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


UpperCAmelCase	      = logging.get_logger(__name__)

UpperCAmelCase	      = {
    '''weiweishi/roc-bert-base-zh''': '''https://huggingface.co/weiweishi/roc-bert-base-zh/resolve/main/config.json''',
}







class        A_   (			__a   ):




	'''simple docstring'''


	_UpperCamelCase     :     Tuple							 =       """roc_bert"""





	def __init__(       self		,    snake_case=3_0522		,    snake_case=768		,    snake_case=12		,    snake_case=12		,    snake_case=3072		,    snake_case="gelu"		,    snake_case=0.1		,    snake_case=0.1		,    snake_case=512		,    snake_case=2		,    snake_case=0.02		,    snake_case=1E-12		,    snake_case=True		,    snake_case=0		,    snake_case="absolute"		,    snake_case=None		,    snake_case=True		,    snake_case=True		,    snake_case=768		,    snake_case=910		,    snake_case=512		,    snake_case=2_4858		,    snake_case=True		,    **snake_case		,    ):
		lowercase       =    vocab_size
		lowercase       =    max_position_embeddings
		lowercase       =    hidden_size
		lowercase       =    num_hidden_layers
		lowercase       =    num_attention_heads
		lowercase       =    intermediate_size
		lowercase       =    hidden_act
		lowercase       =    hidden_dropout_prob
		lowercase       =    attention_probs_dropout_prob
		lowercase       =    initializer_range
		lowercase       =    type_vocab_size
		lowercase       =    layer_norm_eps
		lowercase       =    use_cache
		lowercase       =    enable_pronunciation
		lowercase       =    enable_shape
		lowercase       =    pronunciation_embed_dim
		lowercase       =    pronunciation_vocab_size
		lowercase       =    shape_embed_dim
		lowercase       =    shape_vocab_size
		lowercase       =    concat_input
		lowercase       =    position_embedding_type
		lowercase       =    classifier_dropout
		super().__init__(pad_token_id=a_		,    **a_       )







"""simple docstring"""


from __future__ import annotations


def 					UpperCAmelCase__       (snake_case__							:					list[int]		,   snake_case__							:					int    ):
  """simple docstring"""

  if len(snake_case__    ) < k or k < 0:
    raise ValueError("""Invalid Input"""    )
  _snake_case							:		Optional[int]								=  sum(array[:k]    )
  for i in range(len(snake_case__    ) - k    ):
    _snake_case							:		Optional[Any]								=  current_sum - array[i] + array[i + k]
    _snake_case							:		List[str]								=  max(snake_case__		,   snake_case__    )
  return max_sum


if __name__ == "__main__":
     from doctest import testmod
     from random import randint

     testmod()
     A_						=				[randint(-10_00, 10_00) for i in range(1_00)]
     A_						=				randint(0, 1_10)
     print(F'''The maximum sum of {k} consecutive elements is {max_sum_in_array(array,k)}''')


