






'''simple docstring'''







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 					__UpperCAmelCase (		UpperCamelCase__	):

      '''simple docstring'''





      SCREAMING_SNAKE_CASE				:    Optional[Any]				       =					"musicgen_decoder"
      SCREAMING_SNAKE_CASE				:    str				       =					["past_key_values"]




      def __init__(					self  ,		_UpperCAmelCase=2048  ,		_UpperCAmelCase=2048  ,		_UpperCAmelCase=24  ,		_UpperCAmelCase=4096  ,		_UpperCAmelCase=16  ,		_UpperCAmelCase=0.0  ,		_UpperCAmelCase=True  ,		_UpperCAmelCase="gelu"  ,		_UpperCAmelCase=1024  ,		_UpperCAmelCase=0.1  ,		_UpperCAmelCase=0.0  ,		_UpperCAmelCase=0.0  ,		_UpperCAmelCase=0.02  ,		_UpperCAmelCase=False  ,		_UpperCAmelCase=4  ,		_UpperCAmelCase=2048  ,		_UpperCAmelCase=2048  ,		_UpperCAmelCase=None  ,		_UpperCAmelCase=False  ,		**_UpperCAmelCase  ,		):
             UpperCAmelCase__	:   Union[str, Any]												=	vocab_size
             UpperCAmelCase__	:   str												=	max_position_embeddings
             UpperCAmelCase__	:   List[Any]												=	hidden_size
             UpperCAmelCase__	:   Tuple												=	ffn_dim
             UpperCAmelCase__	:   Optional[Any]												=	num_hidden_layers
             UpperCAmelCase__	:   List[Any]												=	num_attention_heads
             UpperCAmelCase__	:   Optional[Any]												=	dropout
             UpperCAmelCase__	:   Union[str, Any]												=	attention_dropout
             UpperCAmelCase__	:   Any												=	activation_dropout
             UpperCAmelCase__	:   Optional[int]												=	activation_function
             UpperCAmelCase__	:   Dict												=	initializer_factor
             UpperCAmelCase__	:   List[str]												=	layerdrop
             UpperCAmelCase__	:   Union[str, Any]												=	use_cache
             UpperCAmelCase__	:   List[str]												=	scale_embedding  # scale factor will be sqrt(d_model) if True
             UpperCAmelCase__	:   Optional[int]												=	num_codebooks
             super().__init__(
                 pad_token_id=_UpperCAmelCase  ,		bos_token_id=_UpperCAmelCase  ,		eos_token_id=_UpperCAmelCase  ,		tie_word_embeddings=_UpperCAmelCase  ,		**_UpperCAmelCase  ,		)




class 					__UpperCAmelCase (		UpperCamelCase__	):

      '''simple docstring'''





      SCREAMING_SNAKE_CASE				:    Optional[Any]				       =					"musicgen"
      SCREAMING_SNAKE_CASE				:    Dict				       =					True




      def __init__(					self  ,		**_UpperCAmelCase						):
             super().__init__(**_UpperCAmelCase						)
             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'''						)

             UpperCAmelCase__	:   str												=	kwargs.pop('''text_encoder'''						)
             UpperCAmelCase__	:   str												=	text_encoder_config.pop('''model_type'''						)

             UpperCAmelCase__	:   int												=	kwargs.pop('''audio_encoder'''						)
             UpperCAmelCase__	:   Any												=	audio_encoder_config.pop('''model_type'''						)

             UpperCAmelCase__	:   Union[str, Any]												=	kwargs.pop('''decoder'''						)

             UpperCAmelCase__	:   int												=	AutoConfig.for_model(_UpperCAmelCase  ,		**_UpperCAmelCase						)
             UpperCAmelCase__	:   List[Any]												=	AutoConfig.for_model(_UpperCAmelCase  ,		**_UpperCAmelCase						)
             UpperCAmelCase__	:   Union[str, Any]												=	MusicgenDecoderConfig(**_UpperCAmelCase						)
             UpperCAmelCase__	:   str												=	True




      @classmethod
      def 							lowerCamelCase     (					cls  ,		_UpperCAmelCase  ,		_UpperCAmelCase  ,		_UpperCAmelCase  ,		**_UpperCAmelCase  ,		):
             return cls(
                 text_encoder=text_encoder_config.to_dict()  ,		audio_encoder=audio_encoder_config.to_dict()  ,		decoder=decoder_config.to_dict()  ,		**_UpperCAmelCase  ,		)




      def 							lowerCamelCase     (					self						):
             UpperCAmelCase__	:   List[Any]												=	copy.deepcopy(self.__dict__						)
             UpperCAmelCase__	:   Dict												=	self.text_encoder.to_dict()
             UpperCAmelCase__	:   Tuple												=	self.audio_encoder.to_dict()
             UpperCAmelCase__	:   Tuple												=	self.decoder.to_dict()
             UpperCAmelCase__	:   Union[str, Any]												=	self.__class__.model_type
             return output





def        lowerCamelCase_     (     SCREAMING_SNAKE_CASE ):
			'''simple docstring'''
			SCREAMING_SNAKE_CASE     =       len(SCREAMING_SNAKE_CASE )
			SCREAMING_SNAKE_CASE     =       [0] * length
			SCREAMING_SNAKE_CASE     =       [[False for i in range(SCREAMING_SNAKE_CASE )] for j in range(SCREAMING_SNAKE_CASE )]
			for i, c in enumerate(SCREAMING_SNAKE_CASE ):
						SCREAMING_SNAKE_CASE     =       i
						for j in range(i + 1 ):
									if c == string[j] and (i - j < 2 or is_palindromic[j + 1][i - 1]):
												SCREAMING_SNAKE_CASE     =       True
												SCREAMING_SNAKE_CASE     =       min(SCREAMING_SNAKE_CASE       ,						0 if j == 0 else (cut[j - 1] + 1) )
						SCREAMING_SNAKE_CASE     =       mincut
			return cut[length - 1]


if __name__ == "__main__":
		__A    :				Optional[int]    						=	input("""Enter the string: """).strip()
		__A    :				List[Any]    						=	find_minimum_partitions(s)
		print(f'''Minimum number of partitions required for the \'{s}\' is {ans}''')






