



'''simple docstring'''

UpperCAmelCase     		=   'ABCDEFGHIJKLMNOPQRSTUVWXYZ'






def 		_snake_case		( )      ->						None:







	"""simple docstring"""
	lowerCAmelCase   =     input("""Enter message: """							)
	lowerCAmelCase   =     input("""Enter key [alphanumeric]: """							)
	lowerCAmelCase   =     input("""Encrypt/Decrypt [e/d]: """							)

	if mode.lower().startswith("""e"""							):
		lowerCAmelCase   =     """encrypt"""
		lowerCAmelCase   =     encrypt_message(_SCREAMING_SNAKE_CASE							,		_SCREAMING_SNAKE_CASE							)
	elif mode.lower().startswith("""d"""							):
		lowerCAmelCase   =     """decrypt"""
		lowerCAmelCase   =     decrypt_message(_SCREAMING_SNAKE_CASE							,		_SCREAMING_SNAKE_CASE							)

	print(f'\n{mode.title()}ed message:'							)
	print(_SCREAMING_SNAKE_CASE							)






def 		_snake_case		( _SCREAMING_SNAKE_CASE					:						str							,		_SCREAMING_SNAKE_CASE					:						str							)      ->						str:







	"""simple docstring"""
	return translate_message(_SCREAMING_SNAKE_CASE							,		_SCREAMING_SNAKE_CASE							,		"""encrypt"""							)






def 		_snake_case		( _SCREAMING_SNAKE_CASE					:						str							,		_SCREAMING_SNAKE_CASE					:						str							)      ->						str:







	"""simple docstring"""
	return translate_message(_SCREAMING_SNAKE_CASE							,		_SCREAMING_SNAKE_CASE							,		"""decrypt"""							)






def 		_snake_case		( _SCREAMING_SNAKE_CASE					:						str							,		_SCREAMING_SNAKE_CASE					:						str							,		_SCREAMING_SNAKE_CASE					:						str							)      ->						str:







	"""simple docstring"""
	lowerCAmelCase   =     []
	lowerCAmelCase   =     0
	lowerCAmelCase   =     key.upper()

	for symbol in message:
		lowerCAmelCase   =     LETTERS.find(symbol.upper()							)
		if num != -1:
			if mode == "encrypt":
				num += LETTERS.find(key[key_index]							)
			elif mode == "decrypt":
				num -= LETTERS.find(key[key_index]							)

			num %= len(_SCREAMING_SNAKE_CASE							)

			if symbol.isupper():
				translated.append(LETTERS[num]							)
			elif symbol.islower():
				translated.append(LETTERS[num].lower()							)

			key_index += 1
			if key_index == len(_SCREAMING_SNAKE_CASE							):
				lowerCAmelCase   =     0
		else:
			translated.append(_SCREAMING_SNAKE_CASE							)
	return "".join(_SCREAMING_SNAKE_CASE							)


if __name__ == "__main__":
				main()




'''simple docstring'''

import unittest

from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision, slow, torch_device


if is_torch_available():
				import torch

				from transformers import AutoModelForImageClassification

if is_vision_available():
				from transformers import AutoImageProcessor

@require_torch
@require_vision
class __snake_case(				unittest.TestCase ):


						'''simple docstring'''



						@slow
						def     __snake_case   ( self				)     ->     List[str]:
							lowerCAmelCase   =     AutoImageProcessor.from_pretrained("""microsoft/dit-base-finetuned-rvlcdip"""				)
							lowerCAmelCase   =     AutoModelForImageClassification.from_pretrained("""microsoft/dit-base-finetuned-rvlcdip"""				)
							model.to(A_				)

							from datasets import load_dataset

							lowerCAmelCase   =     load_dataset("""nielsr/rvlcdip-demo"""				)

							lowerCAmelCase   =     dataset["""train"""][0]["""image"""].convert("""RGB"""				)

							lowerCAmelCase   =     image_processor(A_     ,	return_tensors="""pt"""				).to(A_				)

							# forward pass
							with torch.no_grad():
								lowerCAmelCase   =     model(**A_				)
								lowerCAmelCase   =     outputs.logits

							lowerCAmelCase   =     torch.Size((1, 16)				)
							self.assertEqual(logits.shape     ,	A_				)

							lowerCAmelCase   =     torch.tensor(
							    [-0.4_1_5_8, -0.4_0_9_2, -0.4_3_4_7]     ,	device=A_     ,	dtype=torch.float     ,	)
							self.assertTrue(torch.allclose(logits[0, :3]     ,	A_     ,	atol=1e-4				)				)