


from typing import Literal

lowerCAmelCase					 =	'''ABCDEFGHIJKLMNOPQRSTUVWXYZ'''







def  _lowerCamelCase(			lowercase__     ,				lowercase__     ,				lowercase__			)		->			str:

		'''simple docstring'''







		__lowercase=    LETTERS if mode == 'decrypt' else key
		__lowercase=    key if mode == 'decrypt' else LETTERS
		__lowercase=    ''
		# loop through each symbol in the message
		for symbol in message:
				if symbol.upper() in chars_a:
						# encrypt/decrypt the symbol
						__lowercase=    chars_a.find(symbol.upper()			)
						if symbol.isupper():
								translated += chars_b[sym_index].upper()
						else:
								translated += chars_b[sym_index].lower()
				else:
						# symbol is not in LETTERS, just add it
						translated += symbol
		return translated







def  _lowerCamelCase(			lowercase__     ,				lowercase__			)		->			str:

		'''simple docstring'''







		return translate_message(lowercase__     ,				lowercase__     ,				'encrypt'			)







def  _lowerCamelCase(			lowercase__     ,				lowercase__			)		->			str:

		'''simple docstring'''







		return translate_message(lowercase__     ,				lowercase__     ,				'decrypt'			)







def  _lowerCamelCase(			)		->			None:

		'''simple docstring'''







		__lowercase=    'Hello World'
		__lowercase=    'QWERTYUIOPASDFGHJKLZXCVBNM'
		__lowercase=    'decrypt'  # set to 'encrypt' or 'decrypt'

		if mode == "encrypt":
				__lowercase=    encrypt_message(lowercase__     ,				lowercase__			)
		elif mode == "decrypt":
				__lowercase=    decrypt_message(lowercase__     ,				lowercase__			)
		print(F'Using the key {key}, the {mode}ed message is: {translated}'			)


if __name__ == "__main__":
	import doctest

	doctest.testmod()
	main()










from dataclasses import dataclass
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
# Copied from diffusers.pipelines.stable_diffusion.__init__.StableDiffusionPipelineOutput with Stable->Alt
class    A					(     A_				):
							UpperCamelCase_     :							Union[List[PIL.Image.Image], np.ndarray]
							UpperCamelCase_     :							Optional[List[bool]]


if is_transformers_available() and is_torch_available():
	from .modeling_roberta_series import RobertaSeriesModelWithTransformation
	from .pipeline_alt_diffusion import AltDiffusionPipeline
	from .pipeline_alt_diffusion_imgaimg import AltDiffusionImgaImgPipeline






