

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


lowerCAmelCase_			      =      logging.get_logger(__name__)

lowerCAmelCase_			      =      {
    '''microsoft/biogpt''': '''https://huggingface.co/microsoft/biogpt/resolve/main/config.json''',
    # See all BioGPT models at https://huggingface.co/models?filter=biogpt
}





class       snake_case_  (						__A   ):







			'''simple docstring'''

			SCREAMING_SNAKE_CASE	:  Dict		     =							"biogpt"







			def __init__(	self					:							Optional[Any]				,  _UpperCamelCase					:							List[str]=4_2_3_8_4				,  _UpperCamelCase					:							Tuple=1_0_2_4				,  _UpperCamelCase					:							Dict=2_4				,  _UpperCamelCase					:							List[Any]=1_6				,  _UpperCamelCase					:							str=4_0_9_6				,  _UpperCamelCase					:							List[Any]="gelu"				,  _UpperCamelCase					:							List[Any]=0.1				,  _UpperCamelCase					:							int=0.1				,  _UpperCamelCase					:							Dict=1_0_2_4				,  _UpperCamelCase					:							List[str]=0.02				,  _UpperCamelCase					:							List[str]=1e-12				,  _UpperCamelCase					:							Dict=True				,  _UpperCamelCase					:							Tuple=True				,  _UpperCamelCase					:							Tuple=0.0				,  _UpperCamelCase					:							str=0.0				,  _UpperCamelCase					:							str=1				,  _UpperCamelCase					:							List[str]=0				,  _UpperCamelCase					:							int=2				,  **_UpperCamelCase					:							Tuple				,  ) ->List[Any]:
									snake_case_  =      vocab_size
									snake_case_  =      max_position_embeddings
									snake_case_  =      hidden_size
									snake_case_  =      num_hidden_layers
									snake_case_  =      num_attention_heads
									snake_case_  =      intermediate_size
									snake_case_  =      hidden_act
									snake_case_  =      hidden_dropout_prob
									snake_case_  =      attention_probs_dropout_prob
									snake_case_  =      initializer_range
									snake_case_  =      layer_norm_eps
									snake_case_  =      scale_embedding
									snake_case_  =      use_cache
									snake_case_  =      layerdrop
									snake_case_  =      activation_dropout
									super().__init__(pad_token_id=_UpperCamelCase				,  bos_token_id=_UpperCamelCase				,  eos_token_id=_UpperCamelCase				,  **_UpperCamelCase				)






from math import factorial






def 				_UpperCAmelCase			(    A = 20     ):




   '''simple docstring'''

   UpperCAmelCase__						=2 * n  # middle entry of odd rows starting at row 3 is the solution for n = 1,
   # 2, 3,...
   UpperCAmelCase__						=n // 2

   return int(factorial(A     ) / (factorial(A     ) * factorial(n - k     ))     )


if __name__ == "__main__":
    import sys

    if len(sys.argv) == 1:
        print(solution(20))
    else:
        try:
            UpperCamelCase_												=	int(sys.argv[1])
            print(solution(n))
        except ValueError:
            print('Invalid entry - please enter a number.')



