






from __future__ import annotations

A__			:    Tuple         =				tuple[int, int, int]
A__			:    List[str]         =				tuple[str, str, str]


# used alphabet --------------------------
# from string.ascii_uppercase
A__			:    Union[str, Any]         =				'ABCDEFGHIJKLMNOPQRSTUVWXYZ'

# -------------------------- default selection --------------------------
# rotors --------------------------
A__			:    List[str]         =				'EGZWVONAHDCLFQMSIPJBYUKXTR'
A__			:    List[Any]         =				'FOBHMDKEXQNRAULPGSJVTYICZW'
A__			:    Any         =				'ZJXESIUQLHAVRMDOYGTNFWPBKC'
# reflector --------------------------
A__			:    Optional[Any]         =				{
    'A': 'N',
    'N': 'A',
    'B': 'O',
    'O': 'B',
    'C': 'P',
    'P': 'C',
    'D': 'Q',
    'Q': 'D',
    'E': 'R',
    'R': 'E',
    'F': 'S',
    'S': 'F',
    'G': 'T',
    'T': 'G',
    'H': 'U',
    'U': 'H',
    'I': 'V',
    'V': 'I',
    'J': 'W',
    'W': 'J',
    'K': 'X',
    'X': 'K',
    'L': 'Y',
    'Y': 'L',
    'M': 'Z',
    'Z': 'M',
}

# -------------------------- extra rotors --------------------------
A__			:    Optional[Any]         =				'RMDJXFUWGISLHVTCQNKYPBEZOA'
A__			:    Any         =				'SGLCPQWZHKXAREONTFBVIYJUDM'
A__			:    Dict         =				'HVSICLTYKQUBXDWAJZOMFGPREN'
A__			:    List[Any]         =				'RZWQHFMVDBKICJLNTUXAGYPSOE'
A__			:    Any         =				'LFKIJODBEGAMQPXVUHYSTCZRWN'
A__			:    str         =				'KOAEGVDHXPQZMLFTYWJNBRCIUS'






def 						a    (		lowerCamelCase_	,     lowerCamelCase_	,     lowerCamelCase_       ):






				'''simple docstring'''
				# Checks if there are 3 unique rotors

				if (unique_rotsel := len(set(lowerCamelCase_       )       )) < 3:
								lowercase__     				=    F"""Please use 3 unique rotors (not {unique_rotsel})"""
								raise Exception(lowerCamelCase_       )

				# Checks if rotor positions are valid
				lowercase__				,		lowercase__				,		lowercase__     				=    rotpos
				if not 0 < rotorposa <= len(lowerCamelCase_       ):
								lowercase__     				=    F"""First rotor position is not within range of 1..26 ({rotorposa}"""
								raise ValueError(lowerCamelCase_       )
				if not 0 < rotorposa <= len(lowerCamelCase_       ):
								lowercase__     				=    F"""Second rotor position is not within range of 1..26 ({rotorposa})"""
								raise ValueError(lowerCamelCase_       )
				if not 0 < rotorposa <= len(lowerCamelCase_       ):
								lowercase__     				=    F"""Third rotor position is not within range of 1..26 ({rotorposa})"""
								raise ValueError(lowerCamelCase_       )

				# Validates string and returns dict
				lowercase__     				=    _plugboard(lowerCamelCase_       )

				return rotpos, rotsel, pbdict






def 						a    (		lowerCamelCase_       ):






				'''simple docstring'''

				# tests the input string if it
				# a) is type string
				# b) has even length (so pairs can be made)
				if not isinstance(lowerCamelCase_	,     lowerCamelCase_       ):
								lowercase__     				=    F"""Plugboard setting isn't type string ({type(lowerCamelCase_       )})"""
								raise TypeError(lowerCamelCase_       )
				elif len(lowerCamelCase_       ) % 2 != 0:
								lowercase__     				=    F"""Odd number of symbols ({len(lowerCamelCase_       )})"""
								raise Exception(lowerCamelCase_       )
				elif pbstring == "":
								return {}

				pbstring.replace(''' '''	,     ''''''       )

				# Checks if all characters are unique
				lowercase__     				=    set()
				for i in pbstring:
								if i not in abc:
												lowercase__     				=    F"""'{i}' not in list of symbols"""
												raise Exception(lowerCamelCase_       )
								elif i in tmppbl:
												lowercase__     				=    F"""Duplicate symbol ({i})"""
												raise Exception(lowerCamelCase_       )
								else:
												tmppbl.add(lowerCamelCase_       )
				del tmppbl

				# Created the dictionary
				lowercase__     				=    {}
				for j in range(0	,     len(lowerCamelCase_       ) - 1	,     2       ):
								lowercase__     				=    pbstring[j + 1]
								lowercase__     				=    pbstring[j]

				return pb






def 						a    (		lowerCamelCase_	,     lowerCamelCase_	,     lowerCamelCase_ = (rotora, rotora, rotora)	,     lowerCamelCase_ = ""	,     ):






				'''simple docstring'''
				lowercase__     				=    text.upper()
				lowercase__				,		lowercase__				,		lowercase__     				=    _validator(
				    lowerCamelCase_	,     lowerCamelCase_	,     plugb.upper()       )

				lowercase__				,		lowercase__				,		lowercase__     				=    rotor_position
				lowercase__				,		lowercase__				,		lowercase__     				=    rotor_selection
				rotorposa -= 1
				rotorposa -= 1
				rotorposa -= 1

				lowercase__     				=    []

				# encryption/decryption process --------------------------
				for symbol in text:
								if symbol in abc:
												# 1st plugboard --------------------------
												if symbol in plugboard:
																lowercase__     				=    plugboard[symbol]

												# rotor ra --------------------------
												lowercase__     				=    abc.index(lowerCamelCase_       ) + rotorposa
												lowercase__     				=    rotora[index % len(lowerCamelCase_       )]

												# rotor rb --------------------------
												lowercase__     				=    abc.index(lowerCamelCase_       ) + rotorposa
												lowercase__     				=    rotora[index % len(lowerCamelCase_       )]

												# rotor rc --------------------------
												lowercase__     				=    abc.index(lowerCamelCase_       ) + rotorposa
												lowercase__     				=    rotora[index % len(lowerCamelCase_       )]

												# reflector --------------------------
												# this is the reason you don't need another machine to decipher

												lowercase__     				=    reflector[symbol]

												# 2nd rotors
												lowercase__     				=    abc[rotora.index(lowerCamelCase_       ) - rotorposa]
												lowercase__     				=    abc[rotora.index(lowerCamelCase_       ) - rotorposa]
												lowercase__     				=    abc[rotora.index(lowerCamelCase_       ) - rotorposa]

												# 2nd plugboard
												if symbol in plugboard:
																lowercase__     				=    plugboard[symbol]

												# moves/resets rotor positions
												rotorposa += 1
												if rotorposa >= len(lowerCamelCase_       ):
																lowercase__     				=    0
																rotorposa += 1
												if rotorposa >= len(lowerCamelCase_       ):
																lowercase__     				=    0
																rotorposa += 1
												if rotorposa >= len(lowerCamelCase_       ):
																lowercase__     				=    0

        # else:
        #    pass
        #    Error could be also raised
        #    raise ValueError(
        #       'Invalid symbol('+repr(symbol)+')')
								result.append(lowerCamelCase_       )

				return "".join(lowerCamelCase_       )


if __name__ == "__main__":
							A__			:    Tuple         =				'This is my Python script that emulates the Enigma machine from WWII.'
							A__			:    Dict         =				(1, 1, 1)
							A__			:    Optional[int]         =				'pictures'
							A__			:    Dict         =				(rotora, rotora, rotora)
							A__			:    Union[str, Any]         =				enigma(message, rotor_pos, rotor_sel, pb)

							print('Encrypted message:', en)
							print('Decrypted message:', enigma(en, rotor_pos, rotor_sel, pb))












import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_bert import BertTokenizer


A__			:    Dict         =				logging.get_logger(__name__)

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

A__			:    Optional[int]         =				{
    'vocab_file': {
        'bert-base-uncased': 'https://huggingface.co/bert-base-uncased/resolve/main/vocab.txt',
        'bert-large-uncased': 'https://huggingface.co/bert-large-uncased/resolve/main/vocab.txt',
        'bert-base-cased': 'https://huggingface.co/bert-base-cased/resolve/main/vocab.txt',
        'bert-large-cased': 'https://huggingface.co/bert-large-cased/resolve/main/vocab.txt',
        'bert-base-multilingual-uncased': (
            'https://huggingface.co/bert-base-multilingual-uncased/resolve/main/vocab.txt'
        ),
        'bert-base-multilingual-cased': 'https://huggingface.co/bert-base-multilingual-cased/resolve/main/vocab.txt',
        'bert-base-chinese': 'https://huggingface.co/bert-base-chinese/resolve/main/vocab.txt',
        'bert-base-german-cased': 'https://huggingface.co/bert-base-german-cased/resolve/main/vocab.txt',
        'bert-large-uncased-whole-word-masking': (
            'https://huggingface.co/bert-large-uncased-whole-word-masking/resolve/main/vocab.txt'
        ),
        'bert-large-cased-whole-word-masking': (
            'https://huggingface.co/bert-large-cased-whole-word-masking/resolve/main/vocab.txt'
        ),
        'bert-large-uncased-whole-word-masking-finetuned-squad': (
            'https://huggingface.co/bert-large-uncased-whole-word-masking-finetuned-squad/resolve/main/vocab.txt'
        ),
        'bert-large-cased-whole-word-masking-finetuned-squad': (
            'https://huggingface.co/bert-large-cased-whole-word-masking-finetuned-squad/resolve/main/vocab.txt'
        ),
        'bert-base-cased-finetuned-mrpc': (
            'https://huggingface.co/bert-base-cased-finetuned-mrpc/resolve/main/vocab.txt'
        ),
        'bert-base-german-dbmdz-cased': 'https://huggingface.co/bert-base-german-dbmdz-cased/resolve/main/vocab.txt',
        'bert-base-german-dbmdz-uncased': (
            'https://huggingface.co/bert-base-german-dbmdz-uncased/resolve/main/vocab.txt'
        ),
        'TurkuNLP/bert-base-finnish-cased-v1': (
            'https://huggingface.co/TurkuNLP/bert-base-finnish-cased-v1/resolve/main/vocab.txt'
        ),
        'TurkuNLP/bert-base-finnish-uncased-v1': (
            'https://huggingface.co/TurkuNLP/bert-base-finnish-uncased-v1/resolve/main/vocab.txt'
        ),
        'wietsedv/bert-base-dutch-cased': (
            'https://huggingface.co/wietsedv/bert-base-dutch-cased/resolve/main/vocab.txt'
        ),
    },
    'tokenizer_file': {
        'bert-base-uncased': 'https://huggingface.co/bert-base-uncased/resolve/main/tokenizer.json',
        'bert-large-uncased': 'https://huggingface.co/bert-large-uncased/resolve/main/tokenizer.json',
        'bert-base-cased': 'https://huggingface.co/bert-base-cased/resolve/main/tokenizer.json',
        'bert-large-cased': 'https://huggingface.co/bert-large-cased/resolve/main/tokenizer.json',
        'bert-base-multilingual-uncased': (
            'https://huggingface.co/bert-base-multilingual-uncased/resolve/main/tokenizer.json'
        ),
        'bert-base-multilingual-cased': (
            'https://huggingface.co/bert-base-multilingual-cased/resolve/main/tokenizer.json'
        ),
        'bert-base-chinese': 'https://huggingface.co/bert-base-chinese/resolve/main/tokenizer.json',
        'bert-base-german-cased': 'https://huggingface.co/bert-base-german-cased/resolve/main/tokenizer.json',
        'bert-large-uncased-whole-word-masking': (
            'https://huggingface.co/bert-large-uncased-whole-word-masking/resolve/main/tokenizer.json'
        ),
        'bert-large-cased-whole-word-masking': (
            'https://huggingface.co/bert-large-cased-whole-word-masking/resolve/main/tokenizer.json'
        ),
        'bert-large-uncased-whole-word-masking-finetuned-squad': (
            'https://huggingface.co/bert-large-uncased-whole-word-masking-finetuned-squad/resolve/main/tokenizer.json'
        ),
        'bert-large-cased-whole-word-masking-finetuned-squad': (
            'https://huggingface.co/bert-large-cased-whole-word-masking-finetuned-squad/resolve/main/tokenizer.json'
        ),
        'bert-base-cased-finetuned-mrpc': (
            'https://huggingface.co/bert-base-cased-finetuned-mrpc/resolve/main/tokenizer.json'
        ),
        'bert-base-german-dbmdz-cased': (
            'https://huggingface.co/bert-base-german-dbmdz-cased/resolve/main/tokenizer.json'
        ),
        'bert-base-german-dbmdz-uncased': (
            'https://huggingface.co/bert-base-german-dbmdz-uncased/resolve/main/tokenizer.json'
        ),
        'TurkuNLP/bert-base-finnish-cased-v1': (
            'https://huggingface.co/TurkuNLP/bert-base-finnish-cased-v1/resolve/main/tokenizer.json'
        ),
        'TurkuNLP/bert-base-finnish-uncased-v1': (
            'https://huggingface.co/TurkuNLP/bert-base-finnish-uncased-v1/resolve/main/tokenizer.json'
        ),
        'wietsedv/bert-base-dutch-cased': (
            'https://huggingface.co/wietsedv/bert-base-dutch-cased/resolve/main/tokenizer.json'
        ),
    },
}

A__			:    List[str]         =				{
    'bert-base-uncased': 5_12,
    'bert-large-uncased': 5_12,
    'bert-base-cased': 5_12,
    'bert-large-cased': 5_12,
    'bert-base-multilingual-uncased': 5_12,
    'bert-base-multilingual-cased': 5_12,
    'bert-base-chinese': 5_12,
    'bert-base-german-cased': 5_12,
    'bert-large-uncased-whole-word-masking': 5_12,
    'bert-large-cased-whole-word-masking': 5_12,
    'bert-large-uncased-whole-word-masking-finetuned-squad': 5_12,
    'bert-large-cased-whole-word-masking-finetuned-squad': 5_12,
    'bert-base-cased-finetuned-mrpc': 5_12,
    'bert-base-german-dbmdz-cased': 5_12,
    'bert-base-german-dbmdz-uncased': 5_12,
    'TurkuNLP/bert-base-finnish-cased-v1': 5_12,
    'TurkuNLP/bert-base-finnish-uncased-v1': 5_12,
    'wietsedv/bert-base-dutch-cased': 5_12,
}

A__			:    Optional[int]         =				{
    'bert-base-uncased': {'do_lower_case': True},
    'bert-large-uncased': {'do_lower_case': True},
    'bert-base-cased': {'do_lower_case': False},
    'bert-large-cased': {'do_lower_case': False},
    'bert-base-multilingual-uncased': {'do_lower_case': True},
    'bert-base-multilingual-cased': {'do_lower_case': False},
    'bert-base-chinese': {'do_lower_case': False},
    'bert-base-german-cased': {'do_lower_case': False},
    'bert-large-uncased-whole-word-masking': {'do_lower_case': True},
    'bert-large-cased-whole-word-masking': {'do_lower_case': False},
    'bert-large-uncased-whole-word-masking-finetuned-squad': {'do_lower_case': True},
    'bert-large-cased-whole-word-masking-finetuned-squad': {'do_lower_case': False},
    'bert-base-cased-finetuned-mrpc': {'do_lower_case': False},
    'bert-base-german-dbmdz-cased': {'do_lower_case': False},
    'bert-base-german-dbmdz-uncased': {'do_lower_case': True},
    'TurkuNLP/bert-base-finnish-cased-v1': {'do_lower_case': False},
    'TurkuNLP/bert-base-finnish-uncased-v1': {'do_lower_case': True},
    'wietsedv/bert-base-dutch-cased': {'do_lower_case': False},
}
class    _UpperCAmelCase      ( A__			):

				"""simple docstring"""




				lowercase__       							= VOCAB_FILES_NAMES
				lowercase__       							= PRETRAINED_VOCAB_FILES_MAP
				lowercase__       							= PRETRAINED_INIT_CONFIGURATION
				lowercase__       							= PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				lowercase__       							= BertTokenizer




				def __init__(  self		:					Any,						lowerCamelCase		:					Optional[Any]=None,						lowerCamelCase		:					Any=None,						lowerCamelCase		:					Tuple=True,						lowerCamelCase		:					Dict="[UNK]",						lowerCamelCase		:					Any="[SEP]",						lowerCamelCase		:					List[Any]="[PAD]",						lowerCamelCase		:					Optional[Any]="[CLS]",						lowerCamelCase		:					Dict="[MASK]",						lowerCamelCase		:					List[Any]=True,						lowerCamelCase		:					Tuple=None,						**lowerCamelCase		:					Dict,						):

								'''simple docstring'''
								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,						)

								lowercase__     				=    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
								):
												lowercase__     				=    getattr(lowerCamelCase,						normalizer_state.pop('''type'''						)						)
												lowercase__     				=    do_lower_case
												lowercase__     				=    strip_accents
												lowercase__     				=    tokenize_chinese_chars
												lowercase__     				=    normalizer_class(**lowerCamelCase						)

								lowercase__     				=    do_lower_case




				def        lowercase__     (  self		:					Any,						lowerCamelCase		:					List[Any],						lowerCamelCase		:					Dict=None						):

								'''simple docstring'''
								lowercase__     				=    [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        lowercase__     (  self		:					List[Any],						lowerCamelCase		:					List[int],						lowerCamelCase		:					Optional[List[int]] = None						):

								'''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						) * [0] + len(token_ids_a + sep						) * [1]




				def        lowercase__     (  self		:					Any,						lowerCamelCase		:					str,						lowerCamelCase		:					Optional[str] = None						):

								'''simple docstring'''
								lowercase__     				=    self._tokenizer.model.save(lowerCamelCase,						name=lowerCamelCase						)
								return tuple(lowerCamelCase						)




