



'''simple docstring'''

import string



def      __lowerCamelCase     (      lowerCAmelCase_  )			->      None:
		for key in range(len(string.ascii_uppercase  )  ):
				_a     :      Union[str, Any]        =							''
				for symbol in message:
						if symbol in string.ascii_uppercase:
								_a     :      Optional[Any]        =							string.ascii_uppercase.find(lowerCAmelCase_  )
								_a     :      List[str]        =							num - key
								if num < 0:
										_a     :      str        =							num + len(string.ascii_uppercase  )
								_a     :      int        =							translated + string.ascii_uppercase[num]
						else:
								_a     :      Dict        =							translated + symbol
				print(f"""Decryption using Key #{key}: {translated}"""  )



def      __lowerCamelCase     (      )			->      None:
		_a     :      int        =							input('Encrypted message: '  )
		_a     :      Tuple        =							message.upper()
		decrypt(lowerCAmelCase_  )


if __name__ == "__main__":
							import doctest

							doctest.testmod()
							main()












"""simple docstring"""



import unittest

from transformers import load_tool

from .test_tools_common import ToolTesterMixin


__A		:       Dict  				=		'''
Hugging Face was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf originally as a company that developed a chatbot app targeted at teenagers.[2] After open-sourcing the model behind the chatbot, the company pivoted to focus on being a platform for machine learning.

In March 2021, Hugging Face raised $40 million in a Series B funding round.[3]

On April 28, 2021, the company launched the BigScience Research Workshop in collaboration with several other research groups to release an open large language model.[4] In 2022, the workshop concluded with the announcement of BLOOM, a multilingual large language model with 176 billion parameters.[5]
'''





class 					_UpperCAmelCase       ( unittest.TestCase   ,						_A							):




					def   A  (				self     :						List[Any]   )  ->  Dict:
							lowercase_ : Optional[int]							       =   load_tool('''text-question-answering'''   )
							self.tool.setup()
							lowercase_ : Union[str, Any]							       =   load_tool('''text-question-answering'''    ,						remote=A   )




					def   A  (				self     :						Any   )  ->  List[str]:
							lowercase_ : Union[str, Any]							       =   self.tool(A    ,						'''What did Hugging Face do in April 2021?'''   )
							self.assertEqual(A    ,						'''launched the BigScience Research Workshop'''   )




					def   A  (				self     :						str   )  ->  List[str]:
							lowercase_ : int							       =   self.remote_tool(A    ,						'''What did Hugging Face do in April 2021?'''   )
							self.assertEqual(A    ,						'''launched the BigScience Research Workshop'''   )




					def   A  (				self     :						List[Any]   )  ->  int:
							lowercase_ : Optional[Any]							       =   self.tool(text=A    ,						question='''What did Hugging Face do in April 2021?'''   )
							self.assertEqual(A    ,						'''launched the BigScience Research Workshop'''   )






					def   A  (				self     :						List[str]   )  ->  Optional[int]:
							lowercase_ : int							       =   self.remote_tool(text=A    ,						question='''What did Hugging Face do in April 2021?'''   )
							self.assertEqual(A    ,						'''launched the BigScience Research Workshop'''   )



