





from __future__ import annotations

import unittest

from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow


if is_tf_available():
      import numpy as np
      import tensorflow as tf

      from transformers import TFXLMRobertaModel

@require_tf
@require_sentencepiece
@require_tokenizers
class    _UpperCAmelCase							(		unittest.TestCase     ):
      @slow
      def 		_lowerCamelCase      (		self       ):
         A_     :				List[str]			      =	TFXLMRobertaModel.from_pretrained("""jplu/tf-xlm-roberta-base"""       )

         A_     :				Any			      =	{
             """input_ids""": tf.convert_to_tensor([[0, 2646, 10269, 83, 99942, 2]]      ,       dtype=tf.intaa       ),  # "My dog is cute"
             """attention_mask""": tf.convert_to_tensor([[1, 1, 1, 1, 1, 1]]      ,       dtype=tf.intaa       ),
         }

         A_     :				Union[str, Any]			      =	model(a__       )["""last_hidden_state"""]
         A_     :				Tuple			      =	tf.TensorShape((1, 6, 768)       )
         self.assertEqual(output.shape      ,       a__       )
         # compare the actual values for a slice.
         A_     :				Tuple			      =	tf.convert_to_tensor(
             [
                 [
                     [0.068_1762, 0.1089_4451, 0.0677_2504],
                     [-0.0642_3668, 0.0236_6615, 0.0432_9344],
                     [-0.0605_7295, 0.0997_4135, -0.0007_0584],
                 ]
             ]      ,       dtype=tf.floataa      ,       )

         self.assertTrue(np.allclose(output[:, :3, :3].numpy()      ,       expected_slice.numpy()      ,       atol=1E-4       )       )













_lowerCAmelCase 				=     """ABCDEFGHIJKLMNOPQRSTUVWXYZ"""



def     _lowerCAmelCase		(  ):
   '''simple docstring'''


   A_     :				Any			      =	input("""Enter message: """     )
   A_     :				Dict			      =	input("""Enter key [alphanumeric]: """     )
   A_     :				Dict			      =	input("""Encrypt/Decrypt [e/d]: """     )

   if mode.lower().startswith("""e"""     ):
      A_     :				Union[str, Any]			      =	"""encrypt"""
      A_     :				Optional[int]			      =	encrypt_message(_lowerCAmelCase  ,_lowerCAmelCase     )
   elif mode.lower().startswith("""d"""     ):
      A_     :				str			      =	"""decrypt"""
      A_     :				Dict			      =	decrypt_message(_lowerCAmelCase  ,_lowerCAmelCase     )

   print(f"""\n{mode.title()}ed message:"""     )
   print(_lowerCAmelCase     )



def     _lowerCAmelCase		(  _lowerCAmelCase  ,_lowerCAmelCase     ):
   '''simple docstring'''


   return translate_message(_lowerCAmelCase  ,_lowerCAmelCase  ,"""encrypt"""     )



def     _lowerCAmelCase		(  _lowerCAmelCase  ,_lowerCAmelCase     ):
   '''simple docstring'''


   return translate_message(_lowerCAmelCase  ,_lowerCAmelCase  ,"""decrypt"""     )



def     _lowerCAmelCase		(  _lowerCAmelCase  ,_lowerCAmelCase  ,_lowerCAmelCase     ):
   '''simple docstring'''


   A_     :				Dict			      =	[]
   A_     :				List[Any]			      =	0
   A_     :				int			      =	key.upper()

   for symbol in message:
      A_     :				Optional[int]			      =	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(_lowerCAmelCase     )

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

         key_index += 1
         if key_index == len(_lowerCAmelCase     ):
            A_     :				Dict			      =	0
      else:
         translated.append(_lowerCAmelCase     )
   return "".join(_lowerCAmelCase     )


if __name__ == "__main__":
      main()






