"""simple docstring"""







from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


lowerCamelCase      : Dict       =logging.get_logger(__name__)

lowerCamelCase      : int       ={
    '''nghuyong/ernie-1.0-base-zh''': '''https://huggingface.co/nghuyong/ernie-1.0-base-zh/resolve/main/config.json''',
    '''nghuyong/ernie-2.0-base-en''': '''https://huggingface.co/nghuyong/ernie-2.0-base-en/resolve/main/config.json''',
    '''nghuyong/ernie-2.0-large-en''': '''https://huggingface.co/nghuyong/ernie-2.0-large-en/resolve/main/config.json''',
    '''nghuyong/ernie-3.0-base-zh''': '''https://huggingface.co/nghuyong/ernie-3.0-base-zh/resolve/main/config.json''',
    '''nghuyong/ernie-3.0-medium-zh''': '''https://huggingface.co/nghuyong/ernie-3.0-medium-zh/resolve/main/config.json''',
    '''nghuyong/ernie-3.0-mini-zh''': '''https://huggingface.co/nghuyong/ernie-3.0-mini-zh/resolve/main/config.json''',
    '''nghuyong/ernie-3.0-micro-zh''': '''https://huggingface.co/nghuyong/ernie-3.0-micro-zh/resolve/main/config.json''',
    '''nghuyong/ernie-3.0-nano-zh''': '''https://huggingface.co/nghuyong/ernie-3.0-nano-zh/resolve/main/config.json''',
    '''nghuyong/ernie-gram-zh''': '''https://huggingface.co/nghuyong/ernie-gram-zh/resolve/main/config.json''',
    '''nghuyong/ernie-health-zh''': '''https://huggingface.co/nghuyong/ernie-health-zh/resolve/main/config.json''',
}






class 							__snake_case(					snake_case_	):


    '''simple docstring'''





    _UpperCAmelCase       =			"ernie"
    def __init__(  self					,       __lowerCamelCase=30522					,       __lowerCamelCase=768					,       __lowerCamelCase=12					,       __lowerCamelCase=12					,       __lowerCamelCase=3072					,       __lowerCamelCase="gelu"					,       __lowerCamelCase=0.1					,       __lowerCamelCase=0.1					,       __lowerCamelCase=512					,       __lowerCamelCase=2					,       __lowerCamelCase=3					,       __lowerCamelCase=False					,       __lowerCamelCase=0.02					,       __lowerCamelCase=1e-12					,       __lowerCamelCase=0					,       __lowerCamelCase="absolute"					,       __lowerCamelCase=True					,       __lowerCamelCase=None					,       **__lowerCamelCase					,       ):




         '''simple docstring'''



         super().__init__(pad_token_id=SCREAMING_SNAKE_CASE_					,       **SCREAMING_SNAKE_CASE_	)

         __A					:					int								=		vocab_size
         __A					:					Optional[int]								=		hidden_size
         __A					:					Optional[int]								=		num_hidden_layers
         __A					:					List[str]								=		num_attention_heads
         __A					:					Optional[Any]								=		hidden_act
         __A					:					Dict								=		intermediate_size
         __A					:					Any								=		hidden_dropout_prob
         __A					:					int								=		attention_probs_dropout_prob
         __A					:					Optional[Any]								=		max_position_embeddings
         __A					:					Any								=		type_vocab_size
         __A					:					Optional[int]								=		task_type_vocab_size
         __A					:					List[str]								=		use_task_id
         __A					:					str								=		initializer_range
         __A					:					List[str]								=		layer_norm_eps
         __A					:					int								=		position_embedding_type
         __A					:					List[Any]								=		use_cache
         __A					:					Union[str, Any]								=		classifier_dropout







class 							__snake_case(					snake_case_	):


    '''simple docstring'''





    @property
    def 						_a							(  self	):




         '''simple docstring'''



         if self.task == "multiple-choice":
              __A					:					Any								=		{0: '''batch''', 1: '''choice''', 2: '''sequence'''}
         else:
              __A					:					Optional[int]								=		{0: '''batch''', 1: '''sequence'''}
         return OrderedDict(
             [
                 ('input_ids', dynamic_axis),
                 ('attention_mask', dynamic_axis),
                 ('token_type_ids', dynamic_axis),
                 ('task_type_ids', dynamic_axis),
             ]	)









"""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


