

class       __snake_case  :

		def __init__(					self						,		_A):
						# we need a list not a string, so do something to change the type
						SCREAMING_SNAKE_CASE_									=						arr.split(',')


		def 						lowerCAmelCase__     (					self):
						SCREAMING_SNAKE_CASE_									=						[int(self.array[0])] * len(self.array)
						SCREAMING_SNAKE_CASE_									=						[int(self.array[0])] * len(self.array)
						for i in range(1						,		len(self.array)):
										SCREAMING_SNAKE_CASE_									=						max(
										    int(self.array[i]) + sum_value[i - 1]						,		int(self.array[i]))
										SCREAMING_SNAKE_CASE_									=						max(sum_value[i]						,		rear[i - 1])
						return rear[len(self.array) - 1]


if __name__ == "__main__":
							UpperCamelCase__  :      Tuple			=    input("please input some numbers:")
							UpperCamelCase__  :      Dict			=    SubArray(whole_array)
							UpperCamelCase__  :      Dict			=    array.solve_sub_array()
							print(("the results is:", re))





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


UpperCamelCase__  :      List[Any]			=    logging.get_logger(__name__)

UpperCamelCase__  :      List[str]			=    {
    "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  (    lowerCAmelCase__       ):
  __lowerCAmelCase     :	Any						 =  'biogpt'

  def __init__(					self						,		_A=42384						,		_A=1024						,		_A=24						,		_A=16						,		_A=4096						,		_A="gelu"						,		_A=0.1						,		_A=0.1						,		_A=1024						,		_A=0.0_2						,		_A=1E-12						,		_A=True						,		_A=True						,		_A=0.0						,		_A=0.0						,		_A=1						,		_A=0						,		_A=2						,		**_A						,		):
      SCREAMING_SNAKE_CASE_									=						vocab_size
      SCREAMING_SNAKE_CASE_									=						max_position_embeddings
      SCREAMING_SNAKE_CASE_									=						hidden_size
      SCREAMING_SNAKE_CASE_									=						num_hidden_layers
      SCREAMING_SNAKE_CASE_									=						num_attention_heads
      SCREAMING_SNAKE_CASE_									=						intermediate_size
      SCREAMING_SNAKE_CASE_									=						hidden_act
      SCREAMING_SNAKE_CASE_									=						hidden_dropout_prob
      SCREAMING_SNAKE_CASE_									=						attention_probs_dropout_prob
      SCREAMING_SNAKE_CASE_									=						initializer_range
      SCREAMING_SNAKE_CASE_									=						layer_norm_eps
      SCREAMING_SNAKE_CASE_									=						scale_embedding
      SCREAMING_SNAKE_CASE_									=						use_cache
      SCREAMING_SNAKE_CASE_									=						layerdrop
      SCREAMING_SNAKE_CASE_									=						activation_dropout
      super().__init__(pad_token_id=_A						,		bos_token_id=_A						,		eos_token_id=_A						,		**_A)


