






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


_a      	=  logging.get_logger(__name__)

_a      	=  {
    '''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):





	"""simple docstring"""






	UpperCamelCase__								=      '''markuplm'''

	def __init__(							self       ,    UpperCAmelCase=3_0522       ,    UpperCAmelCase=768       ,    UpperCAmelCase=12       ,    UpperCAmelCase=12       ,    UpperCAmelCase=3072       ,    UpperCAmelCase="gelu"       ,    UpperCAmelCase=0.1       ,    UpperCAmelCase=0.1       ,    UpperCAmelCase=512       ,    UpperCAmelCase=2       ,    UpperCAmelCase=0.02       ,    UpperCAmelCase=1e-12       ,    UpperCAmelCase=0       ,    UpperCAmelCase=0       ,    UpperCAmelCase=2       ,    UpperCAmelCase=256       ,    UpperCAmelCase=1024       ,    UpperCAmelCase=216       ,    UpperCAmelCase=1001       ,    UpperCAmelCase=32       ,    UpperCAmelCase=50       ,    UpperCAmelCase="absolute"       ,    UpperCAmelCase=True       ,    UpperCAmelCase=None       ,    **UpperCAmelCase       ,    ):
							"""simple docstring"""







							super().__init__(
							    pad_token_id=__SCREAMING_SNAKE_CASE       ,    bos_token_id=__SCREAMING_SNAKE_CASE       ,    eos_token_id=__SCREAMING_SNAKE_CASE       ,    **__SCREAMING_SNAKE_CASE       ,    )
							_UpperCAmelCase									=			vocab_size
							_UpperCAmelCase									=			hidden_size
							_UpperCAmelCase									=			num_hidden_layers
							_UpperCAmelCase									=			num_attention_heads
							_UpperCAmelCase									=			hidden_act
							_UpperCAmelCase									=			intermediate_size
							_UpperCAmelCase									=			hidden_dropout_prob
							_UpperCAmelCase									=			attention_probs_dropout_prob
							_UpperCAmelCase									=			max_position_embeddings
							_UpperCAmelCase									=			type_vocab_size
							_UpperCAmelCase									=			initializer_range
							_UpperCAmelCase									=			layer_norm_eps
							_UpperCAmelCase									=			position_embedding_type
							_UpperCAmelCase									=			use_cache
							_UpperCAmelCase									=			classifier_dropout
							# additional properties
							_UpperCAmelCase									=			max_depth
							_UpperCAmelCase									=			max_xpath_tag_unit_embeddings
							_UpperCAmelCase									=			max_xpath_subs_unit_embeddings
							_UpperCAmelCase									=			tag_pad_id
							_UpperCAmelCase									=			subs_pad_id
							_UpperCAmelCase									=			xpath_unit_hidden_size





import logging

from transformers.configuration_utils import PretrainedConfig


__snake_case						:Any      		=     logging.getLogger(__name__)

class     _A       (	__UpperCAmelCase    ):
       UpperCamelCase__  :    Optional[Any]											=						'''masked_bert'''



       def __init__(		self							:     str     ,		__SCREAMING_SNAKE_CASE							:     int=30_522     ,		__SCREAMING_SNAKE_CASE							:     str=768     ,		__SCREAMING_SNAKE_CASE							:     List[str]=12     ,		__SCREAMING_SNAKE_CASE							:     Any=12     ,		__SCREAMING_SNAKE_CASE							:     Union[str, Any]=3_072     ,		__SCREAMING_SNAKE_CASE							:     List[Any]="gelu"     ,		__SCREAMING_SNAKE_CASE							:     int=0.1     ,		__SCREAMING_SNAKE_CASE							:     Dict=0.1     ,		__SCREAMING_SNAKE_CASE							:     Optional[Any]=512     ,		__SCREAMING_SNAKE_CASE							:     Optional[int]=2     ,		__SCREAMING_SNAKE_CASE							:     Dict=0.02     ,		__SCREAMING_SNAKE_CASE							:     List[Any]=1E-12     ,		__SCREAMING_SNAKE_CASE							:     Union[str, Any]=0     ,		__SCREAMING_SNAKE_CASE							:     List[str]="topK"     ,		__SCREAMING_SNAKE_CASE							:     List[Any]="constant"     ,		__SCREAMING_SNAKE_CASE							:     int=0.0     ,		**__SCREAMING_SNAKE_CASE							:     List[Any]     ,		):


           '''simple docstring'''

           super().__init__(pad_token_id=__SCREAMING_SNAKE_CASE     ,		**__SCREAMING_SNAKE_CASE)

           __a						       =				vocab_size
           __a						       =				hidden_size
           __a						       =				num_hidden_layers
           __a						       =				num_attention_heads
           __a						       =				hidden_act
           __a						       =				intermediate_size
           __a						       =				hidden_dropout_prob
           __a						       =				attention_probs_dropout_prob
           __a						       =				max_position_embeddings
           __a						       =				type_vocab_size
           __a						       =				initializer_range
           __a						       =				layer_norm_eps
           __a						       =				pruning_method
           __a						       =				mask_init
           __a						       =				mask_scale





