
'''simple docstring'''




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


lowercase			:				Any    		=			logging.get_logger(__name__)

lowercase			:				int    		=			{
    'tiiuae/falcon-40b': 'https://huggingface.co/tiiuae/falcon-40b/resolve/main/config.json',
    'tiiuae/falcon-7b': 'https://huggingface.co/tiiuae/falcon-7b/resolve/main/config.json',
}





class  A				(							__snake_case						):
     __magic_name__						=		'''falcon'''
     __magic_name__						=		['''past_key_values''']





     def __init__(							self						,			SCREAMING_SNAKE_CASE=65024						,			SCREAMING_SNAKE_CASE=4544						,			SCREAMING_SNAKE_CASE=32						,			SCREAMING_SNAKE_CASE=71						,			SCREAMING_SNAKE_CASE=1e-5						,			SCREAMING_SNAKE_CASE=0.02						,			SCREAMING_SNAKE_CASE=True						,			SCREAMING_SNAKE_CASE=0.0						,			SCREAMING_SNAKE_CASE=0.0						,			SCREAMING_SNAKE_CASE=None						,			SCREAMING_SNAKE_CASE=False						,			SCREAMING_SNAKE_CASE=False						,			SCREAMING_SNAKE_CASE=True						,			SCREAMING_SNAKE_CASE=True						,			SCREAMING_SNAKE_CASE=False						,			SCREAMING_SNAKE_CASE=11						,			SCREAMING_SNAKE_CASE=11						,			**SCREAMING_SNAKE_CASE						,			) ->				Tuple:






         """simple docstring"""






         A       :   Tuple					=						vocab_size
         # Backward compatibility with n_embed kwarg
         A       :   Dict					=						kwargs.pop('''n_embed'''						,			SCREAMING_SNAKE_CASE	)
         A       :   int					=						hidden_size if n_embed is None else n_embed
         A       :   Dict					=						num_hidden_layers
         A       :   List[Any]					=						num_attention_heads
         A       :   Optional[Any]					=						layer_norm_epsilon
         A       :   List[Any]					=						initializer_range
         A       :   str					=						use_cache
         A       :   Optional[int]					=						hidden_dropout
         A       :   Union[str, Any]					=						attention_dropout

         A       :   Dict					=						bos_token_id
         A       :   List[Any]					=						eos_token_id
         A       :   List[str]					=						num_attention_heads if num_kv_heads is None else num_kv_heads
         A       :   int					=						alibi
         A       :   List[str]					=						new_decoder_architecture
         A       :   Union[str, Any]					=						multi_query  # Ignored when new_decoder_architecture is True
         A       :   int					=						parallel_attn
         A       :   Union[str, Any]					=						bias

         super().__init__(bos_token_id=SCREAMING_SNAKE_CASE						,			eos_token_id=SCREAMING_SNAKE_CASE						,			**SCREAMING_SNAKE_CASE	)





     @property
     def 				__lowerCAmelCase							(							self	) ->				List[Any]:






         """simple docstring"""






         return self.hidden_size // self.num_attention_heads





     @property
     def 				__lowerCAmelCase							(							self	) ->				Tuple:






         """simple docstring"""






         return not self.alibi








'''simple docstring'''






from math import ceil







def 				UpperCamelCase_			(    A__					:   int = 10_01					):
  '''simple docstring'''





  lowerCAmelCase_			:      List[Any]			=   1

  for i in range(1							,    int(ceil(n / 2.0					)					)					):
    lowerCAmelCase_			:      int			=   2 * i + 1
    lowerCAmelCase_			:      Tuple			=   2 * i
    lowerCAmelCase_			:      Tuple			=   total + 4 * odd**2 - 6 * even

  return total


if __name__ == "__main__":
  import sys

  if len(sys.argv) == 1:
    print(solution())
  else:
    try:
      __A					:  str											=      int(sys.argv[1])
      print(solution(n))
    except ValueError:
      print("Invalid entry - please enter a number")



