




"""simple docstring"""

import warnings

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


a							      =     logging.get_logger(__name__)

a							      =     {
    '''RUCAIBox/mvp''': '''https://huggingface.co/RUCAIBox/mvp/resolve/main/config.json''',
}





class 							lowercase_			(	__lowerCAmelCase				):



 '''simple docstring'''
 UpperCAmelCase       :	str     =      '''mvp'''
 UpperCAmelCase       :	Union[str, Any]     =      ['''past_key_values''']
 UpperCAmelCase       :	int     =      {'''num_attention_heads''': '''encoder_attention_heads''', '''hidden_size''': '''d_model'''}

 def __init__(					self			:			List[Any]       ,				_UpperCAmelCase			:			Optional[Any]=50_267       ,				_UpperCAmelCase			:			Optional[Any]=1_024       ,				_UpperCAmelCase			:			Tuple=12       ,				_UpperCAmelCase			:			Tuple=4_096       ,				_UpperCAmelCase			:			int=16       ,				_UpperCAmelCase			:			Union[str, Any]=12       ,				_UpperCAmelCase			:			str=4_096       ,				_UpperCAmelCase			:			str=16       ,				_UpperCAmelCase			:			Optional[int]=0.0       ,				_UpperCAmelCase			:			Any=0.0       ,				_UpperCAmelCase			:			Tuple="gelu"       ,				_UpperCAmelCase			:			int=1_024       ,				_UpperCAmelCase			:			List[Any]=0.1       ,				_UpperCAmelCase			:			Dict=0.0       ,				_UpperCAmelCase			:			str=0.0       ,				_UpperCAmelCase			:			str=0.02       ,				_UpperCAmelCase			:			Union[str, Any]=0.0       ,				_UpperCAmelCase			:			Union[str, Any]=False       ,				_UpperCAmelCase			:			Tuple=True       ,				_UpperCAmelCase			:			Any=1       ,				_UpperCAmelCase			:			Optional[int]=0       ,				_UpperCAmelCase			:			Union[str, Any]=2       ,				_UpperCAmelCase			:			Union[str, Any]=True       ,				_UpperCAmelCase			:			Optional[Any]=2       ,				_UpperCAmelCase			:			Union[str, Any]=2       ,				_UpperCAmelCase			:			Optional[Any]=False       ,				_UpperCAmelCase			:			List[Any]=100       ,				_UpperCAmelCase			:			int=800       ,				**_UpperCAmelCase			:			Any       ,				):
       _A     =  vocab_size
       _A     =  max_position_embeddings
       _A     =  d_model
       _A     =  encoder_ffn_dim
       _A     =  encoder_layers
       _A     =  encoder_attention_heads
       _A     =  decoder_ffn_dim
       _A     =  decoder_layers
       _A     =  decoder_attention_heads
       _A     =  dropout
       _A     =  attention_dropout
       _A     =  activation_dropout
       _A     =  activation_function
       _A     =  init_std
       _A     =  encoder_layerdrop
       _A     =  decoder_layerdrop
       _A     =  classifier_dropout
       _A     =  use_cache
       _A     =  encoder_layers
       _A     =  scale_embedding  # scale factor will be sqrt(d_model) if True
       _A     =  use_prompt
       _A     =  prompt_length
       _A     =  prompt_mid_dim

       super().__init__(
           pad_token_id=_UpperCAmelCase       ,				bos_token_id=_UpperCAmelCase       ,				eos_token_id=_UpperCAmelCase       ,				is_encoder_decoder=_UpperCAmelCase       ,				decoder_start_token_id=_UpperCAmelCase       ,				forced_eos_token_id=_UpperCAmelCase       ,				**_UpperCAmelCase       ,				)

       if self.forced_bos_token_id is None and kwargs.get('force_bos_token_to_be_generated'       ,				_UpperCAmelCase						):
             _A     =  self.bos_token_id
             warnings.warn(
                 F'''Please make sure the config includes `forced_bos_token_id={self.bos_token_id}` in future versions. '''
                 'The config can simply be saved and uploaded again to be fixed.'						)







"""simple docstring"""

def 		_snake_case	(   _snake_case				:   int							,    _snake_case				:   int				)       ->   int:






      '''simple docstring'''


      return int((input_a, input_a).count(1				) != 0				)






def 		_snake_case	(   )       ->   None:






      '''simple docstring'''


      assert or_gate(0							,    0				) == 0
      assert or_gate(0							,    1				) == 1
      assert or_gate(1							,    0				) == 1
      assert or_gate(1							,    1				) == 1


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

