

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 			__lowerCAmelCase					( unittest.TestCase							):




  @slow
  def   A__					(    self )  ->			Optional[Any]:
        '''simple docstring'''






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

        _lowercase     	=torch.tensor(
            [[5, 121, 11, 660, 16, 730, 25_543, 110, 83, 6]]							,       device=lowerCAmelCase							,       dtype=torch.long							,       )  # J'aime le camembert !
        with torch.no_grad():
              _lowercase     	=model(lowerCAmelCase )['last_hidden_state']
        _lowercase     	=torch.Size((1, 10, 768) )
        self.assertEqual(output.shape							,       lowerCAmelCase )
        # compare the actual values for a slice.
        _lowercase     	=torch.tensor(
            [[[-0.0254, 0.0235, 0.1027], [0.0606, -0.1811, -0.0418], [-0.1561, -0.1127, 0.2687]]]							,       device=lowerCAmelCase							,       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]							,       lowerCAmelCase							,       atol=1e-4 ) )



import warnings

from ...utils import logging
from .image_processing_vit import ViTImageProcessor


lowercase_     =       logging.get_logger(__name__)





class 			__lowerCAmelCase					( SCREAMING_SNAKE_CASE							):




  def __init__(    self							,       *lowerCAmelCase							,       **lowerCAmelCase )  ->			None:
        '''simple docstring'''






        warnings.warn(
            'The class ViTFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please'
            ' use ViTImageProcessor instead.'							,       lowerCAmelCase							,       )
        super().__init__(*lowerCAmelCase							,       **lowerCAmelCase )


