'''simple docstring'''


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


snake_case__					:      Any				      =  logging.get_logger(__name__)

snake_case__					:      List[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 					__SCREAMING_SNAKE_CASE						(	lowerCamelCase_	):







  '''simple docstring'''






  lowerCamelCase_		:int						   =		'''markuplm'''


  def __init__(			self				,		snake_case_=3_0_5_2_2				,		snake_case_=7_6_8				,		snake_case_=1_2				,		snake_case_=1_2				,		snake_case_=3_0_7_2				,		snake_case_="gelu"				,		snake_case_=0.1				,		snake_case_=0.1				,		snake_case_=5_1_2				,		snake_case_=2				,		snake_case_=0.02				,		snake_case_=1E-12				,		snake_case_=0				,		snake_case_=0				,		snake_case_=2				,		snake_case_=2_5_6				,		snake_case_=1_0_2_4				,		snake_case_=2_1_6				,		snake_case_=1_0_0_1				,		snake_case_=3_2				,		snake_case_=5_0				,		snake_case_="absolute"				,		snake_case_=True				,		snake_case_=None				,		**snake_case_				,		):




       '''simple docstring'''

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







'''simple docstring'''


def  _lowerCamelCase   (				lowerCamelCase_ :							str       ):



     """simple docstring"""





     UpperCAmelCase_							:       Optional[int]       =				[0] * len(lowerCamelCase_       )

     for i in range(1     ,					len(lowerCamelCase_       )       ):
          # use last results for better performance - dynamic programming
          UpperCAmelCase_							:       List[Any]       =				prefix_result[i - 1]
          while j > 0 and input_string[i] != input_string[j]:
               UpperCAmelCase_							:       str       =				prefix_result[j - 1]

          if input_string[i] == input_string[j]:
               j += 1
          UpperCAmelCase_							:       Any       =				j

     return prefix_result


def  _lowerCamelCase   (				lowerCamelCase_ :							str       ):



     """simple docstring"""





     return max(prefix_function(lowerCamelCase_       )       )


if __name__ == "__main__":
 import doctest

 doctest.testmod()






