



"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging


A:     str										=	logging.get_logger(__name__)

A:     List[str]										=	{
    "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    SCREAMING_SNAKE_CASE__						(      UpperCAmelCase__				):
   __lowerCAmelCase						:     Union[str, Any]		=		'xglm'
   __lowerCAmelCase						:     Union[str, Any]		=		['past_key_values']

   __lowerCAmelCase						:     Optional[int]		=		{
       'num_attention_heads': 'attention_heads',
       'hidden_size': 'd_model',
       'num_hidden_layers': 'num_layers',
   }

   def __init__(     self   ,  _SCREAMING_SNAKE_CASE=256008   ,  _SCREAMING_SNAKE_CASE=2048   ,  _SCREAMING_SNAKE_CASE=1024   ,  _SCREAMING_SNAKE_CASE=4096   ,  _SCREAMING_SNAKE_CASE=24   ,  _SCREAMING_SNAKE_CASE=16   ,  _SCREAMING_SNAKE_CASE="gelu"   ,  _SCREAMING_SNAKE_CASE=0.1   ,  _SCREAMING_SNAKE_CASE=0.1   ,  _SCREAMING_SNAKE_CASE=0.0   ,  _SCREAMING_SNAKE_CASE=0.0   ,  _SCREAMING_SNAKE_CASE=0.02   ,  _SCREAMING_SNAKE_CASE=True   ,  _SCREAMING_SNAKE_CASE=True   ,  _SCREAMING_SNAKE_CASE=2   ,  _SCREAMING_SNAKE_CASE=1   ,  _SCREAMING_SNAKE_CASE=0   ,  _SCREAMING_SNAKE_CASE=2   ,  **_SCREAMING_SNAKE_CASE   ,  )						->   Union[str, Any]:





    '''simple docstring'''




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





"""simple docstring"""
def    _snake_case		(		UpperCamelCase		:	int    ,	UpperCamelCase		:	int		):
 return 1 if input_a == input_a else 0

def    _snake_case		(		):
 assert xnor_gate(0    ,	0		) == 1
 assert xnor_gate(0    ,	1		) == 0
 assert xnor_gate(1    ,	0		) == 0
 assert xnor_gate(1    ,	1		) == 1


if __name__ == "__main__":
      print(xnor_gate(0, 0))
      print(xnor_gate(0, 1))
      print(xnor_gate(1, 0))
      print(xnor_gate(1, 1))
