




'''simple docstring'''






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  A		(			unittest.TestCase		):




				'''simple docstring'''





				@slow
				def 	a_	(self      )     ->	List[Any]:
							__UpperCamelCase				:      List[Any]									=       CamembertModel.from_pretrained("camembert-base"      )
							model.to(__lowercase      )

							__UpperCamelCase				:      List[Any]									=       torch.tensor(
							    [[5, 1_2_1, 1_1, 6_6_0, 1_6, 7_3_0, 2_5_5_4_3, 1_1_0, 8_3, 6]]			,  device=__lowercase			,  dtype=torch.long			,  )  # J'aime le camembert !
							with torch.no_grad():
										__UpperCamelCase				:      int									=       model(__lowercase      )["last_hidden_state"]
							__UpperCamelCase				:      Optional[int]									=       torch.Size((1, 1_0, 7_6_8)      )
							self.assertEqual(output.shape			,  __lowercase      )
							# compare the actual values for a slice.
							__UpperCamelCase				:      Any									=       torch.tensor(
							    [[[-0.0_254, 0.0_235, 0.1_027], [0.0_606, -0.1_811, -0.0_418], [-0.1_561, -0.1_127, 0.2_687]]]			,  device=__lowercase			,  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]			,  __lowercase			,  atol=1E-4      )      )









'''simple docstring'''






from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_lowerCAmelCase				     = {'''configuration_visual_bert''': ['''VISUAL_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''VisualBertConfig''']}

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				_lowerCAmelCase				     = [
				    '''VISUAL_BERT_PRETRAINED_MODEL_ARCHIVE_LIST''',
				    '''VisualBertForMultipleChoice''',
				    '''VisualBertForPreTraining''',
				    '''VisualBertForQuestionAnswering''',
				    '''VisualBertForRegionToPhraseAlignment''',
				    '''VisualBertForVisualReasoning''',
				    '''VisualBertLayer''',
				    '''VisualBertModel''',
				    '''VisualBertPreTrainedModel''',
				]


if TYPE_CHECKING:
				from .configuration_visual_bert import VISUAL_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP, VisualBertConfig

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_visual_bert import (
								    VISUAL_BERT_PRETRAINED_MODEL_ARCHIVE_LIST,
								    VisualBertForMultipleChoice,
								    VisualBertForPreTraining,
								    VisualBertForQuestionAnswering,
								    VisualBertForRegionToPhraseAlignment,
								    VisualBertForVisualReasoning,
								    VisualBertLayer,
								    VisualBertModel,
								    VisualBertPreTrainedModel,
								)


else:
				import sys

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



