code: 
  
  
  
  
  
  from typing import Callable, Optional, Union
  
  from ...configuration_utils import PretrainedConfig
  from ...utils import logging
  
  
  __lowerCAmelCase     =			logging.get_logger(__name__)
  
  __lowerCAmelCase     =			{
      "microsoft/prophetnet-large-uncased": (
          "https://huggingface.co/microsoft/prophetnet-large-uncased/resolve/main/config.json"
      ),
  }
  
  
  
  
  class   _UpperCAmelCase	(   A_					):
  					__A          =   "prophetnet"
  					__A          =   ["past_key_values"]
  					__A          =   {
  					    "num_attention_heads": "num_encoder_attention_heads",
  					}
  
  
  
  
  					def __init__(						self    ,      __lowerCAmelCase = 0.1    ,      __lowerCAmelCase = "gelu"    ,      __lowerCAmelCase = 30_522    ,      __lowerCAmelCase = 1_024    ,      __lowerCAmelCase = 4_096    ,      __lowerCAmelCase = 12    ,      __lowerCAmelCase = 16    ,      __lowerCAmelCase = 4_096    ,      __lowerCAmelCase = 12    ,      __lowerCAmelCase = 16    ,      __lowerCAmelCase = 0.1    ,      __lowerCAmelCase = 0.1    ,      __lowerCAmelCase = 512    ,      __lowerCAmelCase = 0.0_2    ,      __lowerCAmelCase = True    ,      __lowerCAmelCase = True    ,      __lowerCAmelCase = 0    ,      __lowerCAmelCase = 2    ,      __lowerCAmelCase = 32    ,      __lowerCAmelCase = 128    ,      __lowerCAmelCase = False    ,      __lowerCAmelCase = 0.0    ,      __lowerCAmelCase = True    ,      __lowerCAmelCase = 0    ,      __lowerCAmelCase = 1    ,      __lowerCAmelCase = 2    ,      **__lowerCAmelCase    ,      )						->  Any:
  							UpperCamelCase__         =	vocab_size
  							UpperCamelCase__         =	hidden_size
  							UpperCamelCase__         =	encoder_ffn_dim
  							UpperCamelCase__         =	num_encoder_layers
  							UpperCamelCase__         =	num_encoder_attention_heads
  							UpperCamelCase__         =	decoder_ffn_dim
  							UpperCamelCase__         =	num_decoder_layers
  							UpperCamelCase__         =	num_decoder_attention_heads
  							UpperCamelCase__         =	max_position_embeddings
  							UpperCamelCase__         =	init_std  # Normal(0, this parameter)
  							UpperCamelCase__         =	activation_function
  
  							# parameters for prophetnet
  							UpperCamelCase__         =	ngram
  							UpperCamelCase__         =	num_buckets
  							UpperCamelCase__         =	relative_max_distance
  							UpperCamelCase__         =	disable_ngram_loss
  							UpperCamelCase__         =	eps
  
  							# 3 Types of Dropout
  							UpperCamelCase__         =	attention_dropout
  							UpperCamelCase__         =	activation_dropout
  							UpperCamelCase__         =	dropout
  
  							UpperCamelCase__         =	use_cache
  
  							super().__init__(
  							    pad_token_id=__lowerCAmelCase    ,      bos_token_id=__lowerCAmelCase    ,      eos_token_id=__lowerCAmelCase    ,      is_encoder_decoder=__lowerCAmelCase    ,      add_cross_attention=__lowerCAmelCase    ,      decoder_start_token_id=__lowerCAmelCase    ,      **__lowerCAmelCase    ,      )
  
  
  
  
  					@property
  					def 	snake_case_		(						self       )						->  List[str]:
  							return self.num_encoder_layers + self.num_decoder_layers
  
  
  
  
  					@num_hidden_layers.setter
  					def 	snake_case_		(						self    ,      __lowerCAmelCase       )						->  Optional[Any]:
  							raise NotImplementedError(
  							    """This model does not support the setting of `num_hidden_layers`. Please set `num_encoder_layers` and"""
  							    """ `num_decoder_layers`."""       )
  
  
  
  
style_context: 
  
  
  
  
  
  from dataclasses import dataclass
  
  __lowerCAmelCase     =			"0.1"
  __lowerCAmelCase     =			"Lucia Harcekova"
  
  
  
  
  @dataclass
  class   _UpperCAmelCase	:
  					__A          =   42
  					__A          =   42
  					__A          =   42
  
  
  
  
  					def __repr__(						self       )						->  str:
  							return F"""({self.offset}, {self.length}, {self.indicator})"""
  
  
  
  
  class   _UpperCAmelCase	:
  
  
  
  
  					def __init__(						self    ,      __lowerCAmelCase = 13    ,      __lowerCAmelCase = 6       )						->  None:
  							UpperCamelCase__         =	window_size
  							UpperCamelCase__         =	lookahead_buffer_size
  							UpperCamelCase__         =	self.window_size - self.lookahead_buffer_size
  
  
  
  
  					def 	snake_case_		(						self    ,      __lowerCAmelCase       )						->  list[Token]:
  							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(__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:
  											UpperCamelCase__         =	search_buffer[-self.search_buffer_size :]
  
  									# update the text
  									UpperCamelCase__         =	text[token.length + 1 :]
  
  									# append the token to output
  									output.append(__lowerCAmelCase       )
  
  							return output
  
  
  
  
  					def 	snake_case_		(						self    ,      __lowerCAmelCase       )						->  str:
  							UpperCamelCase__         =	""""""
  
  							for token in tokens:
  									for _ in range(token.length       ):
  											output += output[-token.offset]
  									output += token.indicator
  
  							return output
  
  
  
  
  					def 	snake_case_		(						self    ,      __lowerCAmelCase    ,      __lowerCAmelCase       )						->  Token:
  
  							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(__lowerCAmelCase    ,      __lowerCAmelCase    ,      text[length]       )
  
  							for i, character in enumerate(__lowerCAmelCase       ):
  									UpperCamelCase__         =	len(__lowerCAmelCase       ) - i
  									if character == text[0]:
  											UpperCamelCase__         =	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:
  													UpperCamelCase__  ,			UpperCamelCase__         =	found_offset, found_length
  
  							return Token(__lowerCAmelCase    ,      __lowerCAmelCase    ,      text[length]       )
  
  
  
  
  					def 	snake_case_		(						self    ,      __lowerCAmelCase    ,      __lowerCAmelCase    ,      __lowerCAmelCase    ,      __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."
  
  
  
  
  
  