
from __future__ import annotations

from typing import Any




def 						A_			(				*snake_case				: list[list[int]]			)   ->     list[list[int]]:



						'''simple docstring'''

						if all(_check_not_integer(snake_case			) for m in matrix_s			):
												for i in matrix_s[1:]:
																		_verify_matrix_sizes(matrix_s[0]			,   snake_case			)
												return [[sum(snake_case			) for t in zip(*snake_case			)] for m in zip(*snake_case			)]
						raise TypeError('''Expected a matrix, got int/list instead'''			)




def 						A_			(				snake_case				: list[list[int]]			,   snake_case				: list[list[int]]			)   ->     list[list[int]]:



						'''simple docstring'''

						if (
						    _check_not_integer(snake_case			)
						    and _check_not_integer(snake_case			)
						    and _verify_matrix_sizes(snake_case			,   snake_case			)
						):
												return [[i - j for i, j in zip(*snake_case			)] for m in zip(snake_case			,   snake_case			)]
						raise TypeError('''Expected a matrix, got int/list instead'''			)




def 						A_			(				snake_case				: list[list[int]]			,   snake_case				: int | float			)   ->     list[list[float]]:



						'''simple docstring'''

						return [[x * n for x in row] for row in matrix]




def 						A_			(				snake_case				: list[list[int]]			,   snake_case				: list[list[int]]			)   ->     list[list[int]]:



						'''simple docstring'''

						if _check_not_integer(snake_case			) and _check_not_integer(snake_case			):
												__UpperCamelCase	,				__UpperCamelCase  	=      _verify_matrix_sizes(snake_case			,   snake_case			)

						if cols[0] != rows[1]:
												__UpperCamelCase  	=      (
												    '''Cannot multiply matrix of dimensions '''
												    f"({rows[0]},{cols[0]}) and ({rows[1]},{cols[1]})"
												)
												raise ValueError(snake_case			)
						return [
						    [sum(m * n for m, n in zip(snake_case			,   snake_case			)			) for j in zip(*snake_case			)] for i in matrix_a
						]




def 						A_			(				snake_case				: int			)   ->     list[list[int]]:



						'''simple docstring'''

						__UpperCamelCase  	=      int(snake_case			)
						return [[int(row == column			) for column in range(snake_case			)] for row in range(snake_case			)]




def 						A_			(				snake_case				: list[list[int]]			,   snake_case				: bool = True			)   ->     list[list[int]] | map[list[int]]:



						'''simple docstring'''

						if _check_not_integer(snake_case			):
												if return_map:
																		return map(snake_case			,   zip(*snake_case			)			)
												else:
																		return list(map(snake_case			,   zip(*snake_case			)			)			)
						raise TypeError('''Expected a matrix, got int/list instead'''			)




def 						A_			(				snake_case				: list[list[int]]			,   snake_case				: int			,   snake_case				: int			)   ->     list[list[int]]:



						'''simple docstring'''

						__UpperCamelCase  	=      matrix[:row] + matrix[row + 1 :]
						return [row[:column] + row[column + 1 :] for row in minor]




def 						A_			(				snake_case				: list[list[int]]			)   ->     Any:



						'''simple docstring'''

						if len(snake_case			) == 1:
												return matrix[0][0]

						return sum(
						    x * determinant(minor(snake_case			,   0			,   snake_case			)			) * (-1) ** i
						    for i, x in enumerate(matrix[0]			)			)




def 						A_			(				snake_case				: list[list[int]]			)   ->     list[list[float]] | None:



						'''simple docstring'''

						__UpperCamelCase  	=      determinant(snake_case			)
						if det == 0:
												return None

						__UpperCamelCase  	=      [
						    [determinant(minor(snake_case			,   snake_case			,   snake_case			)			) for j in range(len(snake_case			)			)]
						    for i in range(len(snake_case			)			)
						]

						__UpperCamelCase  	=      [
						    [x * (-1) ** (row + col) for col, x in enumerate(matrix_minor[row]			)]
						    for row in range(len(snake_case			)			)
						]
						__UpperCamelCase  	=      list(transpose(snake_case			)			)
						return scalar_multiply(snake_case			,   1 / det			)




def 						A_			(				snake_case				: list[list[int]]			)   ->     bool:



						'''simple docstring'''

						return not isinstance(snake_case			,   snake_case			) and not isinstance(matrix[0]			,   snake_case			)




def 						A_			(				snake_case				: list[list[int]]			)   ->     tuple[int, int]:



						'''simple docstring'''

						return len(snake_case			), len(matrix[0]			)




def 						A_			(				snake_case				: list[list[int]]			,   snake_case				: list[list[int]]			)   ->     tuple[tuple[int, int], tuple[int, int]]:



						'''simple docstring'''

						__UpperCamelCase  	=      _shape(snake_case			) + _shape(snake_case			)
						if shape[0] != shape[3] or shape[1] != shape[2]:
												__UpperCamelCase  	=      (
												    '''operands could not be broadcast together with shape '''
												    f"({shape[0], shape[1]}), ({shape[2], shape[3]})"
												)
												raise ValueError(snake_case			)
						return (shape[0], shape[2]), (shape[1], shape[3])




def 						A_			(				)   ->     None:



						'''simple docstring'''

						__UpperCamelCase  	=      [[12, 10], [3, 9]]
						__UpperCamelCase  	=      [[3, 4], [7, 4]]
						__UpperCamelCase  	=      [[11, 12, 13, 14], [21, 22, 23, 24], [31, 32, 33, 34], [41, 42, 43, 44]]
						__UpperCamelCase  	=      [[3, 0, 2], [2, 0, -2], [0, 1, 1]]
						print(f"Add Operation, {add(snake_case			,   snake_case			) = } \n"			)
						print(
						    f"Multiply Operation, {multiply(snake_case			,   snake_case			) = } \n"			,   )
						print(f"Identity: {identity(5			)}\n"			)
						print(f"Minor of {matrix_c} = {minor(snake_case			,   1			,   2			)} \n"			)
						print(f"Determinant of {matrix_b} = {determinant(snake_case			)} \n"			)
						print(f"Inverse of {matrix_d} = {inverse(snake_case			)}\n"			)


if __name__ == "__main__":
				import doctest

				doctest.testmod()
				main()










"""simple docstring"""





import copy

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


_lowercase						   =     logging.get_logger(__name__)

_lowercase						   =     {
    """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    __lowercase							(      snake_case_						):


				'''simple docstring'''


				_lowerCAmelCase						      ="musicgen_decoder"
				_lowerCAmelCase						      =["past_key_values"]

				def __init__( self :  List[str]   ,SCREAMING_SNAKE_CASE_ :  Dict=2_0_4_8   ,SCREAMING_SNAKE_CASE_ :  str=2_0_4_8   ,SCREAMING_SNAKE_CASE_ :  List[str]=2_4   ,SCREAMING_SNAKE_CASE_ :  int=4_0_9_6   ,SCREAMING_SNAKE_CASE_ :  List[Any]=1_6   ,SCREAMING_SNAKE_CASE_ :  Dict=0.0   ,SCREAMING_SNAKE_CASE_ :  Any=True   ,SCREAMING_SNAKE_CASE_ :  Any="gelu"   ,SCREAMING_SNAKE_CASE_ :  Tuple=1_0_2_4   ,SCREAMING_SNAKE_CASE_ :  Any=0.1   ,SCREAMING_SNAKE_CASE_ :  List[str]=0.0   ,SCREAMING_SNAKE_CASE_ :  Optional[Any]=0.0   ,SCREAMING_SNAKE_CASE_ :  Tuple=0.02   ,SCREAMING_SNAKE_CASE_ :  Optional[Any]=False   ,SCREAMING_SNAKE_CASE_ :  List[str]=4   ,SCREAMING_SNAKE_CASE_ :  str=2_0_4_8   ,SCREAMING_SNAKE_CASE_ :  str=2_0_4_8   ,SCREAMING_SNAKE_CASE_ :  Optional[int]=None   ,SCREAMING_SNAKE_CASE_ :  Tuple=False   ,**SCREAMING_SNAKE_CASE_ :  Union[str, Any]   ,):
										snake_case__							:       List[str]				      =       vocab_size
										snake_case__							:       List[str]				      =       max_position_embeddings
										snake_case__							:       List[Any]				      =       hidden_size
										snake_case__							:       Dict				      =       ffn_dim
										snake_case__							:       Union[str, Any]				      =       num_hidden_layers
										snake_case__							:       List[str]				      =       num_attention_heads
										snake_case__							:       Optional[Any]				      =       dropout
										snake_case__							:       Dict				      =       attention_dropout
										snake_case__							:       Union[str, Any]				      =       activation_dropout
										snake_case__							:       Dict				      =       activation_function
										snake_case__							:       Union[str, Any]				      =       initializer_factor
										snake_case__							:       List[str]				      =       layerdrop
										snake_case__							:       Any				      =       use_cache
										snake_case__							:       Tuple				      =       scale_embedding  # scale factor will be sqrt(d_model) if True
										snake_case__							:       Any				      =       num_codebooks
										super().__init__(
										    pad_token_id=SCREAMING_SNAKE_CASE_   ,bos_token_id=SCREAMING_SNAKE_CASE_   ,eos_token_id=SCREAMING_SNAKE_CASE_   ,tie_word_embeddings=SCREAMING_SNAKE_CASE_   ,**SCREAMING_SNAKE_CASE_   ,)







class    __lowercase							(      snake_case_						):


				'''simple docstring'''


				_lowerCAmelCase						      ="musicgen"
				_lowerCAmelCase						      =True

				def __init__( self :  Optional[Any]   ,**SCREAMING_SNAKE_CASE_ :  Dict   ):
										super().__init__(**SCREAMING_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'''   )

										snake_case__							:       Optional[int]				      =       kwargs.pop('''text_encoder'''   )
										snake_case__							:       Optional[Any]				      =       text_encoder_config.pop('''model_type'''   )

										snake_case__							:       Union[str, Any]				      =       kwargs.pop('''audio_encoder'''   )
										snake_case__							:       Dict				      =       audio_encoder_config.pop('''model_type'''   )

										snake_case__							:       Optional[Any]				      =       kwargs.pop('''decoder'''   )

										snake_case__							:       Union[str, Any]				      =       AutoConfig.for_model(SCREAMING_SNAKE_CASE_   ,**SCREAMING_SNAKE_CASE_   )
										snake_case__							:       List[Any]				      =       AutoConfig.for_model(SCREAMING_SNAKE_CASE_   ,**SCREAMING_SNAKE_CASE_   )
										snake_case__							:       List[str]				      =       MusicgenDecoderConfig(**SCREAMING_SNAKE_CASE_   )
										snake_case__							:       Union[str, Any]				      =       True

				@classmethod
				def    _lowerCamelCase       ( cls :  Dict   ,SCREAMING_SNAKE_CASE_ :  PretrainedConfig   ,SCREAMING_SNAKE_CASE_ :  PretrainedConfig   ,SCREAMING_SNAKE_CASE_ :  MusicgenDecoderConfig   ,**SCREAMING_SNAKE_CASE_ :  str   ,):
										return cls(
										    text_encoder=text_encoder_config.to_dict()   ,audio_encoder=audio_encoder_config.to_dict()   ,decoder=decoder_config.to_dict()   ,**SCREAMING_SNAKE_CASE_   ,)





				def    _lowerCamelCase       ( self :  Optional[Any]   ):
										snake_case__							:       Optional[Any]				      =       copy.deepcopy(self.__dict__   )
										snake_case__							:       Any				      =       self.text_encoder.to_dict()
										snake_case__							:       Dict				      =       self.audio_encoder.to_dict()
										snake_case__							:       Dict				      =       self.decoder.to_dict()
										snake_case__							:       Optional[int]				      =       self.__class__.model_type
										return output


