





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









import os
from shutil import copyfile
from typing import List, Optional, Tuple

from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
      from .tokenization_camembert import CamembertTokenizer
else:
      lowercase_          =		None


lowercase_          =		logging.get_logger(__name__)

lowercase_          =		{"""vocab_file""": """sentencepiece.bpe.model""", """tokenizer_file""": """tokenizer.json"""}

lowercase_          =		{
    """vocab_file""": {
        """camembert-base""": """https://huggingface.co/camembert-base/resolve/main/sentencepiece.bpe.model""",
    },
    """tokenizer_file""": {
        """camembert-base""": """https://huggingface.co/camembert-base/resolve/main/tokenizer.json""",
    },
}

lowercase_          =		{
    """camembert-base""": 512,
}

lowercase_          =		"""▁"""
class     SCREAMING_SNAKE_CASE       (UpperCAmelCase				):
   _UpperCamelCase   :		int			 =	VOCAB_FILES_NAMES
   _UpperCamelCase   :		Dict			 =	PRETRAINED_VOCAB_FILES_MAP
   _UpperCamelCase   :		Dict			 =	PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   _UpperCamelCase   :		Dict			 =	['input_ids', 'attention_mask']
   _UpperCamelCase   :		Optional[int]			 =	CamembertTokenizer


   def __init__(   self      :    List[Any]      ,					a      :    Union[str, Any]=None      ,					a      :    str=None      ,					a      :    Tuple="<s>"      ,					a      :    Tuple="</s>"      ,					a      :    Optional[int]="</s>"      ,					a      :    int="<s>"      ,					a      :    Dict="<unk>"      ,					a      :    Optional[Any]="<pad>"      ,					a      :    Union[str, Any]="<mask>"      ,					a      :    Any=["<s>NOTUSED", "</s>NOTUSED"]      ,					**a      :    int      ,					)->       str:





     """simple docstring"""







     lowercase__           =  AddedToken(a      ,					lstrip=a      ,					rstrip=a	) if isinstance(a      ,					a	) else mask_token

     super().__init__(
         a      ,					tokenizer_file=a      ,					bos_token=a      ,					eos_token=a      ,					sep_token=a      ,					cls_token=a      ,					unk_token=a      ,					pad_token=a      ,					mask_token=a      ,					additional_special_tokens=a      ,					**a      ,					)

     lowercase__           =  vocab_file
     lowercase__           =  False if not self.vocab_file else True


   def 	SCREAMING_SNAKE_CASE_							(   self      :    Any      ,					a      :    List[int]      ,					a      :    Optional[List[int]] = None	)->       List[int]:





     """simple docstring"""







     if token_ids_a is None:
       return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
     lowercase__           =  [self.cls_token_id]
     lowercase__           =  [self.sep_token_id]
     return cls + token_ids_a + sep + sep + token_ids_a + sep


   def 	SCREAMING_SNAKE_CASE_							(   self      :    Any      ,					a      :    List[int]      ,					a      :    Optional[List[int]] = None	)->       List[int]:





     """simple docstring"""







     lowercase__           =  [self.sep_token_id]
     lowercase__           =  [self.cls_token_id]

     if token_ids_a is None:
       return len(cls + token_ids_a + sep	) * [0]
     return len(cls + token_ids_a + sep + sep + token_ids_a + sep	) * [0]


   def 	SCREAMING_SNAKE_CASE_							(   self      :    Optional[int]      ,					a      :    str      ,					a      :    Optional[str] = None	)->       Tuple[str]:





     """simple docstring"""







     if not self.can_save_slow_tokenizer:
       raise ValueError(
           'Your fast tokenizer does not have the necessary information to save the vocabulary for a slow '
           'tokenizer.'	)

     if not os.path.isdir(a	):
       logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""	)
       return
     lowercase__           =  os.path.join(
         a      ,					(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']	)

     if os.path.abspath(self.vocab_file	) != os.path.abspath(a	):
       copyfile(self.vocab_file      ,					a	)

     return (out_vocab_file,)


