




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


lowerCamelCase				:		str     =   logging.get_logger(__name__)

lowerCamelCase				:		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   A(						UpperCamelCase   ):



 '''simple docstring'''


 UpperCamelCase						   =						'''markuplm'''

 def __init__(				self					:  Dict						,							A_					:  List[str]=30522						,							A_					:  Optional[int]=768						,							A_					:  Any=12						,							A_					:  List[Any]=12						,							A_					:  Tuple=3072						,							A_					:  List[Any]="gelu"						,							A_					:  Dict=0.1						,							A_					:  Any=0.1						,							A_					:  int=512						,							A_					:  List[str]=2						,							A_					:  Tuple=0.02						,							A_					:  Dict=1E-12						,							A_					:  Optional[Any]=0						,							A_					:  int=0						,							A_					:  Tuple=2						,							A_					:  Union[str, Any]=256						,							A_					:  Any=1024						,							A_					:  Tuple=216						,							A_					:  str=1001						,							A_					:  Optional[int]=32						,							A_					:  int=50						,							A_					:  str="absolute"						,							A_					:  List[str]=True						,							A_					:  Union[str, Any]=None						,							**A_					:  List[str]						,							)   ->	Tuple:

       """simple docstring"""






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









import warnings

from ...utils import logging
from .image_processing_donut import DonutImageProcessor


lowerCamelCase				:		Any     =   logging.get_logger(__name__)







class   A(						UpperCamelCase   ):



 '''simple docstring'''


 def __init__(				self					:  Dict						,							*A_					:  Optional[int]						,							**A_					:  int  )   ->	None:

       """simple docstring"""






       warnings.warn(
           'The class DonutFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please'
           ' use DonutImageProcessor instead.'						,							A_						,							)
       super().__init__(*A_						,							**A_  )



