



"""simple docstring"""

from string import ascii_uppercase

lowercase__					:						str												=			{char: i for i, char in enumerate(ascii_uppercase)}
lowercase__					:						List[Any]												=			dict(enumerate(ascii_uppercase))




def __lowercase    (							_a	,    _a					):
    snake_case_				:  List[str]       =			len(_a					)
    snake_case_				:  Dict       =			0
    while True:
        if x == i:
            snake_case_				:  Any       =			0
        if len(_a					) == len(_a					):
            break
        key += key[i]
        i += 1
    return key




def __lowercase    (							_a	,    _a					):
    snake_case_				:  Optional[int]       =			''''''
    snake_case_				:  List[Any]       =			0
    for letter in message:
        if letter == " ":
            cipher_text += " "
        else:
            snake_case_				:  Optional[int]       =			(dicta[letter] - dicta[key_new[i]]) % 26
            i += 1
            cipher_text += dicta[x]
    return cipher_text




def __lowercase    (							_a	,    _a					):
    snake_case_				:  Optional[Any]       =			''''''
    snake_case_				:  str       =			0
    for letter in cipher_text:
        if letter == " ":
            or_txt += " "
        else:
            snake_case_				:  str       =			(dicta[letter] + dicta[key_new[i]] + 26) % 26
            i += 1
            or_txt += dicta[x]
    return or_txt




def __lowercase    (							):
    snake_case_				:  List[Any]       =			'''THE GERMAN ATTACK'''
    snake_case_				:  Optional[int]       =			'''SECRET'''
    snake_case_				:  Optional[Any]       =			generate_key(_a	,    _a					)
    snake_case_				:  List[str]       =			cipher_text(_a	,    _a					)
    print(f"Encrypted Text = {s}"					)
    print(f"Original Text = {original_text(_a	,    _a					)}"					)


if __name__ == "__main__":
     import doctest

     doctest.testmod()
     main()










"""simple docstring"""

from dataclasses import dataclass
from enum import Enum
from typing import List, Optional, Union

import numpy as np
import PIL
from PIL import Image

from ...utils import BaseOutput, is_torch_available, is_transformers_available




@dataclass
class  _UpperCAmelCase (    lowerCAmelCase__):
 _lowerCAmelCase     :    Union[List[PIL.Image.Image], np.ndarray]
 _lowerCAmelCase     :    Optional[List[bool]]


if is_transformers_available() and is_torch_available():
     from .pipeline_semantic_stable_diffusion import SemanticStableDiffusionPipeline





