




from __future__ import annotations

from collections.abc import Iterator
from typing import Any




class    snake_case__							:
				"""simple docstring"""



				def __init__(				self    :					int ,				__lowerCamelCase    :					Any							) ->					None:
							a   =      data
							a   =      None





				def __str__(				self    :					Optional[Any]							) ->					str:
							return f"""{self.data}"""




class    snake_case__							:
				"""simple docstring"""



				def __init__(				self    :					int							) ->					None:
							a   =      None
							a   =      None





				def __iter__(				self    :					List[Any]							) ->					Iterator[Any]:
							a   =      self.front
							while node:
										yield node.data
										a   =      node.next





				def __len__(				self    :					Dict							) ->					int:
							return len(tuple(iter(self							)							)							)





				def __str__(				self    :					Union[str, Any]							) ->					str:
							return " <- ".join(str(__lowerCamelCase							) for item in self							)





				def 							__UpperCAmelCase							(				self    :					Any							) ->					bool:
							return len(self							) == 0





				def 							__UpperCAmelCase							(				self    :					List[str] ,				__lowerCamelCase    :					Any							) ->					None:
							a   =      Node(__lowerCamelCase							)
							if self.is_empty():
										a   =      a   =      node
							else:
										assert isinstance(self.rear ,				__lowerCamelCase							)
										a   =      node
										a   =      node





				def 							__UpperCAmelCase							(				self    :					Dict							) ->					Any:
							if self.is_empty():
										raise IndexError("dequeue from empty queue"							)
							assert isinstance(self.front ,				__lowerCamelCase							)
							a   =      self.front
							a   =      self.front.next
							if self.front is None:
										a   =      None
							return node.data





				def 							__UpperCAmelCase							(				self    :					Optional[int]							) ->					None:
							a   =      a   =      None


if __name__ == "__main__":
		from doctest import testmod

		testmod()












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 							__UpperCAmelCase							(				self    :					Optional[Any]							) ->					List[str]:
							a   =      CamembertModel.from_pretrained("camembert-base"							)
							model.to(__lowerCamelCase							)

							a   =      torch.tensor(
							    [[5, 1_21, 11, 6_60, 16, 7_30, 2_55_43, 1_10, 83, 6]] ,				device=__lowerCamelCase ,				dtype=torch.long ,				)  # J'aime le camembert !
							with torch.no_grad():
										a   =      model(__lowerCamelCase							)["last_hidden_state"]
							a   =      torch.Size((1, 10, 7_68)							)
							self.assertEqual(output.shape ,				__lowerCamelCase							)
							# compare the actual values for a slice.
							a   =      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=__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							)							)






