



'''simple docstring'''





import json
import os
from typing import Dict, List, Optional, Tuple

import regex as re

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


A					:       int									=     logging.get_logger(__name__)


A					:       Union[str, Any]									=     {
    """vocab_file""": """vocab.json""",
    """merges_file""": """merges.txt""",
    """tokenizer_config_file""": """tokenizer_config.json""",
}

A					:       Dict									=     {
    """vocab_file""": {
        """facebook/blenderbot_small-90M""": """https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/vocab.json"""
    },
    """merges_file""": {
        """facebook/blenderbot_small-90M""": """https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/merges.txt"""
    },
    """tokenizer_config_file""": {
        """facebook/blenderbot_small-90M""": (
            """https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/tokenizer_config.json"""
        )
    },
}

A					:       Optional[Any]									=     {"""facebook/blenderbot_small-90M""": 512}
def 						_a       (    lowerCamelCase_				):
   snake_case       :				int		    =set()
   snake_case       :				Union[str, Any]		    =word[0]
   for char in word[1:]:
      pairs.add((prev_char, char)				)
      snake_case       :				Dict		    =char

   snake_case       :				int		    =set(snake_case__				)
   return pairs





class 				lowerCAmelCase_						(			lowerCamelCase__		):
    __UpperCAmelCase				=			VOCAB_FILES_NAMES
    __UpperCAmelCase				=			PRETRAINED_VOCAB_FILES_MAP
    __UpperCAmelCase				=			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    __UpperCAmelCase				=			['input_ids', 'attention_mask']





    def __init__(							self							:							Any,							_snake_case							:							Optional[int],							_snake_case							:							List[Any],							_snake_case							:							Tuple="__start__",							_snake_case							:							List[str]="__end__",							_snake_case							:							List[str]="__unk__",							_snake_case							:							Dict="__null__",							**_snake_case							:							List[Any],							):



       '''simple docstring'''







       super().__init__(unk_token=SCREAMING_SNAKE_CASE__,							bos_token=SCREAMING_SNAKE_CASE__,							eos_token=SCREAMING_SNAKE_CASE__,							pad_token=SCREAMING_SNAKE_CASE__,							**SCREAMING_SNAKE_CASE__      )

       with open(SCREAMING_SNAKE_CASE__,							encoding='''utf-8'''      ) as vocab_handle:
          snake_case       :				List[str]		    =json.load(SCREAMING_SNAKE_CASE__      )
       snake_case       :				List[str]		    ={v: k for k, v in self.encoder.items()}
       with open(SCREAMING_SNAKE_CASE__,							encoding='''utf-8'''      ) as merges_handle:
          snake_case       :				List[str]		    =merges_handle.read().split('''\n'''      )[1:-1]
       snake_case       :				Tuple		    =[tuple(merge.split()      ) for merge in merges]
       snake_case       :				Union[str, Any]		    =dict(zip(SCREAMING_SNAKE_CASE__,							range(len(SCREAMING_SNAKE_CASE__      )      )      )      )
       snake_case       :				Union[str, Any]		    ={}





    @property
    def 	__snake_case  (							self							:							Any      ):



       '''simple docstring'''







       return len(self.encoder      )





    def 	__snake_case  (							self							:							str      ):



       '''simple docstring'''







       return dict(self.encoder,							**self.added_tokens_encoder      )





    def 	__snake_case  (							self							:							Tuple,							_snake_case							:							List[str]      ):



       '''simple docstring'''







       if token in self.cache:
          return self.cache[token]
       snake_case       :				str		    =re.sub('''([.,!?()])''',							r''' \1''',							SCREAMING_SNAKE_CASE__      )
       snake_case       :				List[Any]		    =re.sub('''(\')''',							r''' \1 ''',							SCREAMING_SNAKE_CASE__      )
       snake_case       :				Dict		    =re.sub(r'''\s{2,}''',							''' ''',							SCREAMING_SNAKE_CASE__      )
       if "\n" in token:
          snake_case       :				Tuple		    =token.replace('''\n''',							''' __newln__'''      )

       snake_case       :				List[Any]		    =token.split(''' '''      )
       snake_case       :				List[Any]		    =[]
       for token in tokens:
          if not len(SCREAMING_SNAKE_CASE__      ):
             continue

          snake_case       :				int		    =token.lower()
          snake_case       :				Tuple		    =tuple(SCREAMING_SNAKE_CASE__      )
          snake_case       :				Any		    =tuple(list(word[:-1]      ) + [word[-1] + '''</w>''']      )
          snake_case       :				Dict		    =get_pairs(SCREAMING_SNAKE_CASE__      )

          if not pairs:
             words.append(SCREAMING_SNAKE_CASE__      )
             continue

          while True:
             snake_case       :				List[str]		    =min(SCREAMING_SNAKE_CASE__,							key=lambda _snake_case      : self.bpe_ranks.get(SCREAMING_SNAKE_CASE__,							float('''inf'''      )      )      )
             if bigram not in self.bpe_ranks:
                break
             snake_case       :				Optional[Any]		    =bigram
             snake_case       :				str		    =[]
             snake_case       :				Optional[int]		    =0

             while i < len(SCREAMING_SNAKE_CASE__      ):
                try:
                   snake_case       :				List[str]		    =word.index(SCREAMING_SNAKE_CASE__,							SCREAMING_SNAKE_CASE__      )
                   new_word.extend(word[i:j]      )
                   snake_case       :				int		    =j
                except ValueError:
                   new_word.extend(word[i:]      )
                   break

                if word[i] == first and i < len(SCREAMING_SNAKE_CASE__      ) - 1 and word[i + 1] == second:
                   new_word.append(first + second      )
                   i += 2
                else:
                   new_word.append(word[i]      )
                   i += 1
             snake_case       :				Dict		    =tuple(SCREAMING_SNAKE_CASE__      )
             snake_case       :				Union[str, Any]		    =new_word
             if len(SCREAMING_SNAKE_CASE__      ) == 1:
                break
             else:
                snake_case       :				Dict		    =get_pairs(SCREAMING_SNAKE_CASE__      )
          snake_case       :				Tuple		    ='''@@ '''.join(SCREAMING_SNAKE_CASE__      )
          snake_case       :				Dict		    =word[:-4]

          snake_case       :				Any		    =word
          words.append(SCREAMING_SNAKE_CASE__      )
       return " ".join(SCREAMING_SNAKE_CASE__      )





    def 	__snake_case  (							self							:							Union[str, Any],							_snake_case							:							Any      ):



       '''simple docstring'''







       snake_case       :				int		    =[]

       snake_case       :				Dict		    =re.findall(r'''\S+\n?''',							SCREAMING_SNAKE_CASE__      )

       for token in words:
          split_tokens.extend(list(self.bpe(SCREAMING_SNAKE_CASE__      ).split(''' '''      )      )      )
       return split_tokens





    def 	__snake_case  (							self							:							List[str],							_snake_case							:							Any      ):



       '''simple docstring'''







       snake_case       :				List[Any]		    =token.lower()
       return self.encoder.get(SCREAMING_SNAKE_CASE__,							self.encoder.get(self.unk_token      )      )





    def 	__snake_case  (							self							:							Optional[int],							_snake_case							:							str      ):



       '''simple docstring'''







       return self.decoder.get(SCREAMING_SNAKE_CASE__,							self.unk_token      )





    def 	__snake_case  (							self							:							Any,							_snake_case							:							List[str]      ):



       '''simple docstring'''







       snake_case       :				int		    =''' '''.join(SCREAMING_SNAKE_CASE__      ).replace('''@@ ''',							''''''      ).strip()
       return out_string






    def 	__snake_case  (							self							:							List[Any],							_snake_case							:							Tuple,							_snake_case							:							Any = None      ):



       '''simple docstring'''







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

       with open(SCREAMING_SNAKE_CASE__,							'''w''',							encoding='''utf-8'''      ) as f:
          f.write(json.dumps(self.encoder,							indent=2,							sort_keys=SCREAMING_SNAKE_CASE__,							ensure_ascii=SCREAMING_SNAKE_CASE__      ) + '''\n'''      )

       snake_case       :				List[str]		    =0
       with open(SCREAMING_SNAKE_CASE__,							'''w''',							encoding='''utf-8'''      ) as writer:
          writer.write('''#version: 0.2\n'''      )
          for bpe_tokens, token_index in sorted(self.bpe_ranks.items(),							key=lambda _snake_case      : kv[1]      ):
             if index != token_index:
                logger.warning(
                    f'''Saving vocabulary to {merge_file}: BPE merge indices are not consecutive.'''
                    ''' Please check that the tokenizer is not corrupted!'''      )
                snake_case       :				Union[str, Any]		    =token_index
             writer.write(''' '''.join(SCREAMING_SNAKE_CASE__      ) + '''\n'''      )
             index += 1

       return vocab_file, merge_file









"""simple docstring"""






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


UpperCamelCase__				:str			   =	logging.get_logger(__name__)

UpperCamelCase__				:Optional[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(  lowerCamelCase__		):

		"""simple docstring"""





		A    =							"markuplm"
		def __init__( self					,				SCREAMING_SNAKE_CASE__=3_05_22					,				SCREAMING_SNAKE_CASE__=7_68					,				SCREAMING_SNAKE_CASE__=12					,				SCREAMING_SNAKE_CASE__=12					,				SCREAMING_SNAKE_CASE__=30_72					,				SCREAMING_SNAKE_CASE__="gelu"					,				SCREAMING_SNAKE_CASE__=0.1					,				SCREAMING_SNAKE_CASE__=0.1					,				SCREAMING_SNAKE_CASE__=5_12					,				SCREAMING_SNAKE_CASE__=2					,				SCREAMING_SNAKE_CASE__=0.0_2					,				SCREAMING_SNAKE_CASE__=1E-12					,				SCREAMING_SNAKE_CASE__=0					,				SCREAMING_SNAKE_CASE__=0					,				SCREAMING_SNAKE_CASE__=2					,				SCREAMING_SNAKE_CASE__=2_56					,				SCREAMING_SNAKE_CASE__=10_24					,				SCREAMING_SNAKE_CASE__=2_16					,				SCREAMING_SNAKE_CASE__=10_01					,				SCREAMING_SNAKE_CASE__=32					,				SCREAMING_SNAKE_CASE__=50					,				SCREAMING_SNAKE_CASE__="absolute"					,				SCREAMING_SNAKE_CASE__=True					,				SCREAMING_SNAKE_CASE__=None					,				**SCREAMING_SNAKE_CASE__					,				)      ->	Optional[Any]:

					"""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					:Any					     =	vocab_size
					_UpperCamelCase					:Union[str, Any]					     =	hidden_size
					_UpperCamelCase					:List[Any]					     =	num_hidden_layers
					_UpperCamelCase					:int					     =	num_attention_heads
					_UpperCamelCase					:Tuple					     =	hidden_act
					_UpperCamelCase					:str					     =	intermediate_size
					_UpperCamelCase					:Optional[int]					     =	hidden_dropout_prob
					_UpperCamelCase					:Any					     =	attention_probs_dropout_prob
					_UpperCamelCase					:Union[str, Any]					     =	max_position_embeddings
					_UpperCamelCase					:Dict					     =	type_vocab_size
					_UpperCamelCase					:int					     =	initializer_range
					_UpperCamelCase					:Optional[int]					     =	layer_norm_eps
					_UpperCamelCase					:Any					     =	position_embedding_type
					_UpperCamelCase					:Any					     =	use_cache
					_UpperCamelCase					:List[str]					     =	classifier_dropout
					# additional properties
					_UpperCamelCase					:Union[str, Any]					     =	max_depth
					_UpperCamelCase					:Union[str, Any]					     =	max_xpath_tag_unit_embeddings
					_UpperCamelCase					:Optional[Any]					     =	max_xpath_subs_unit_embeddings
					_UpperCamelCase					:int					     =	tag_pad_id
					_UpperCamelCase					:str					     =	subs_pad_id
					_UpperCamelCase					:List[str]					     =	xpath_unit_hidden_size

