


'''simple docstring'''

from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


__lowercase:		Any							=     {
    "configuration_videomae": ["VIDEOMAE_PRETRAINED_CONFIG_ARCHIVE_MAP", "VideoMAEConfig"],
}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__lowercase:		Any							=     [
							    "VIDEOMAE_PRETRAINED_MODEL_ARCHIVE_LIST",
							    "VideoMAEForPreTraining",
							    "VideoMAEModel",
							    "VideoMAEPreTrainedModel",
							    "VideoMAEForVideoClassification",
							]

try:
							if not is_vision_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__lowercase:		List[str]							=     ["VideoMAEFeatureExtractor"]
							__lowercase:		List[str]							=     ["VideoMAEImageProcessor"]

if TYPE_CHECKING:
							from .configuration_videomae import VIDEOMAE_PRETRAINED_CONFIG_ARCHIVE_MAP, VideoMAEConfig

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_videomae import (
														    VIDEOMAE_PRETRAINED_MODEL_ARCHIVE_LIST,
														    VideoMAEForPreTraining,
														    VideoMAEForVideoClassification,
														    VideoMAEModel,
														    VideoMAEPreTrainedModel,
														)

							try:
														if not is_vision_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .feature_extraction_videomae import VideoMAEFeatureExtractor
														from .image_processing_videomae import VideoMAEImageProcessor

else:
							import sys

							__lowercase:		List[str]							=     _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)



'''simple docstring'''

from dataclasses import dataclass

__lowercase:		List[str]							=     "0.1"
__lowercase:		Union[str, Any]							=     "Lucia Harcekova"







@dataclass
class  UpperCAmelCase :
 _lowerCamelCase :					int
 _lowerCamelCase :					int
 _lowerCamelCase :					str

 def __repr__( self :	List[str]					):





    """simple docstring"""



    return f'({self.offset}, {self.length}, {self.indicator})'







class  UpperCAmelCase :

 def __init__( self :	Optional[int],					a_ :	int = 13,					a_ :	int = 6					):





    """simple docstring"""



    UpperCamelCase__ 						=						window_size
    UpperCamelCase__ 						=						lookahead_buffer_size
    UpperCamelCase__ 						=						self.window_size - self.lookahead_buffer_size

 def 		lowercase_						( self :	Optional[int],					a_ :	str					):





    """simple docstring"""



    UpperCamelCase__ 						=						[]
    UpperCamelCase__ 						=						""

    # 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__ 						=						self._find_encoding_token(a_,					a_					)

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

       # update the text
       UpperCamelCase__ 						=						text[token.length + 1 :]

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

    return output

 def 		lowercase_						( self :	List[Any],					a_ :	list[Token]					):





    """simple docstring"""



    UpperCamelCase__ 						=						""

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

    return output

 def 		lowercase_						( self :	Any,					a_ :	str,					a_ :	str					):





    """simple docstring"""



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

    # Initialise result parameters to default values
    UpperCamelCase__						,		UpperCamelCase__ 						=						0, 0

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

    for i, character in enumerate(a_					):
       UpperCamelCase__ 						=						len(a_					) - i
       if character == text[0]:
          UpperCamelCase__ 						=						self._match_length_from_index(a_,					a_,					0,					a_					)
          # 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__ 						=						found_offset, found_length

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

 def 		lowercase_						( self :	Optional[int],					a_ :	str,					a_ :	str,					a_ :	int,					a_ :	int					):





    """simple docstring"""



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


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

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

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