"""simple docstring"""


import os
import sys

lowerCAmelCase_:					Any     =					os.path.join(os.path.dirname(__file__), "src")
sys.path.append(SRC_DIR)


from transformers import (
    AutoConfig,
    AutoModel,
    AutoModelForCausalLM,
    AutoModelForMaskedLM,
    AutoModelForQuestionAnswering,
    AutoModelForSequenceClassification,
    AutoTokenizer,
    add_start_docstrings,
)


lowerCAmelCase_:					Union[str, Any]     =					[
    "torch",
    "numpy",
    "tokenizers",
    "filelock",
    "requests",
    "tqdm",
    "regex",
    "sentencepiece",
    "sacremoses",
    "importlib_metadata",
    "huggingface_hub",
]







@add_start_docstrings(AutoConfig.__doc__      )
def 					__a   (		*A    ,				**A      ):






     '''simple docstring'''



     return AutoConfig.from_pretrained(*A    ,				**A      )







@add_start_docstrings(AutoTokenizer.__doc__      )
def 					__a   (		*A    ,				**A      ):






     '''simple docstring'''



     return AutoTokenizer.from_pretrained(*A    ,				**A      )







@add_start_docstrings(AutoModel.__doc__      )
def 					__a   (		*A    ,				**A      ):






     '''simple docstring'''



     return AutoModel.from_pretrained(*A    ,				**A      )







@add_start_docstrings(AutoModelForCausalLM.__doc__      )
def 					__a   (		*A    ,				**A      ):






     '''simple docstring'''



     return AutoModelForCausalLM.from_pretrained(*A    ,				**A      )







@add_start_docstrings(AutoModelForMaskedLM.__doc__      )
def 					__a   (		*A    ,				**A      ):






     '''simple docstring'''



     return AutoModelForMaskedLM.from_pretrained(*A    ,				**A      )







@add_start_docstrings(AutoModelForSequenceClassification.__doc__      )
def 					__a   (		*A    ,				**A      ):






     '''simple docstring'''



     return AutoModelForSequenceClassification.from_pretrained(*A    ,				**A      )







@add_start_docstrings(AutoModelForQuestionAnswering.__doc__      )
def 					__a   (		*A    ,				**A      ):






     '''simple docstring'''



     return AutoModelForQuestionAnswering.from_pretrained(*A    ,				**A      )





"""simple docstring"""


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


lowerCAmelCase_:					List[Any]     =					logging.get_logger(__name__)

lowerCAmelCase_:					int     =					{
    "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__    (   _a	):
   snake_case_							=      "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=_UpperCAmelCase,				bos_token_id=_UpperCAmelCase,				eos_token_id=_UpperCAmelCase,				**_UpperCAmelCase,				)
        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




