



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


snake_case    :						Tuple  =						logging.get_logger(__name__)

snake_case    :						Tuple  =						{
    '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 							lowerCAmelCase__  (	UpperCamelCase						):
					__A     :    Dict           =						'markuplm'







					def __init__(       self      :     Any			,		_A      :     Optional[Any]=3_0522			,		_A      :     str=768			,		_A      :     Optional[Any]=12			,		_A      :     Dict=12			,		_A      :     Optional[int]=3072			,		_A      :     str="gelu"			,		_A      :     str=0.1			,		_A      :     str=0.1			,		_A      :     List[Any]=512			,		_A      :     int=2			,		_A      :     Any=0.02			,		_A      :     Dict=1e-12			,		_A      :     int=0			,		_A      :     Dict=0			,		_A      :     Dict=2			,		_A      :     Union[str, Any]=256			,		_A      :     List[Any]=1024			,		_A      :     Any=216			,		_A      :     Optional[Any]=1001			,		_A      :     Any=32			,		_A      :     Dict=50			,		_A      :     Optional[Any]="absolute"			,		_A      :     Dict=True			,		_A      :     Optional[Any]=None			,		**_A      :     Optional[int]			,		):
											super().__init__(
											    pad_token_id=_A			,		bos_token_id=_A			,		eos_token_id=_A			,		**_A			,		)
											A__	:							List[str]						    = vocab_size
											A__	:							List[Any]						    = hidden_size
											A__	:							List[str]						    = num_hidden_layers
											A__	:							Dict						    = num_attention_heads
											A__	:							Tuple						    = hidden_act
											A__	:							Dict						    = intermediate_size
											A__	:							str						    = hidden_dropout_prob
											A__	:							str						    = attention_probs_dropout_prob
											A__	:							Optional[Any]						    = max_position_embeddings
											A__	:							Optional[int]						    = type_vocab_size
											A__	:							Union[str, Any]						    = initializer_range
											A__	:							str						    = layer_norm_eps
											A__	:							List[str]						    = position_embedding_type
											A__	:							str						    = use_cache
											A__	:							int						    = classifier_dropout
											# additional properties
											A__	:							Dict						    = max_depth
											A__	:							Optional[int]						    = max_xpath_tag_unit_embeddings
											A__	:							str						    = max_xpath_subs_unit_embeddings
											A__	:							Optional[int]						    = tag_pad_id
											A__	:							str						    = subs_pad_id
											A__	:							List[Any]						    = xpath_unit_hidden_size




def 	snake_case__       (					__lowercase							,     __lowercase							,     __lowercase = 0							,     __lowercase = 0       )		->		int:







						"""simple docstring"""

						A__	:							Tuple						    = right or len(__lowercase       ) - 1
						if left > right:
												return -1
						elif list_data[left] == key:
												return left
						elif list_data[right] == key:
												return right
						else:
												return search(__lowercase							,     __lowercase							,     left + 1							,     right - 1       )


if __name__ == "__main__":
		import doctest

		doctest.testmod()