




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


lowerCamelCase				:		int     =   logging.get_logger(__name__)

lowerCamelCase				:		Tuple     =   {
    "google/canine-s": "https://huggingface.co/google/canine-s/resolve/main/config.json",
    # See all CANINE models at https://huggingface.co/models?filter=canine
}







class   A(						UpperCamelCase   ):



 '''simple docstring'''


 UpperCamelCase						   =						'''canine'''

 def __init__(				self					:  Any						,							A_					:  Optional[Any]=768						,							A_					:  Union[str, Any]=12						,							A_					:  Dict=12						,							A_					:  Optional[int]=3072						,							A_					:  Optional[int]="gelu"						,							A_					:  Optional[Any]=0.1						,							A_					:  Optional[int]=0.1						,							A_					:  Union[str, Any]=16384						,							A_					:  int=16						,							A_					:  Any=0.02						,							A_					:  Dict=1E-12						,							A_					:  str=0						,							A_					:  int=0XE0_00						,							A_					:  str=0XE0_01						,							A_					:  Any=4						,							A_					:  Union[str, Any]=4						,							A_					:  Any=8						,							A_					:  Dict=16384						,							A_					:  str=128						,							**A_					:  str						,							)   ->	Optional[int]:

       """simple docstring"""






       super().__init__(pad_token_id=A_						,							bos_token_id=A_						,							eos_token_id=A_						,							**A_  )

       lowerCamelCase_		     =    max_position_embeddings
       lowerCamelCase_		     =    hidden_size
       lowerCamelCase_		     =    num_hidden_layers
       lowerCamelCase_		     =    num_attention_heads
       lowerCamelCase_		     =    intermediate_size
       lowerCamelCase_		     =    hidden_act
       lowerCamelCase_		     =    hidden_dropout_prob
       lowerCamelCase_		     =    attention_probs_dropout_prob
       lowerCamelCase_		     =    initializer_range
       lowerCamelCase_		     =    type_vocab_size
       lowerCamelCase_		     =    layer_norm_eps

       # Character config:
       lowerCamelCase_		     =    downsampling_rate
       lowerCamelCase_		     =    upsampling_kernel_size
       lowerCamelCase_		     =    num_hash_functions
       lowerCamelCase_		     =    num_hash_buckets
       lowerCamelCase_		     =    local_transformer_stride









def 			_SCREAMING_SNAKE_CASE			(							lowercase	:       float	,							lowercase	:       list[float]     ):


      '''simple docstring'''



      if discount_rate < 0:
            raise ValueError('Discount rate cannot be negative'     )
      if not cash_flows:
            raise ValueError('Cash flows list cannot be empty'     )
      lowerCamelCase_		     =    sum(
          cash_flow / ((1 + discount_rate) ** i) for i, cash_flow in enumerate(lowercase     )     )
      return round(lowercase	,							ndigits=2     )


if __name__ == "__main__":
 import doctest

 doctest.testmod()



