






import copy

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import AutoConfig


UpperCamelCase											=      logging.get_logger(__name__)

UpperCamelCase											=      {
    '''facebook/musicgen-small''': '''https://huggingface.co/facebook/musicgen-small/resolve/main/config.json''',
    # See all Musicgen models at https://huggingface.co/models?filter=musicgen
}




class 	lowerCamelCase__				(							UpperCAmelCase ):
      lowerCamelCase_							:   Optional[Any]											=	'musicgen_decoder'
      lowerCamelCase_							:   List[Any]											=	['past_key_values']






      def __init__(self					:    str		,		_snake_case					:    Optional[int]=2048		,		_snake_case					:    Dict=2048		,		_snake_case					:    Optional[Any]=24		,		_snake_case					:    Union[str, Any]=4096		,		_snake_case					:    Dict=16		,		_snake_case					:    str=0.0		,		_snake_case					:    Union[str, Any]=True		,		_snake_case					:    List[Any]="gelu"		,		_snake_case					:    List[str]=1024		,		_snake_case					:    Any=0.1		,		_snake_case					:    str=0.0		,		_snake_case					:    Any=0.0		,		_snake_case					:    Optional[int]=0.02		,		_snake_case					:    Union[str, Any]=False		,		_snake_case					:    Dict=4		,		_snake_case					:    str=2048		,		_snake_case					:    List[Any]=2048		,		_snake_case					:    Any=None		,		_snake_case					:    int=False		,		**_snake_case					:    List[Any]		,		)       ->   Optional[Any]:


       """simple docstring"""






       lowerCamelCase_							:    Optional[int]							=     vocab_size
       lowerCamelCase_							:    int							=     max_position_embeddings
       lowerCamelCase_							:    str							=     hidden_size
       lowerCamelCase_							:    Union[str, Any]							=     ffn_dim
       lowerCamelCase_							:    Dict							=     num_hidden_layers
       lowerCamelCase_							:    str							=     num_attention_heads
       lowerCamelCase_							:    List[Any]							=     dropout
       lowerCamelCase_							:    Optional[Any]							=     attention_dropout
       lowerCamelCase_							:    List[str]							=     activation_dropout
       lowerCamelCase_							:    int							=     activation_function
       lowerCamelCase_							:    int							=     initializer_factor
       lowerCamelCase_							:    Union[str, Any]							=     layerdrop
       lowerCamelCase_							:    Optional[int]							=     use_cache
       lowerCamelCase_							:    Dict							=     scale_embedding  # scale factor will be sqrt(d_model) if True
       lowerCamelCase_							:    Tuple							=     num_codebooks
       super().__init__(
           pad_token_id=_snake_case		,		bos_token_id=_snake_case		,		eos_token_id=_snake_case		,		tie_word_embeddings=_snake_case		,		**_snake_case		,		)




class 	lowerCamelCase__				(							UpperCAmelCase ):
      lowerCamelCase_							:   Tuple											=	'musicgen'
      lowerCamelCase_							:   Optional[int]											=	True






      def __init__(self					:    Optional[Any]		,		**_snake_case					:    List[Any]		)       ->   Dict:


       """simple docstring"""






       super().__init__(**_snake_case		)
       if "text_encoder" not in kwargs or "audio_encoder" not in kwargs or "decoder" not in kwargs:
        raise ValueError('Config has to be initialized with text_encoder, audio_encoder and decoder config'		)

       lowerCamelCase_							:    Dict							=     kwargs.pop('text_encoder'		)
       lowerCamelCase_							:    Union[str, Any]							=     text_encoder_config.pop('model_type'		)

       lowerCamelCase_							:    str							=     kwargs.pop('audio_encoder'		)
       lowerCamelCase_							:    Tuple							=     audio_encoder_config.pop('model_type'		)

       lowerCamelCase_							:    str							=     kwargs.pop('decoder'		)

       lowerCamelCase_							:    Optional[int]							=     AutoConfig.for_model(_snake_case		,		**_snake_case		)
       lowerCamelCase_							:    str							=     AutoConfig.for_model(_snake_case		,		**_snake_case		)
       lowerCamelCase_							:    Optional[Any]							=     MusicgenDecoderConfig(**_snake_case		)
       lowerCamelCase_							:    Any							=     True






      @classmethod
      def      UpperCAmelCase_     (cls					:    Any		,		_snake_case					:    PretrainedConfig		,		_snake_case					:    PretrainedConfig		,		_snake_case					:    MusicgenDecoderConfig		,		**_snake_case					:    Dict		,		)       ->   Union[str, Any]:


       """simple docstring"""






       return cls(
           text_encoder=text_encoder_config.to_dict()		,		audio_encoder=audio_encoder_config.to_dict()		,		decoder=decoder_config.to_dict()		,		**_snake_case		,		)






      def      UpperCAmelCase_     (self					:    Dict		)       ->   Optional[Any]:


       """simple docstring"""






       lowerCamelCase_							:    Union[str, Any]							=     copy.deepcopy(self.__dict__		)
       lowerCamelCase_							:    Optional[int]							=     self.text_encoder.to_dict()
       lowerCamelCase_							:    Optional[int]							=     self.audio_encoder.to_dict()
       lowerCamelCase_							:    int							=     self.decoder.to_dict()
       lowerCamelCase_							:    Union[str, Any]							=     self.__class__.model_type
       return output








from dataclasses import dataclass

UpperCamelCase											=      '''0.1'''
UpperCamelCase											=      '''Lucia Harcekova'''




@dataclass
class 	lowerCamelCase__				:
      lowerCamelCase_							:   int
      lowerCamelCase_							:   int
      lowerCamelCase_							:   str






      def __repr__(self					:    Tuple		)       ->   str:


       """simple docstring"""






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




class 	lowerCamelCase__				:






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


       """simple docstring"""






       lowerCamelCase_							:    Any							=     window_size
       lowerCamelCase_							:    List[str]							=     lookahead_buffer_size
       lowerCamelCase_							:    Optional[int]							=     self.window_size - self.lookahead_buffer_size






      def      UpperCAmelCase_     (self					:    Tuple		,		_snake_case					:    str		)       ->   list[Token]:


       """simple docstring"""






       lowerCamelCase_							:    Optional[Any]							=     []
       lowerCamelCase_							:    List[str]							=     ''

       # 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(_snake_case		,		_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(_snake_case		) > self.search_buffer_size:
         lowerCamelCase_							:    int							=     search_buffer[-self.search_buffer_size :]

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

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

       return output






      def      UpperCAmelCase_     (self					:    Tuple		,		_snake_case					:    list[Token]		)       ->   str:


       """simple docstring"""






       lowerCamelCase_							:    Optional[Any]							=     ''

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

       return output






      def      UpperCAmelCase_     (self					:    Dict		,		_snake_case					:    str		,		_snake_case					:    str		)       ->   Token:


       """simple docstring"""






       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(_snake_case		,		_snake_case		,		text[length]		)

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

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






      def      UpperCAmelCase_     (self					:    Any		,		_snake_case					:    str		,		_snake_case					:    str		,		_snake_case					:    int		,		_snake_case					:    int		)       ->   int:


       """simple docstring"""






       if not text or text[text_index] != window[window_index]:
        return 0
       return 1 + self._match_length_from_index(
           _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=1_3, 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."
