code: 
  
  
  
  
  import numpy as np
  from numpy import floataa
  from numpy.typing import NDArray
  
  
  def       a			(   a		,	a  )    ->NDArray[floataa]:
  
  
  
  
  			'''simple docstring'''
  
  
  			SCREAMING_SNAKE_CASE	,       SCREAMING_SNAKE_CASE    	=   np.shape(a  )
  
  			SCREAMING_SNAKE_CASE    	=   np.zeros((rows, 1)		,	dtype=a  )
  			for row in reversed(range(a  )  ):
  						SCREAMING_SNAKE_CASE    	=   0
  						for col in range(row + 1		,	a  ):
  									total += coefficients[row, col] * x[col]
  
  						SCREAMING_SNAKE_CASE    	=   (vector[row] - total) / coefficients[row, row]
  
  			return x
  
  
  def       a			(   a		,	a  )    ->NDArray[floataa]:
  
  
  
  
  			'''simple docstring'''
  
  
  			SCREAMING_SNAKE_CASE	,       SCREAMING_SNAKE_CASE    	=   np.shape(a  )
  			if rows != columns:
  						return np.array(()		,	dtype=a  )
  
  			# augmented matrix
  			SCREAMING_SNAKE_CASE    	=   np.concatenate((coefficients, vector)		,	axis=1  )
  			SCREAMING_SNAKE_CASE    	=   augmented_mat.astype('''float64'''  )
  
  			# scale the matrix leaving it triangular
  			for row in range(rows - 1  ):
  						SCREAMING_SNAKE_CASE    	=   augmented_mat[row, row]
  						for col in range(row + 1		,	a  ):
  									SCREAMING_SNAKE_CASE    	=   augmented_mat[col, row] / pivot
  									augmented_mat[col, :] -= factor * augmented_mat[row, :]
  
  			SCREAMING_SNAKE_CASE    	=   retroactive_resolution(
  			    augmented_mat[:, 0:columns]		,	augmented_mat[:, columns : columns + 1]  )
  
  			return x
  
  
  if __name__ == "__main__":
  							import doctest
  
  							doctest.testmod()
style_context: 
  import copy
  
  from ...configuration_utils import PretrainedConfig
  from ...utils import logging
  from ..auto.configuration_auto import AutoConfig
  
  
  __lowerCAmelCase				      =					logging.get_logger(__name__)
  
  __lowerCAmelCase				      =					{
      '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			(					__lowerCamelCase				):
  	UpperCamelCase_     :				int								=  'musicgen_decoder'
  	UpperCamelCase_     :				Optional[int]								=  ['past_key_values']
  
  
  
  
  
  
  
  	def __init__(    self			:List[str]      ,    lowercase			:Tuple=2_0_4_8      ,    lowercase			:Dict=2_0_4_8      ,    lowercase			:Tuple=2_4      ,    lowercase			:Any=4_0_9_6      ,    lowercase			:Optional[Any]=1_6      ,    lowercase			:List[Any]=0.0      ,    lowercase			:Union[str, Any]=True      ,    lowercase			:Optional[Any]="gelu"      ,    lowercase			:Any=1_0_2_4      ,    lowercase			:str=0.1      ,    lowercase			:List[Any]=0.0      ,    lowercase			:List[Any]=0.0      ,    lowercase			:List[Any]=0.02      ,    lowercase			:Optional[int]=False      ,    lowercase			:List[Any]=4      ,    lowercase			:Any=2_0_4_8      ,    lowercase			:Any=2_0_4_8      ,    lowercase			:Optional[int]=None      ,    lowercase			:Tuple=False      ,    **lowercase			:List[Any]      ,    )		->			Tuple:
  
  
  
  
  
  
  
  				"""simple docstring"""
  
  
  
  
  
  
  				SCREAMING_SNAKE_CASE    	=   vocab_size
  				SCREAMING_SNAKE_CASE    	=   max_position_embeddings
  				SCREAMING_SNAKE_CASE    	=   hidden_size
  				SCREAMING_SNAKE_CASE    	=   ffn_dim
  				SCREAMING_SNAKE_CASE    	=   num_hidden_layers
  				SCREAMING_SNAKE_CASE    	=   num_attention_heads
  				SCREAMING_SNAKE_CASE    	=   dropout
  				SCREAMING_SNAKE_CASE    	=   attention_dropout
  				SCREAMING_SNAKE_CASE    	=   activation_dropout
  				SCREAMING_SNAKE_CASE    	=   activation_function
  				SCREAMING_SNAKE_CASE    	=   initializer_factor
  				SCREAMING_SNAKE_CASE    	=   layerdrop
  				SCREAMING_SNAKE_CASE    	=   use_cache
  				SCREAMING_SNAKE_CASE    	=   scale_embedding  # scale factor will be sqrt(d_model) if True
  				SCREAMING_SNAKE_CASE    	=   num_codebooks
  				super().__init__(
  				    pad_token_id=lowercase      ,    bos_token_id=lowercase      ,    eos_token_id=lowercase      ,    tie_word_embeddings=lowercase      ,    **lowercase      ,    )
  
  
  
  
  
  class 						lowerCamelCase			(					__lowerCamelCase				):
  	UpperCamelCase_     :				str								=  'musicgen'
  	UpperCamelCase_     :				Union[str, Any]								=  True
  
  
  
  
  
  
  
  	def __init__(    self			:str      ,    **lowercase			:int )		->			Optional[Any]:
  
  
  
  
  
  
  
  				"""simple docstring"""
  
  
  
  
  
  
  				super().__init__(**lowercase )
  				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''' )
  
  				SCREAMING_SNAKE_CASE    	=   kwargs.pop('''text_encoder''' )
  				SCREAMING_SNAKE_CASE    	=   text_encoder_config.pop('''model_type''' )
  
  				SCREAMING_SNAKE_CASE    	=   kwargs.pop('''audio_encoder''' )
  				SCREAMING_SNAKE_CASE    	=   audio_encoder_config.pop('''model_type''' )
  
  				SCREAMING_SNAKE_CASE    	=   kwargs.pop('''decoder''' )
  
  				SCREAMING_SNAKE_CASE    	=   AutoConfig.for_model(lowercase      ,    **lowercase )
  				SCREAMING_SNAKE_CASE    	=   AutoConfig.for_model(lowercase      ,    **lowercase )
  				SCREAMING_SNAKE_CASE    	=   MusicgenDecoderConfig(**lowercase )
  				SCREAMING_SNAKE_CASE    	=   True
  
  
  
  
  
  
  
  	@classmethod
  	def    snake_case__    (    cls			:Tuple      ,    lowercase			:PretrainedConfig      ,    lowercase			:PretrainedConfig      ,    lowercase			:MusicgenDecoderConfig      ,    **lowercase			:Tuple      ,    )		->			Tuple:
  
  
  
  
  
  
  
  				"""simple docstring"""
  
  
  
  
  
  
  				return cls(
  				    text_encoder=text_encoder_config.to_dict()      ,    audio_encoder=audio_encoder_config.to_dict()      ,    decoder=decoder_config.to_dict()      ,    **lowercase      ,    )
  
  
  
  
  
  
  
  	def    snake_case__    (    self			:Dict )		->			Dict:
  
  
  
  
  
  
  
  				"""simple docstring"""
  
  
  
  
  
  
  				SCREAMING_SNAKE_CASE    	=   copy.deepcopy(self.__dict__ )
  				SCREAMING_SNAKE_CASE    	=   self.text_encoder.to_dict()
  				SCREAMING_SNAKE_CASE    	=   self.audio_encoder.to_dict()
  				SCREAMING_SNAKE_CASE    	=   self.decoder.to_dict()
  				SCREAMING_SNAKE_CASE    	=   self.__class__.model_type
  				return output