
import unittest

from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device


if is_torch_available():
   import torch

   from transformers import CamembertModel






@require_torch
@require_sentencepiece
@require_tokenizers
class 						UpperCAmelCase	(		unittest.TestCase				):



   @slow
   def        _SCREAMING_SNAKE_CASE     (self	:      Any				)	->			int:


          '''simple docstring'''


          snake_case :     int           =   CamembertModel.from_pretrained("camembert-base"				)
          model.to(snake_case__				)

          snake_case :     List[str]           =   torch.tensor(
              [[5, 1_21, 11, 6_60, 16, 7_30, 2_55_43, 1_10, 83, 6]]					,		device=snake_case__					,		dtype=torch.long					,		)  # J'aime le camembert !
          with torch.no_grad():
                 snake_case :     Any           =   model(snake_case__				)["last_hidden_state"]
          snake_case :     Optional[Any]           =   torch.Size((1, 10, 7_68)				)
          self.assertEqual(output.shape					,		snake_case__				)
          # compare the actual values for a slice.
          snake_case :     Dict           =   torch.tensor(
              [[[-0.0254, 0.0235, 0.1027], [0.0606, -0.1811, -0.0418], [-0.1561, -0.1127, 0.2687]]]					,		device=snake_case__					,		dtype=torch.float					,		)
          # camembert = torch.hub.load('pytorch/fairseq', 'camembert.v0')
          # camembert.eval()
          # expected_slice = roberta.model.forward(input_ids)[0][:, :3, :3].detach()

          self.assertTrue(torch.allclose(output[:, :3, :3]					,		snake_case__					,		atol=1e-4				)				)







def     UpperCamelCase      (					__lowerCamelCase  :				list       ,      __lowerCamelCase  :				list       ,      __lowerCamelCase  :				list       ,      __lowerCamelCase  :				int       ,      __lowerCamelCase  :				int					):
       if target == 0:
              answer.append(path.copy()					)
       else:
              for index in range(__lowerCamelCase       ,      len(__lowerCamelCase					)					):
                     if target >= candidates[index]:
                            path.append(candidates[index]					)
                            backtrack(__lowerCamelCase       ,      __lowerCamelCase       ,      __lowerCamelCase       ,      target - candidates[index]       ,      __lowerCamelCase					)
                            path.pop(len(__lowerCamelCase					) - 1					)


def     UpperCamelCase      (					__lowerCamelCase  :				list       ,      __lowerCamelCase  :				int					):
       snake_case :     Optional[Any]           =   []  # type: list[int]
       snake_case :     Tuple           =   []  # type: list[int]
       backtrack(__lowerCamelCase       ,      __lowerCamelCase       ,      __lowerCamelCase       ,      __lowerCamelCase       ,      0					)
       return answer


def     UpperCamelCase      (					):
       print(combination_sum([-8, 2.3, 0]       ,      1					)					)


if __name__ == "__main__":
   import doctest

   doctest.testmod()
   main()





