

from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


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

a_     :    int     		=   {
    "YituTech/conv-bert-base": "https://huggingface.co/YituTech/conv-bert-base/resolve/main/config.json",
    "YituTech/conv-bert-medium-small": (
        "https://huggingface.co/YituTech/conv-bert-medium-small/resolve/main/config.json"
    ),
    "YituTech/conv-bert-small": "https://huggingface.co/YituTech/conv-bert-small/resolve/main/config.json",
    # See all ConvBERT models at https://huggingface.co/models?filter=convbert
}




class   UpperCamelCase			(  SCREAMING_SNAKE_CASE ):
    __UpperCamelCase    ="convbert"

    def __init__(      self			:   List[Any]				,     snake_case__			:   Union[str, Any]=3_0_5_2_2				,     snake_case__			:   List[Any]=7_6_8				,     snake_case__			:   str=1_2				,     snake_case__			:   Optional[int]=1_2				,     snake_case__			:   List[Any]=3_0_7_2				,     snake_case__			:   str="gelu"				,     snake_case__			:   List[str]=0.1				,     snake_case__			:   Optional[int]=0.1				,     snake_case__			:   List[Any]=5_1_2				,     snake_case__			:   int=2				,     snake_case__			:   Any=0.02				,     snake_case__			:   Optional[Any]=1E-12				,     snake_case__			:   str=1				,     snake_case__			:   Dict=0				,     snake_case__			:   Any=2				,     snake_case__			:   str=7_6_8				,     snake_case__			:   Dict=2				,     snake_case__			:   Optional[int]=9				,     snake_case__			:   Any=1				,     snake_case__			:   List[str]=None				,     **snake_case__			:   str				,     ):

     """simple docstring"""






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

     SCREAMING_SNAKE_CASE		    =      vocab_size
     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		    =      max_position_embeddings
     SCREAMING_SNAKE_CASE		    =      type_vocab_size
     SCREAMING_SNAKE_CASE		    =      initializer_range
     SCREAMING_SNAKE_CASE		    =      layer_norm_eps
     SCREAMING_SNAKE_CASE		    =      embedding_size
     SCREAMING_SNAKE_CASE		    =      head_ratio
     SCREAMING_SNAKE_CASE		    =      conv_kernel_size
     SCREAMING_SNAKE_CASE		    =      num_groups
     SCREAMING_SNAKE_CASE		    =      classifier_dropout




class   UpperCamelCase			(  SCREAMING_SNAKE_CASE ):

    @property
    def UpperCamelCase      (      self			:   str     ):

     """simple docstring"""






     if self.task == "multiple-choice":
      SCREAMING_SNAKE_CASE		    =      {0: 'batch', 1: 'choice', 2: 'sequence'}
     else:
      SCREAMING_SNAKE_CASE		    =      {0: 'batch', 1: 'sequence'}
     return OrderedDict(
         [
             ('input_ids', dynamic_axis),
             ('attention_mask', dynamic_axis),
             ('token_type_ids', dynamic_axis),
         ]     )




from collections.abc import Sequence


def 							__lowerCAmelCase     (							_UpperCamelCase		:	Sequence[int] | None = None						)		->				int:
 '''simple docstring'''


 if nums is None or not nums:
  raise ValueError('Input sequence should not be empty'						)

 SCREAMING_SNAKE_CASE		    =      nums[0]
 for i in range(1		,				len(_UpperCamelCase						)						):
  SCREAMING_SNAKE_CASE		    =      nums[i]
  SCREAMING_SNAKE_CASE		    =      max(_UpperCamelCase		,				ans + num		,				_UpperCamelCase						)

 return ans


if __name__ == "__main__":
      import doctest

      doctest.testmod()

      # Try on a sample input from the user
      a_     :    str     		=   int(input("Enter number of elements : ").strip())
      a_     :    Any     		=   list(map(int, input("\nEnter the numbers : ").strip().split()))[:n]
      print(max_subsequence_sum(array))

