"""simple docstring"""






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   UpperCAmelCase__				(    __lowerCamelCase			):


	"""simple docstring"""
	lowerCAmelCase__    :					Any						      =							VOCAB_FILES_NAMES
	lowerCAmelCase__    :					str						      =							PRETRAINED_VOCAB_FILES_MAP
	lowerCAmelCase__    :					List[Any]						      =							PRETRAINED_INIT_CONFIGURATION
	lowerCAmelCase__    :					Any						      =							PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
	lowerCAmelCase__    :					int						      =							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       ,     )

							a_							:			Any     		=					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
							):
													a_							:			Dict     		=					getattr(_SCREAMING_SNAKE_CASE       ,     normalizer_state.pop("type" ) )
													a_							:			Optional[Any]     		=					do_lower_case
													a_							:			str     		=					strip_accents
													a_							:			Union[str, Any]     		=					tokenize_chinese_chars
													a_							:			List[str]     		=					normalizer_class(**_SCREAMING_SNAKE_CASE )

							a_							:			Optional[Any]     		=					do_lower_case







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





"""simple docstring"""






import numpy as np

UpperCamelCase     					=     [
    ['a', 'b', 'c', 'd', 'e'],
    ['f', 'g', 'h', 'i', 'k'],
    ['l', 'm', 'n', 'o', 'p'],
    ['q', 'r', 's', 't', 'u'],
    ['v', 'w', 'x', 'y', 'z'],
]
class   UpperCAmelCase__				:


	"""simple docstring"""







	def __init__(			self )    ->	None:
							a_							:			List[Any]     		=					np.array(_SCREAMING_SNAKE_CASE )







	def       A    (			self       ,     _SCREAMING_SNAKE_CASE )    ->	np.ndarray:
							a_		,					a_							:			List[str]     		=					np.where(letter == self.SQUARE )
							a_							:			Union[str, Any]     		=					np.concatenate([indexa + 1, indexa + 1] )
							return indexes







	def       A    (			self       ,     _SCREAMING_SNAKE_CASE       ,     _SCREAMING_SNAKE_CASE )    ->	str:
							return self.SQUARE[indexa - 1, indexa - 1]







	def       A    (			self       ,     _SCREAMING_SNAKE_CASE )    ->	str:
							a_							:			List[str]     		=					message.lower()
							a_							:			Union[str, Any]     		=					message.replace("j"       ,     "i" )

							a_							:			Tuple     		=					""
							for letter_index in range(len(_SCREAMING_SNAKE_CASE ) ):
													if message[letter_index] != " ":
																			a_							:			Dict     		=					self.letter_to_numbers(message[letter_index] )
																			a_							:			str     		=					encoded_message + str(numbers[0] ) + str(numbers[1] )
													elif message[letter_index] == " ":
																			a_							:			Any     		=					encoded_message + " "

							return encoded_message







	def       A    (			self       ,     _SCREAMING_SNAKE_CASE )    ->	str:
							a_							:			Dict     		=					message.replace(" "       ,     "  " )
							a_							:			str     		=					""
							for numbers_index in range(int(len(_SCREAMING_SNAKE_CASE ) / 2 ) ):
													if message[numbers_index * 2] != " ":
																			a_							:			str     		=					message[numbers_index * 2]
																			a_							:			str     		=					message[numbers_index * 2 + 1]

																			a_							:			Optional[Any]     		=					self.numbers_to_letter(int(_SCREAMING_SNAKE_CASE )       ,     int(_SCREAMING_SNAKE_CASE ) )
																			a_							:			Optional[Any]     		=					decoded_message + letter
													elif message[numbers_index * 2] == " ":
																			a_							:			str     		=					decoded_message + " "

							return decoded_message




