

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


__A	:   List[str]	=					logging.get_logger(__name__)

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

__A	:   List[str]	=					{
    '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'
        ),
    },
}

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

__A	:   Optional[int]	=					{
    'microsoft/layoutlm-base-uncased': {'do_lower_case': True},
    'microsoft/layoutlm-large-uncased': {'do_lower_case': True},
}


class 			_SCREAMING_SNAKE_CASE      (  lowerCAmelCase__):
						_UpperCamelCase:str	=		VOCAB_FILES_NAMES
						_UpperCamelCase:Optional[Any]	=		PRETRAINED_VOCAB_FILES_MAP
						_UpperCamelCase:Optional[int]	=		PRETRAINED_INIT_CONFIGURATION
						_UpperCamelCase:Tuple	=		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
						_UpperCamelCase:List[str]	=		LayoutLMTokenizer







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

													lowerCamelCase_								=json.loads(self.backend_tokenizer.normalizer.__getstate__()							)
													if (
													    normalizer_state.get("""lowercase"""     ,						_SCREAMING_SNAKE_CASE							) != do_lower_case
													    or normalizer_state.get("""strip_accents"""     ,						_SCREAMING_SNAKE_CASE							) != strip_accents
													    or normalizer_state.get("""handle_chinese_chars"""     ,						_SCREAMING_SNAKE_CASE							) != tokenize_chinese_chars
													):
																				lowerCamelCase_								=getattr(_SCREAMING_SNAKE_CASE     ,						normalizer_state.pop("""type"""							)							)
																				lowerCamelCase_								=do_lower_case
																				lowerCamelCase_								=strip_accents
																				lowerCamelCase_								=tokenize_chinese_chars
																				lowerCamelCase_								=normalizer_class(**_SCREAMING_SNAKE_CASE							)

													lowerCamelCase_								=do_lower_case







						def        _snake_case				(			self     ,						_SCREAMING_SNAKE_CASE     ,						_SCREAMING_SNAKE_CASE=None							)->							Any:
													lowerCamelCase_								=[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     ,						_SCREAMING_SNAKE_CASE     ,						_SCREAMING_SNAKE_CASE = None							)->							List[int]:
													lowerCamelCase_								=[self.sep_token_id]
													lowerCamelCase_								=[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     ,						_SCREAMING_SNAKE_CASE     ,						_SCREAMING_SNAKE_CASE = None							)->							Tuple[str]:
													lowerCamelCase_								=self._tokenizer.model.save(_SCREAMING_SNAKE_CASE     ,						name=_SCREAMING_SNAKE_CASE							)
													return tuple(_SCREAMING_SNAKE_CASE							)



from __future__ import annotations




def        __UpperCamelCase     (      _A					:							int      ,  _A					:							list[int]      ,  _A					:							list[int]      ,  _A					:							int		)				->int:



							"""simple docstring"""

							# Base Case
							if counter == 0 or capacity == 0:
														return 0

							# If weight of the nth item is more than Knapsack of capacity,
							#   then this item cannot be included in the optimal solution,
							# else return the maximum of two cases:
							#   (1) nth item included
							#   (2) not included
							if weights[counter - 1] > capacity:
														return knapsack(_A      ,  _A      ,  _A      ,  counter - 1		)
							else:
														lowerCamelCase_								=capacity - weights[counter - 1]
														lowerCamelCase_								=values[counter - 1] + knapsack(
														    _A      ,  _A      ,  _A      ,  counter - 1		)
														lowerCamelCase_								=knapsack(_A      ,  _A      ,  _A      ,  counter - 1		)
														return max(_A      ,  _A		)


if __name__ == "__main__":
	import doctest

	doctest.testmod()
