

from __future__ import annotations

import unittest

from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow


if is_tf_available():
					import numpy as np
					import tensorflow as tf

					from transformers import TFCamembertModel





@require_tf
@require_sentencepiece
@require_tokenizers
class 	snake_case_   (		unittest.TestCase					):







			'''simple docstring'''

			@slow
			def 				snake_case__(     self :				int							)      ->str:
									snake_case_   =	TFCamembertModel.from_pretrained('''jplu/tf-camembert-base'''							)

									snake_case_   =	tf.convert_to_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]]							,   dtype=tf.intaa							,   )  # J'aime le camembert !"

									snake_case_   =	model(_UpperCamelCase							)['''last_hidden_state''']
									snake_case_   =	tf.TensorShape((1, 1_0, 7_6_8)							)
									self.assertEqual(output.shape							,   _UpperCamelCase							)
									# compare the actual values for a slice.
									snake_case_   =	tf.convert_to_tensor(
									    [[[-0.0254, 0.0235, 0.1027], [0.0606, -0.1811, -0.0418], [-0.1561, -0.1127, 0.2687]]]							,   dtype=tf.floataa							,   )
									# camembert = torch.hub.load('pytorch/fairseq', 'camembert.v0')
									# camembert.eval()
									# expected_slice = roberta.model.forward(input_ids)[0][:, :3, :3].detach()

									self.assertTrue(np.allclose(output[:, :3, :3].numpy()							,   expected_slice.numpy()							,   atol=1e-4							)							)


def   __SCREAMING_SNAKE_CASE					(SCREAMING_SNAKE_CASE__       ):
						snake_case_   =	[]
						if len(SCREAMING_SNAKE_CASE__       ) == 1:
												return [nums.copy()]
						for _ in range(len(SCREAMING_SNAKE_CASE__       )       ):
												snake_case_   =	nums.pop(0       )
												snake_case_   =	permute(SCREAMING_SNAKE_CASE__       )
												for perm in permutations:
																		perm.append(SCREAMING_SNAKE_CASE__       )
												result.extend(SCREAMING_SNAKE_CASE__       )
												nums.append(SCREAMING_SNAKE_CASE__       )
						return result


def   __SCREAMING_SNAKE_CASE					(SCREAMING_SNAKE_CASE__       ):

						def backtrack(SCREAMING_SNAKE_CASE__       ):
												if start == len(SCREAMING_SNAKE_CASE__       ) - 1:
																		output.append(nums[:]       )
												else:
																		for i in range(SCREAMING_SNAKE_CASE__  ,		len(SCREAMING_SNAKE_CASE__       )       ):
																								snake_case_,    snake_case_   =	nums[i], nums[start]
																								backtrack(start + 1       )
																								snake_case_,    snake_case_   =	nums[i], nums[start]  # backtrack

						snake_case_   =	[]
						backtrack(0       )
						return output


if __name__ == "__main__":
					import doctest

					# use res to print the data in permute2 function
					lowerCAmelCase_       	=	permutea([1, 2, 3])
					print(res)
					doctest.testmod()