
                  VisualBertPreTrainedModel,
              )


else:
       import sys

       __lowerCamelCase   	=  _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)



