




'''simple docstring'''







from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCAmelCase_    	=							logging.get_logger(__name__)

lowerCAmelCase_    	=							{
    'MCG-NJU/videomae-base': 'https://huggingface.co/MCG-NJU/videomae-base/resolve/main/config.json',
}

class   _snake_case( UpperCAmelCase			):
 __snake_case:       int									=				'''videomae'''






 def __init__(self					:     Any						,		a					:     Any=2_24						,		a					:     Union[str, Any]=16						,		a					:     Any=3						,		a					:     Dict=16						,		a					:     List[str]=2						,		a					:     Union[str, Any]=7_68						,		a					:     Dict=12						,		a					:     Tuple=12						,		a					:     Optional[Any]=30_72						,		a					:     List[Any]="gelu"						,		a					:     Dict=0.0						,		a					:     Any=0.0						,		a					:     Optional[int]=0.02						,		a					:     List[str]=1e-12						,		a					:     Tuple=True						,		a					:     List[Any]=True						,		a					:     Tuple=6						,		a					:     Dict=3_84						,		a					:     int=4						,		a					:     str=15_36						,		a					:     Optional[int]=True						,		**a					:     Any						,		)					->      Any:






    """simple docstring"""


    super().__init__(**A_						)

    A__         =    image_size
    A__         =    patch_size
    A__         =    num_channels
    A__         =    num_frames
    A__         =    tubelet_size

    A__         =    hidden_size
    A__         =    num_hidden_layers
    A__         =    num_attention_heads
    A__         =    intermediate_size
    A__         =    hidden_act
    A__         =    hidden_dropout_prob
    A__         =    attention_probs_dropout_prob
    A__         =    initializer_range
    A__         =    layer_norm_eps
    A__         =    qkv_bias
    A__         =    use_mean_pooling

    A__         =    decoder_num_attention_heads
    A__         =    decoder_hidden_size
    A__         =    decoder_num_hidden_layers
    A__         =    decoder_intermediate_size
    A__         =    norm_pix_loss






'''simple docstring'''







from dataclasses import dataclass

lowerCAmelCase_    	=							'''0.1'''
lowerCAmelCase_    	=							'''Lucia Harcekova'''

@dataclass
class   _snake_case:
 __snake_case:       int
 __snake_case:       int
 __snake_case:       str






 def __repr__(self					:     Optional[int]						)					->      str:






    """simple docstring"""


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




class   _snake_case:






 def __init__(self					:     Optional[Any]						,		a					:     int = 13						,		a					:     int = 6						)					->      None:






    """simple docstring"""


    A__         =    window_size
    A__         =    lookahead_buffer_size
    A__         =    self.window_size - self.lookahead_buffer_size






 def 	_UpperCamelCase   (self					:     Optional[Any]						,		a					:     str						)					->      list[Token]:






    """simple docstring"""


    A__         =    []
    A__         =    ''

    # 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__         =    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:
          A__         =    search_buffer[-self.search_buffer_size :]

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

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

    return output






 def 	_UpperCamelCase   (self					:     Optional[int]						,		a					:     list[Token]						)					->      str:






    """simple docstring"""


    A__         =    ''

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

    return output






 def 	_UpperCamelCase   (self					:     Any						,		a					:     str						,		a					:     str						)					->      Token:






    """simple docstring"""


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

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

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

    for i, character in enumerate(a						):
       A__         =    len(a						) - i
       if character == text[0]:
          A__         =    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:
             A__     , A__         =    found_offset, found_length

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






 def 	_UpperCamelCase   (self					:     int						,		a					:     str						,		a					:     str						,		a					:     int						,		a					:     int						)					->      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
    lowerCAmelCase_    	=							LZaaCompressor(window_size=1_3, 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."


