
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging


A__   :		Optional[Any] 		=logging.get_logger(__name__)

A__   :		str 		={
    'microsoft/markuplm-base': 'https://huggingface.co/microsoft/markuplm-base/resolve/main/config.json',
    'microsoft/markuplm-large': 'https://huggingface.co/microsoft/markuplm-large/resolve/main/config.json',
}







class  __A				( _SCREAMING_SNAKE_CASE			):
 lowerCamelCase				       ='''markuplm'''
 def __init__(   self			:    Optional[int]				,   lowerCamelCase			:    Optional[Any]=3_05_22				,   lowerCamelCase			:    Optional[Any]=7_68				,   lowerCamelCase			:    Dict=12				,   lowerCamelCase			:    Dict=12				,   lowerCamelCase			:    Dict=30_72				,   lowerCamelCase			:    Union[str, Any]="gelu"				,   lowerCamelCase			:    Dict=0.1				,   lowerCamelCase			:    str=0.1				,   lowerCamelCase			:    List[str]=5_12				,   lowerCamelCase			:    Any=2				,   lowerCamelCase			:    Optional[int]=0.02				,   lowerCamelCase			:    Tuple=1e-1_2				,   lowerCamelCase			:    Optional[int]=0				,   lowerCamelCase			:    Optional[Any]=0				,   lowerCamelCase			:    List[Any]=2				,   lowerCamelCase			:    int=2_56				,   lowerCamelCase			:    Any=10_24				,   lowerCamelCase			:    List[str]=2_16				,   lowerCamelCase			:    Dict=10_01				,   lowerCamelCase			:    Union[str, Any]=32				,   lowerCamelCase			:    List[str]=50				,   lowerCamelCase			:    Union[str, Any]="absolute"				,   lowerCamelCase			:    Dict=True				,   lowerCamelCase			:    Optional[Any]=None				,   **lowerCamelCase			:    Optional[int]				,   ):



   """simple docstring"""





   super().__init__(
       pad_token_id=lowerCamelCase				,   bos_token_id=lowerCamelCase				,   eos_token_id=lowerCamelCase				,   **lowerCamelCase				,   )
   __A		:     int												=		vocab_size
   __A		:     Tuple												=		hidden_size
   __A		:     Optional[int]												=		num_hidden_layers
   __A		:     Dict												=		num_attention_heads
   __A		:     Any												=		hidden_act
   __A		:     str												=		intermediate_size
   __A		:     Union[str, Any]												=		hidden_dropout_prob
   __A		:     List[str]												=		attention_probs_dropout_prob
   __A		:     Union[str, Any]												=		max_position_embeddings
   __A		:     Optional[int]												=		type_vocab_size
   __A		:     Optional[Any]												=		initializer_range
   __A		:     List[Any]												=		layer_norm_eps
   __A		:     Optional[int]												=		position_embedding_type
   __A		:     Any												=		use_cache
   __A		:     List[Any]												=		classifier_dropout
   # additional properties
   __A		:     List[str]												=		max_depth
   __A		:     List[Any]												=		max_xpath_tag_unit_embeddings
   __A		:     Tuple												=		max_xpath_subs_unit_embeddings
   __A		:     str												=		tag_pad_id
   __A		:     Any												=		subs_pad_id
   __A		:     Optional[int]												=		xpath_unit_hidden_size





'''simple docstring'''
def        A_     (						__SCREAMING_SNAKE_CASE						:  list			,     __SCREAMING_SNAKE_CASE						:  list			,     __SCREAMING_SNAKE_CASE						:  int			,     __SCREAMING_SNAKE_CASE						:  int			,     __SCREAMING_SNAKE_CASE						:  int )				->       int:





  """simple docstring"""

  if index == number_of_items:
    return 0
  __A		:     List[Any]												=		0
  __A		:     Union[str, Any]												=		0
  __A		:     List[Any]												=		knapsack(__SCREAMING_SNAKE_CASE			,     __SCREAMING_SNAKE_CASE			,     __SCREAMING_SNAKE_CASE			,     __SCREAMING_SNAKE_CASE			,     index + 1 )
  if weights[index] <= max_weight:
    __A		:     Tuple												=		values[index] + knapsack(
        __SCREAMING_SNAKE_CASE			,     __SCREAMING_SNAKE_CASE			,     __SCREAMING_SNAKE_CASE			,     max_weight - weights[index]			,     index + 1 )
  return max(__SCREAMING_SNAKE_CASE			,     __SCREAMING_SNAKE_CASE )


if __name__ == "__main__":
     import doctest

     doctest.testmod()



