
from ..utils import DummyObject, requires_backends





class     __UpperCamelCase (							metaclass=lowerCAmelCase__       ):






     """simple docstring"""







     lowerCAmelCase_							   =			['''torch''', '''transformers''', '''onnx''']



     def __init__(				self							:							Any     ,						*_A							:							List[Any]     ,						**_A							:							Optional[int] ):







       """simple docstring"""




       requires_backends(self     ,						['''torch''', '''transformers''', '''onnx'''] )



     @classmethod
     def  UpperCAmelCase__							(				cls							:							Optional[Any]     ,						*_A							:							List[str]     ,						**_A							:							Union[str, Any] ):







       """simple docstring"""




       requires_backends(cls     ,						['''torch''', '''transformers''', '''onnx'''] )




     @classmethod
     def  UpperCAmelCase__							(				cls							:							List[str]     ,						*_A							:							Any     ,						**_A							:							Optional[int] ):







       """simple docstring"""




       requires_backends(cls     ,						['''torch''', '''transformers''', '''onnx'''] )






class     __UpperCamelCase (							metaclass=lowerCAmelCase__       ):






     """simple docstring"""







     lowerCAmelCase_							   =			['''torch''', '''transformers''', '''onnx''']



     def __init__(				self							:							List[Any]     ,						*_A							:							str     ,						**_A							:							Union[str, Any] ):







       """simple docstring"""




       requires_backends(self     ,						['''torch''', '''transformers''', '''onnx'''] )



     @classmethod
     def  UpperCAmelCase__							(				cls							:							Union[str, Any]     ,						*_A							:							List[Any]     ,						**_A							:							Optional[int] ):







       """simple docstring"""




       requires_backends(cls     ,						['''torch''', '''transformers''', '''onnx'''] )




     @classmethod
     def  UpperCAmelCase__							(				cls							:							Union[str, Any]     ,						*_A							:							Dict     ,						**_A							:							int ):







       """simple docstring"""




       requires_backends(cls     ,						['''torch''', '''transformers''', '''onnx'''] )






class     __UpperCamelCase (							metaclass=lowerCAmelCase__       ):






     """simple docstring"""







     lowerCAmelCase_							   =			['''torch''', '''transformers''', '''onnx''']



     def __init__(				self							:							List[str]     ,						*_A							:							Union[str, Any]     ,						**_A							:							Optional[int] ):







       """simple docstring"""




       requires_backends(self     ,						['''torch''', '''transformers''', '''onnx'''] )



     @classmethod
     def  UpperCAmelCase__							(				cls							:							str     ,						*_A							:							Tuple     ,						**_A							:							Any ):







       """simple docstring"""




       requires_backends(cls     ,						['''torch''', '''transformers''', '''onnx'''] )




     @classmethod
     def  UpperCAmelCase__							(				cls							:							Dict     ,						*_A							:							int     ,						**_A							:							Optional[Any] ):







       """simple docstring"""




       requires_backends(cls     ,						['''torch''', '''transformers''', '''onnx'''] )






class     __UpperCamelCase (							metaclass=lowerCAmelCase__       ):






     """simple docstring"""







     lowerCAmelCase_							   =			['''torch''', '''transformers''', '''onnx''']



     def __init__(				self							:							Optional[Any]     ,						*_A							:							int     ,						**_A							:							List[Any] ):







       """simple docstring"""




       requires_backends(self     ,						['''torch''', '''transformers''', '''onnx'''] )



     @classmethod
     def  UpperCAmelCase__							(				cls							:							List[str]     ,						*_A							:							Union[str, Any]     ,						**_A							:							Optional[int] ):







       """simple docstring"""




       requires_backends(cls     ,						['''torch''', '''transformers''', '''onnx'''] )




     @classmethod
     def  UpperCAmelCase__							(				cls							:							Union[str, Any]     ,						*_A							:							Any     ,						**_A							:							List[Any] ):







       """simple docstring"""




       requires_backends(cls     ,						['''torch''', '''transformers''', '''onnx'''] )






class     __UpperCamelCase (							metaclass=lowerCAmelCase__       ):






     """simple docstring"""







     lowerCAmelCase_							   =			['''torch''', '''transformers''', '''onnx''']



     def __init__(				self							:							Dict     ,						*_A							:							Any     ,						**_A							:							Any ):







       """simple docstring"""




       requires_backends(self     ,						['''torch''', '''transformers''', '''onnx'''] )



     @classmethod
     def  UpperCAmelCase__							(				cls							:							Optional[int]     ,						*_A							:							List[Any]     ,						**_A							:							Any ):







       """simple docstring"""




       requires_backends(cls     ,						['''torch''', '''transformers''', '''onnx'''] )




     @classmethod
     def  UpperCAmelCase__							(				cls							:							Optional[int]     ,						*_A							:							str     ,						**_A							:							str ):







       """simple docstring"""




       requires_backends(cls     ,						['''torch''', '''transformers''', '''onnx'''] )






class     __UpperCamelCase (							metaclass=lowerCAmelCase__       ):






     """simple docstring"""







     lowerCAmelCase_							   =			['''torch''', '''transformers''', '''onnx''']



     def __init__(				self							:							List[str]     ,						*_A							:							Union[str, Any]     ,						**_A							:							int ):







       """simple docstring"""




       requires_backends(self     ,						['''torch''', '''transformers''', '''onnx'''] )



     @classmethod
     def  UpperCAmelCase__							(				cls							:							Tuple     ,						*_A							:							int     ,						**_A							:							Optional[int] ):







       """simple docstring"""




       requires_backends(cls     ,						['''torch''', '''transformers''', '''onnx'''] )




     @classmethod
     def  UpperCAmelCase__							(				cls							:							Any     ,						*_A							:							int     ,						**_A							:							List[Any] ):







       """simple docstring"""




       requires_backends(cls     ,						['''torch''', '''transformers''', '''onnx'''] )





"""simple docstring"""






from ...configuration_utils import PretrainedConfig
from ...utils import logging


__snake_case				:  Tuple =       logging.get_logger(__name__)

__snake_case				:  Any =       {
    'facebook/xglm-564M': 'https://huggingface.co/facebook/xglm-564M/resolve/main/config.json',
    # See all XGLM models at https://huggingface.co/models?filter=xglm
}



class      A__  (    __SCREAMING_SNAKE_CASE				):




	'''simple docstring'''





	SCREAMING_SNAKE_CASE        =      'xglm'
	SCREAMING_SNAKE_CASE        =      ['past_key_values']

	SCREAMING_SNAKE_CASE        =      {
	    'num_attention_heads': 'attention_heads',
	    'hidden_size': 'd_model',
	    'num_hidden_layers': 'num_layers',
	}

	def __init__(	self:						Optional[Any]			,     _SCREAMING_SNAKE_CASE:						List[Any]=25_6008			,     _SCREAMING_SNAKE_CASE:						Dict=2048			,     _SCREAMING_SNAKE_CASE:						int=1024			,     _SCREAMING_SNAKE_CASE:						Dict=4096			,     _SCREAMING_SNAKE_CASE:						Optional[Any]=24			,     _SCREAMING_SNAKE_CASE:						int=16			,     _SCREAMING_SNAKE_CASE:						List[str]="gelu"			,     _SCREAMING_SNAKE_CASE:						Optional[Any]=0.1			,     _SCREAMING_SNAKE_CASE:						int=0.1			,     _SCREAMING_SNAKE_CASE:						List[Any]=0.0			,     _SCREAMING_SNAKE_CASE:						Union[str, Any]=0.0			,     _SCREAMING_SNAKE_CASE:						Any=0.02			,     _SCREAMING_SNAKE_CASE:						Any=True			,     _SCREAMING_SNAKE_CASE:						Tuple=True			,     _SCREAMING_SNAKE_CASE:						Any=2			,     _SCREAMING_SNAKE_CASE:						str=1			,     _SCREAMING_SNAKE_CASE:						Dict=0			,     _SCREAMING_SNAKE_CASE:						Dict=2			,     **_SCREAMING_SNAKE_CASE:						List[Any]			,     )							->			List[str]:

				"""simple docstring"""

				__lowerCAmelCase :    Optional[int]				=			vocab_size
				__lowerCAmelCase :    int				=			max_position_embeddings
				__lowerCAmelCase :    Optional[Any]				=			d_model
				__lowerCAmelCase :    List[Any]				=			ffn_dim
				__lowerCAmelCase :    int				=			num_layers
				__lowerCAmelCase :    Any				=			attention_heads
				__lowerCAmelCase :    int				=			activation_function
				__lowerCAmelCase :    List[Any]				=			dropout
				__lowerCAmelCase :    Optional[int]				=			attention_dropout
				__lowerCAmelCase :    Optional[int]				=			activation_dropout
				__lowerCAmelCase :    Optional[int]				=			layerdrop
				__lowerCAmelCase :    Optional[int]				=			init_std
				__lowerCAmelCase :    Tuple				=			scale_embedding  # scale factor will be sqrt(d_model) if True
				__lowerCAmelCase :    Dict				=			use_cache

				super().__init__(
				    pad_token_id=_SCREAMING_SNAKE_CASE			,     bos_token_id=_SCREAMING_SNAKE_CASE			,     eos_token_id=_SCREAMING_SNAKE_CASE			,     decoder_start_token_id=_SCREAMING_SNAKE_CASE			,     **_SCREAMING_SNAKE_CASE			,     )