





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


lowercase_          =		logging.get_logger(__name__)

lowercase_          =		{
    """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       (UpperCAmelCase				):
   _UpperCamelCase   :		int			 =	'markuplm'


   def __init__(   self      :    List[Any]      ,					a      :    Optional[int]=30_522      ,					a      :    Optional[int]=768      ,					a      :    Optional[int]=12      ,					a      :    Tuple=12      ,					a      :    List[Any]=3_072      ,					a      :    Optional[int]="gelu"      ,					a      :    Tuple=0.1      ,					a      :    Union[str, Any]=0.1      ,					a      :    List[Any]=512      ,					a      :    List[str]=2      ,					a      :    List[Any]=0.02      ,					a      :    str=1E-1_2      ,					a      :    Dict=0      ,					a      :    Union[str, Any]=0      ,					a      :    Optional[int]=2      ,					a      :    Tuple=256      ,					a      :    int=1_024      ,					a      :    List[str]=216      ,					a      :    Any=1_001      ,					a      :    List[Any]=32      ,					a      :    List[str]=50      ,					a      :    Tuple="absolute"      ,					a      :    Dict=True      ,					a      :    Dict=None      ,					**a      :    Optional[Any]      ,					)->       Union[str, Any]:





     """simple docstring"""







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









from dataclasses import dataclass, field
from typing import ClassVar, Dict

from ..features import Features, Value
from .base import TaskTemplate
@dataclass(frozen=UpperCAmelCase				)
class     SCREAMING_SNAKE_CASE       (UpperCAmelCase				):
   _UpperCamelCase   :		str			 =	field(default='language-modeling'      ,     metadata={'include_in_asdict_even_if_is_default': True}				)

   _UpperCamelCase   :		ClassVar[Features]			 =	Features({'text': Value('string'				)}				)
   _UpperCamelCase   :		ClassVar[Features]			 =	Features({}				)
   _UpperCamelCase   :		str			 =	"text"


   @property
   def 	SCREAMING_SNAKE_CASE_							(   self      :    List[str]	)->       Dict[str, str]:





     """simple docstring"""







     return {self.text_column: "text"}


