






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        snake_case_				(							unittest.TestCase   ):







   """simple docstring"""



   @slow
   def       SCREAMING_SNAKE_CASE__					(     self:						Optional[int]						)	->		str:


       """simple docstring"""



       _lowercase     			=						CamembertModel.from_pretrained('camembert-base'						)
       model.to(snake_case__						)

       _lowercase     			=						torch.tensor(
           [[5, 121, 11, 660, 16, 730, 25_543, 110, 83, 6]] ,							device=snake_case__ ,							dtype=torch.long ,							)  # J'aime le camembert !
       with torch.no_grad():
           _lowercase     			=						model(snake_case__						)['last_hidden_state']
       _lowercase     			=						torch.Size((1, 10, 768)						)
       self.assertEqual(output.shape ,							snake_case__						)
       # compare the actual values for a slice.
       _lowercase     			=						torch.tensor(
           [[[-0.02_54, 0.02_35, 0.10_27], [0.06_06, -0.18_11, -0.04_18], [-0.15_61, -0.11_27, 0.26_87]]] ,							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						)						)








from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available, is_tokenizers_available


lowerCamelCase					    =	{}

try:
   if not is_sentencepiece_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   lowerCamelCase					    =	['''MBart50Tokenizer''']

try:
   if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   lowerCamelCase					    =	['''MBart50TokenizerFast''']


if TYPE_CHECKING:
   try:
      if not is_sentencepiece_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .tokenization_mbartaa import MBartaaTokenizer

   try:
      if not is_tokenizers_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .tokenization_mbartaa_fast import MBartaaTokenizerFast

else:
   import sys

   lowerCamelCase					    =	_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)
