




import numpy as np

lowerCAmelCase_					    = [
    ["""a""", """b""", """c""", """d""", """e"""],
    ["""f""", """g""", """h""", """i""", """k"""],
    ["""l""", """m""", """n""", """o""", """p"""],
    ["""q""", """r""", """s""", """t""", """u"""],
    ["""v""", """w""", """x""", """y""", """z"""],
]






class  _lowerCAmelCase     :

      def __init__(   self		):
        lowerCAmelCase__				:  List[Any]		       =     np.array(__UpperCAmelCase		)

      def 	__magic_name__(   self      ,				__UpperCAmelCase		):
        lowerCAmelCase__       ,			lowerCAmelCase__				:  int		       =     np.where(letter == self.SQUARE		)
        lowerCAmelCase__				:  Optional[Any]		       =     np.concatenate([indexa + 1, indexa + 1]		)
        return indexes

      def 	__magic_name__(   self      ,				__UpperCAmelCase      ,				__UpperCAmelCase		):
        lowerCAmelCase__				:  Optional[Any]		       =     self.SQUARE[indexa - 1, indexa - 1]
        return letter

      def 	__magic_name__(   self      ,				__UpperCAmelCase		):
        lowerCAmelCase__				:  Tuple		       =     message.lower()
        lowerCAmelCase__				:  Optional[int]		       =     message.replace(''' '''      ,				''''''		)
        lowerCAmelCase__				:  Dict		       =     message.replace('''j'''      ,				'''i'''		)

        lowerCAmelCase__				:  int		       =     np.empty((2, len(__UpperCAmelCase		))		)
        for letter_index in range(len(__UpperCAmelCase		)		):
          lowerCAmelCase__				:  Dict		       =     self.letter_to_numbers(message[letter_index]		)

          lowerCAmelCase__				:  int		       =     numbers[0]
          lowerCAmelCase__				:  List[Any]		       =     numbers[1]

        lowerCAmelCase__				:  Tuple		       =     first_step.reshape(2 * len(__UpperCAmelCase		)		)
        lowerCAmelCase__				:  Union[str, Any]		       =     ''''''
        for numbers_index in range(len(__UpperCAmelCase		)		):
          lowerCAmelCase__				:  Optional[Any]		       =     int(second_step[numbers_index * 2]		)
          lowerCAmelCase__				:  int		       =     int(second_step[(numbers_index * 2) + 1]		)
          lowerCAmelCase__				:  Tuple		       =     self.numbers_to_letter(__UpperCAmelCase      ,				__UpperCAmelCase		)
          lowerCAmelCase__				:  Dict		       =     encoded_message + letter

        return encoded_message







      def 	__magic_name__(   self      ,				__UpperCAmelCase		):
        lowerCAmelCase__				:  Union[str, Any]		       =     message.lower()
        message.replace(''' '''      ,				''''''		)
        lowerCAmelCase__				:  List[Any]		       =     np.empty(2 * len(__UpperCAmelCase		)		)
        for letter_index in range(len(__UpperCAmelCase		)		):
          lowerCAmelCase__				:  List[Any]		       =     self.letter_to_numbers(message[letter_index]		)
          lowerCAmelCase__				:  List[Any]		       =     numbers[0]
          lowerCAmelCase__				:  Union[str, Any]		       =     numbers[1]

        lowerCAmelCase__				:  List[Any]		       =     first_step.reshape((2, len(__UpperCAmelCase		))		)
        lowerCAmelCase__				:  Optional[int]		       =     ''''''
        for numbers_index in range(len(__UpperCAmelCase		)		):
          lowerCAmelCase__				:  Optional[int]		       =     int(second_step[0, numbers_index]		)
          lowerCAmelCase__				:  int		       =     int(second_step[1, numbers_index]		)
          lowerCAmelCase__				:  Any		       =     self.numbers_to_letter(__UpperCAmelCase      ,				__UpperCAmelCase		)
          lowerCAmelCase__				:  Dict		       =     decoded_message + letter

        return decoded_message







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 TFCamembertModel






@require_tf
@require_sentencepiece
@require_tokenizers
class  _lowerCAmelCase     (  unittest.TestCase	):

      @slow
      def 	__magic_name__(   self		):
        lowerCAmelCase__				:  Optional[Any]		       =     TFCamembertModel.from_pretrained('''jplu/tf-camembert-base'''		)

        lowerCAmelCase__				:  List[str]		       =     tf.convert_to_tensor(
            [[5, 121, 11, 660, 16, 730, 2_5543, 110, 83, 6]]      ,				dtype=tf.intaa      ,				)  # J'aime le camembert !"

        lowerCAmelCase__				:  str		       =     model(__UpperCAmelCase		)['''last_hidden_state''']
        lowerCAmelCase__				:  List[Any]		       =     tf.TensorShape((1, 10, 768)		)
        self.assertEqual(output.shape      ,				__UpperCAmelCase		)
        # compare the actual values for a slice.
        lowerCAmelCase__				:  int		       =     tf.convert_to_tensor(
            [[[-0.0254, 0.0235, 0.1027], [0.0606, -0.1811, -0.0418], [-0.1561, -0.1127, 0.2687]]]      ,				dtype=tf.floataa      ,				)
        # camembert = torch.hub.load('pytorch/fairseq', 'camembert.v0')
        # camembert.eval()
        # expected_slice = roberta.model.forward(input_ids)[0][:, :3, :3].detach()

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

