import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_layoutlm import LayoutLMTokenizer


UpperCAmelCase      		=					logging.get_logger(__name__)

UpperCAmelCase      		=					{'''vocab_file''': '''vocab.txt''', '''tokenizer_file''': '''tokenizer.json'''}

UpperCAmelCase      		=					{
    '''vocab_file''': {
        '''microsoft/layoutlm-base-uncased''': (
            '''https://huggingface.co/microsoft/layoutlm-base-uncased/resolve/main/vocab.txt'''
        ),
        '''microsoft/layoutlm-large-uncased''': (
            '''https://huggingface.co/microsoft/layoutlm-large-uncased/resolve/main/vocab.txt'''
        ),
    },
    '''tokenizer_file''': {
        '''microsoft/layoutlm-base-uncased''': (
            '''https://huggingface.co/microsoft/layoutlm-base-uncased/resolve/main/tokenizer.json'''
        ),
        '''microsoft/layoutlm-large-uncased''': (
            '''https://huggingface.co/microsoft/layoutlm-large-uncased/resolve/main/tokenizer.json'''
        ),
    },
}

UpperCAmelCase      		=					{
    '''microsoft/layoutlm-base-uncased''': 5_12,
    '''microsoft/layoutlm-large-uncased''': 5_12,
}

UpperCAmelCase      		=					{
    '''microsoft/layoutlm-base-uncased''': {'''do_lower_case''': True},
    '''microsoft/layoutlm-large-uncased''': {'''do_lower_case''': True},
}




class  __lowerCAmelCase	(							a_    ):



 '''simple docstring'''
 _lowerCamelCase    :						Tuple					     =			VOCAB_FILES_NAMES
 _lowerCamelCase    :						Tuple					     =			PRETRAINED_VOCAB_FILES_MAP
 _lowerCamelCase    :						Tuple					     =			PRETRAINED_INIT_CONFIGURATION
 _lowerCamelCase    :						Dict					     =			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 _lowerCamelCase    :						Dict					     =			LayoutLMTokenizer

 def __init__(      self							:		Dict							,      lowerCamelCase							:		Tuple=None							,      lowerCamelCase							:		Optional[int]=None							,      lowerCamelCase							:		Union[str, Any]=True							,      lowerCamelCase							:		Dict="[UNK]"							,      lowerCamelCase							:		Any="[SEP]"							,      lowerCamelCase							:		Optional[Any]="[PAD]"							,      lowerCamelCase							:		str="[CLS]"							,      lowerCamelCase							:		Any="[MASK]"							,      lowerCamelCase							:		Union[str, Any]=True							,      lowerCamelCase							:		Union[str, Any]=None							,      **lowerCamelCase							:		Optional[Any]							,      )			->				Dict:
        super().__init__(
            lowerCamelCase							,      tokenizer_file=lowerCamelCase							,      do_lower_case=lowerCamelCase							,      unk_token=lowerCamelCase							,      sep_token=lowerCamelCase							,      pad_token=lowerCamelCase							,      cls_token=lowerCamelCase							,      mask_token=lowerCamelCase							,      tokenize_chinese_chars=lowerCamelCase							,      strip_accents=lowerCamelCase							,      **lowerCamelCase							,      )

        _UpperCamelCase  :							Any	    =	json.loads(self.backend_tokenizer.normalizer.__getstate__()	)
        if (
            normalizer_state.get('lowercase'							,      lowerCamelCase	) != do_lower_case
            or normalizer_state.get('strip_accents'							,      lowerCamelCase	) != strip_accents
            or normalizer_state.get('handle_chinese_chars'							,      lowerCamelCase	) != tokenize_chinese_chars
        ):
               _UpperCamelCase  :							str	    =	getattr(lowerCamelCase							,      normalizer_state.pop('type'	)	)
               _UpperCamelCase  :							Optional[int]	    =	do_lower_case
               _UpperCamelCase  :							Tuple	    =	strip_accents
               _UpperCamelCase  :							int	    =	tokenize_chinese_chars
               _UpperCamelCase  :							Union[str, Any]	    =	normalizer_class(**lowerCamelCase	)

        _UpperCamelCase  :							Optional[int]	    =	do_lower_case

 def        __snake_case       (      self							:		Dict							,      lowerCamelCase							:		int							,      lowerCamelCase							:		List[Any]=None	)			->				str:
        _UpperCamelCase  :							Tuple	    =	[self.cls_token_id] + token_ids_a + [self.sep_token_id]

        if token_ids_a:
               output += token_ids_a + [self.sep_token_id]

        return output

 def        __snake_case       (      self							:		Optional[Any]							,      lowerCamelCase							:		List[int]							,      lowerCamelCase							:		Optional[List[int]] = None	)			->				List[int]:
        _UpperCamelCase  :							Union[str, Any]	    =	[self.sep_token_id]
        _UpperCamelCase  :							Dict	    =	[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	) * [0] + len(token_ids_a + sep	) * [1]

 def        __snake_case       (      self							:		List[str]							,      lowerCamelCase							:		str							,      lowerCamelCase							:		Optional[str] = None	)			->				Tuple[str]:
        _UpperCamelCase  :							int	    =	self._tokenizer.model.save(lowerCamelCase							,      name=lowerCamelCase	)
        return tuple(lowerCamelCase	)




from .number_theory.prime_numbers import next_prime




class  __lowerCAmelCase	:



 '''simple docstring'''

 def __init__(      self							:		List[Any]							,      lowerCamelCase							:		int							,      lowerCamelCase							:		int | None = None							,      lowerCamelCase							:		float | None = None							,      )			->				None:
        _UpperCamelCase  :							Tuple	    =	size_table
        _UpperCamelCase  :							Tuple	    =	[None] * self.size_table
        _UpperCamelCase  :							int	    =	0.7_5 if lim_charge is None else lim_charge
        _UpperCamelCase  :							Tuple	    =	1 if charge_factor is None else charge_factor
        _UpperCamelCase  :							list	    =	[]
        _UpperCamelCase  :							dict	    =	{}

 def        __snake_case       (      self							:		List[Any]	)			->				Union[str, Any]:
        return self._keys

 def        __snake_case       (      self							:		List[Any]	)			->				Optional[int]:
        return sum(1 for slot in self.values if slot is not None	) / (
            self.size_table * self.charge_factor
        )

 def        __snake_case       (      self							:		Union[str, Any]							,      lowerCamelCase							:		int	)			->				Any:
        return key % self.size_table

 def        __snake_case       (      self							:		Any							,      lowerCamelCase							:		Any	)			->				Optional[Any]:
        print(f"step {step_ord}"	)
        print(list(range(len(self.values	)	)	)	)
        print(self.values	)

 def        __snake_case       (      self							:		Tuple							,      lowerCamelCase							:		Optional[int]	)			->				Any:
        _UpperCamelCase  :							int	    =	1
        _UpperCamelCase  :							Union[str, Any]	    =	values
        for value in values:
               self.insert_data(lowerCamelCase	)
               self._step_by_step(lowerCamelCase	)
               i += 1

 def        __snake_case       (      self							:		Optional[Any]							,      lowerCamelCase							:		Any							,      lowerCamelCase							:		Optional[int]	)			->				Any:
        _UpperCamelCase  :							int	    =	data
        _UpperCamelCase  :							Optional[int]	    =	data

 def        __snake_case       (      self							:		Optional[int]							,      lowerCamelCase							:		Optional[int]							,      lowerCamelCase							:		str=None	)			->				List[Any]:
        _UpperCamelCase  :							Union[str, Any]	    =	self.hash_function(key + 1	)

        while self.values[new_key] is not None and self.values[new_key] != key:
               if self.values.count(lowerCamelCase	) > 0:
                      _UpperCamelCase  :							Optional[int]	    =	self.hash_function(new_key + 1	)
               else:
                      _UpperCamelCase  :							Tuple	    =	None
                      break

        return new_key

 def        __snake_case       (      self							:		Optional[Any]	)			->				Optional[Any]:
        _UpperCamelCase  :							Union[str, Any]	    =	[value for value in self.values if value is not None]
        _UpperCamelCase  :							Union[str, Any]	    =	next_prime(self.size_table							,      factor=2	)
        self._keys.clear()
        _UpperCamelCase  :							Tuple	    =	[None] * self.size_table  # hell's pointers D: don't DRY ;/
        for value in survivor_values:
               self.insert_data(lowerCamelCase	)

 def        __snake_case       (      self							:		Tuple							,      lowerCamelCase							:		str	)			->				Union[str, Any]:
        _UpperCamelCase  :							Dict	    =	self.hash_function(lowerCamelCase	)

        if self.values[key] is None:
               self._set_value(lowerCamelCase							,      lowerCamelCase	)

        elif self.values[key] == data:
               pass

        else:
               _UpperCamelCase  :							Tuple	    =	self._collision_resolution(lowerCamelCase							,      lowerCamelCase	)
               if collision_resolution is not None:
                      self._set_value(lowerCamelCase							,      lowerCamelCase	)
               else:
                      self.rehashing()
                      self.insert_data(lowerCamelCase	)



