


import copy

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


__lowerCAmelCase     :			Union[str, Any]      =logging.get_logger(__name__)

__lowerCAmelCase     :			str      ={
    '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				(      A__	):






				'''simple docstring'''



				SCREAMING_SNAKE_CASE__    :      Dict      =		'''musicgen_decoder'''
				SCREAMING_SNAKE_CASE__    :      List[Any]      =		['''past_key_values''']


				def __init__(	self      :Union[str, Any]      ,      lowerCAmelCase__      :Dict=2_048      ,      lowerCAmelCase__      :Tuple=2_048      ,      lowerCAmelCase__      :Union[str, Any]=24      ,      lowerCAmelCase__      :Optional[Any]=4_096      ,      lowerCAmelCase__      :Any=16      ,      lowerCAmelCase__      :Tuple=0.0      ,      lowerCAmelCase__      :List[Any]=True      ,      lowerCAmelCase__      :Dict="gelu"      ,      lowerCAmelCase__      :Union[str, Any]=1_024      ,      lowerCAmelCase__      :Tuple=0.1      ,      lowerCAmelCase__      :List[Any]=0.0      ,      lowerCAmelCase__      :Tuple=0.0      ,      lowerCAmelCase__      :Any=0.02      ,      lowerCAmelCase__      :List[Any]=False      ,      lowerCAmelCase__      :Tuple=4      ,      lowerCAmelCase__      :int=2_048      ,      lowerCAmelCase__      :Dict=2_048      ,      lowerCAmelCase__      :Tuple=None      ,      lowerCAmelCase__      :Optional[Any]=False      ,      **lowerCAmelCase__      :Optional[Any]      ,      )		->      Optional[Any]:
										__SCREAMING_SNAKE_CASE						:					List[str]		      =		vocab_size
										__SCREAMING_SNAKE_CASE						:					int		      =		max_position_embeddings
										__SCREAMING_SNAKE_CASE						:					List[Any]		      =		hidden_size
										__SCREAMING_SNAKE_CASE						:					Any		      =		ffn_dim
										__SCREAMING_SNAKE_CASE						:					str		      =		num_hidden_layers
										__SCREAMING_SNAKE_CASE						:					Optional[Any]		      =		num_attention_heads
										__SCREAMING_SNAKE_CASE						:					Optional[int]		      =		dropout
										__SCREAMING_SNAKE_CASE						:					Any		      =		attention_dropout
										__SCREAMING_SNAKE_CASE						:					Union[str, Any]		      =		activation_dropout
										__SCREAMING_SNAKE_CASE						:					Tuple		      =		activation_function
										__SCREAMING_SNAKE_CASE						:					Dict		      =		initializer_factor
										__SCREAMING_SNAKE_CASE						:					Tuple		      =		layerdrop
										__SCREAMING_SNAKE_CASE						:					str		      =		use_cache
										__SCREAMING_SNAKE_CASE						:					Union[str, Any]		      =		scale_embedding  # scale factor will be sqrt(d_model) if True
										__SCREAMING_SNAKE_CASE						:					int		      =		num_codebooks
										super().__init__(
										    pad_token_id=lowerCAmelCase__      ,      bos_token_id=lowerCAmelCase__      ,      eos_token_id=lowerCAmelCase__      ,      tie_word_embeddings=lowerCAmelCase__      ,      **lowerCAmelCase__      ,      )




class 	_lowercase				(      A__	):






				'''simple docstring'''



				SCREAMING_SNAKE_CASE__    :      str      =		'''musicgen'''
				SCREAMING_SNAKE_CASE__    :      Optional[int]      =		True


				def __init__(	self      :int      ,      **lowerCAmelCase__      :Any     )		->      Union[str, Any]:
										super().__init__(**lowerCAmelCase__     )
										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						:					str		      =		kwargs.pop('''text_encoder'''     )
										__SCREAMING_SNAKE_CASE						:					List[Any]		      =		text_encoder_config.pop('''model_type'''     )

										__SCREAMING_SNAKE_CASE						:					str		      =		kwargs.pop('''audio_encoder'''     )
										__SCREAMING_SNAKE_CASE						:					Dict		      =		audio_encoder_config.pop('''model_type'''     )

										__SCREAMING_SNAKE_CASE						:					Dict		      =		kwargs.pop('''decoder'''     )

										__SCREAMING_SNAKE_CASE						:					str		      =		AutoConfig.for_model(lowerCAmelCase__      ,      **lowerCAmelCase__     )
										__SCREAMING_SNAKE_CASE						:					List[str]		      =		AutoConfig.for_model(lowerCAmelCase__      ,      **lowerCAmelCase__     )
										__SCREAMING_SNAKE_CASE						:					Tuple		      =		MusicgenDecoderConfig(**lowerCAmelCase__     )
										__SCREAMING_SNAKE_CASE						:					int		      =		True


				@classmethod
				def 		__magic_name__(	cls      :Tuple      ,      lowerCAmelCase__      :PretrainedConfig      ,      lowerCAmelCase__      :PretrainedConfig      ,      lowerCAmelCase__      :MusicgenDecoderConfig      ,      **lowerCAmelCase__      :int      ,      )		->      Any:
										return cls(
										    text_encoder=text_encoder_config.to_dict()      ,      audio_encoder=audio_encoder_config.to_dict()      ,      decoder=decoder_config.to_dict()      ,      **lowerCAmelCase__      ,      )



				def 		__magic_name__(	self      :Any     )		->      int:
										__SCREAMING_SNAKE_CASE						:					Dict		      =		copy.deepcopy(self.__dict__     )
										__SCREAMING_SNAKE_CASE						:					Optional[int]		      =		self.text_encoder.to_dict()
										__SCREAMING_SNAKE_CASE						:					List[str]		      =		self.audio_encoder.to_dict()
										__SCREAMING_SNAKE_CASE						:					List[str]		      =		self.decoder.to_dict()
										__SCREAMING_SNAKE_CASE						:					List[str]		      =		self.__class__.model_type
										return output




from .number_theory.prime_numbers import next_prime
class 	_lowercase				:






				'''simple docstring'''



				def __init__(	self      :Tuple      ,      lowerCAmelCase__      :int      ,      lowerCAmelCase__      :int | None = None      ,      lowerCAmelCase__      :float | None = None      ,      )		->      None:
										__SCREAMING_SNAKE_CASE						:					Tuple		      =		size_table
										__SCREAMING_SNAKE_CASE						:					Dict		      =		[None] * self.size_table
										__SCREAMING_SNAKE_CASE						:					List[Any]		      =		0.75 if lim_charge is None else lim_charge
										__SCREAMING_SNAKE_CASE						:					Tuple		      =		1 if charge_factor is None else charge_factor
										__SCREAMING_SNAKE_CASE						:					list		      =		[]
										__SCREAMING_SNAKE_CASE						:					dict		      =		{}


				def 		__magic_name__(	self      :List[Any]     )		->      Tuple:
										return self._keys


				def 		__magic_name__(	self      :Any     )		->      Dict:
										return sum(1 for slot in self.values if slot is not None     ) / (
										    self.size_table * self.charge_factor
										)


				def 		__magic_name__(	self      :Optional[Any]      ,      lowerCAmelCase__      :Union[str, Any]     )		->      Optional[Any]:
										return key % self.size_table


				def 		__magic_name__(	self      :int      ,      lowerCAmelCase__      :Union[str, Any]     )		->      List[Any]:
										print(f'''step {step_ord}'''     )
										print(list(range(len(self.values     )     )     )     )
										print(self.values     )


				def 		__magic_name__(	self      :List[str]      ,      lowerCAmelCase__      :Optional[Any]     )		->      Dict:
										__SCREAMING_SNAKE_CASE						:					List[Any]		      =		1
										__SCREAMING_SNAKE_CASE						:					Optional[Any]		      =		values
										for value in values:
																self.insert_data(lowerCAmelCase__     )
																self._step_by_step(lowerCAmelCase__     )
																i += 1


				def 		__magic_name__(	self      :Tuple      ,      lowerCAmelCase__      :List[Any]      ,      lowerCAmelCase__      :Union[str, Any]     )		->      str:
										__SCREAMING_SNAKE_CASE						:					Tuple		      =		data
										__SCREAMING_SNAKE_CASE						:					Any		      =		data


				def 		__magic_name__(	self      :Optional[int]      ,      lowerCAmelCase__      :Any      ,      lowerCAmelCase__      :List[str]=None     )		->      int:
										__SCREAMING_SNAKE_CASE						:					Tuple		      =		self.hash_function(key + 1     )

										while self.values[new_key] is not None and self.values[new_key] != key:
																if self.values.count(lowerCAmelCase__     ) > 0:
																						__SCREAMING_SNAKE_CASE						:					Optional[Any]		      =		self.hash_function(new_key + 1     )
																else:
																						__SCREAMING_SNAKE_CASE						:					int		      =		None
																						break

										return new_key


				def 		__magic_name__(	self      :Optional[int]     )		->      Union[str, Any]:
										__SCREAMING_SNAKE_CASE						:					str		      =		[value for value in self.values if value is not None]
										__SCREAMING_SNAKE_CASE						:					Optional[int]		      =		next_prime(self.size_table      ,      factor=2     )
										self._keys.clear()
										__SCREAMING_SNAKE_CASE						:					Optional[Any]		      =		[None] * self.size_table  # hell's pointers D: don't DRY ;/
										for value in survivor_values:
																self.insert_data(lowerCAmelCase__     )



				def 		__magic_name__(	self      :Tuple      ,      lowerCAmelCase__      :str     )		->      Dict:
										__SCREAMING_SNAKE_CASE						:					Union[str, Any]		      =		self.hash_function(lowerCAmelCase__     )

										if self.values[key] is None:
																self._set_value(lowerCAmelCase__      ,      lowerCAmelCase__     )

										elif self.values[key] == data:
																pass

										else:
																__SCREAMING_SNAKE_CASE						:					Tuple		      =		self._collision_resolution(lowerCAmelCase__      ,      lowerCAmelCase__     )
																if collision_resolution is not None:
																						self._set_value(lowerCAmelCase__      ,      lowerCAmelCase__     )
																else:
																						self.rehashing()
																						self.insert_data(lowerCAmelCase__     )
