


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 	__lowerCamelCase			(unittest.TestCase						):







       @slow
       def 		snake_case_	(			self: Any					):






            '''simple docstring'''




            __UpperCamelCase =			TFCamembertModel.from_pretrained('jplu/tf-camembert-base'					)

            __UpperCamelCase =			tf.convert_to_tensor(
                [[5, 121, 11, 660, 16, 730, 2_5543, 110, 83, 6]],dtype=tf.intaa,)  # J'aime le camembert !"

            __UpperCamelCase =			model(A_					)['last_hidden_state']
            __UpperCamelCase =			tf.TensorShape((1, 10, 768)					)
            self.assertEqual(output.shape,A_					)
            # compare the actual values for a slice.
            __UpperCamelCase =			tf.convert_to_tensor(
                [[[-0.0_2_5_4, 0.0_2_3_5, 0.1_0_2_7], [0.0_6_0_6, -0.1_8_1_1, -0.0_4_1_8], [-0.1_5_6_1, -0.1_1_2_7, 0.2_6_8_7]]],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 	_lowerCAmelCase					( UpperCamelCase__:  Union[str, Any]    )			-> Dict:





	"""simple docstring"""







	return [
	    {
	        0: [1, 2],
	        1: [0, 2],
	        2: [0, 1, 3, 5],
	        3: [2, 4],
	        4: [3],
	        5: [2, 6, 8],
	        6: [5, 7],
	        7: [6, 8],
	        8: [5, 7],
	    },
	    {
	        0: [6],
	        1: [9],
	        2: [4, 5],
	        3: [4],
	        4: [2, 3],
	        5: [2],
	        6: [0, 7],
	        7: [6],
	        8: [],
	        9: [1],
	    },
	    {
	        0: [4],
	        1: [6],
	        2: [],
	        3: [5, 6, 7],
	        4: [0, 6],
	        5: [3, 8, 9],
	        6: [1, 3, 4, 7],
	        7: [3, 6, 8, 9],
	        8: [5, 7],
	        9: [5, 7],
	    },
	    {
	        0: [1, 3],
	        1: [0, 2, 4],
	        2: [1, 3, 4],
	        3: [0, 2, 4],
	        4: [1, 2, 3],
	    },
	][index]





def 	_lowerCAmelCase					( UpperCamelCase__:  dict[int, list[int]]    )			-> list[tuple[int, int]]:





	"""simple docstring"""







	A             =					0
	A             =					len(UpperCamelCase__    )  # No of vertices in graph
	A             =					[0] * n
	A             =					[False] * n

	def dfs(UpperCamelCase__:  Union[str, Any]				,       UpperCamelCase__:  str				,       UpperCamelCase__:  Union[str, Any]				,       UpperCamelCase__:  Any    ):
		A             =					True
		A             =					id_
		id_ += 1
		for to in graph[at]:
			if to == parent:
				pass
			elif not visited[to]:
				dfs(UpperCamelCase__				,       UpperCamelCase__				,       UpperCamelCase__				,       id_    )
				A             =					min(low[at]				,       low[to]    )
				if id_ <= low[to]:
					bridges.append((at, to) if at < to else (to, at)    )
			else:
				# This edge is a back edge and cannot be a bridge
				A             =					min(low[at]				,       low[to]    )

	A             =					[]
	for i in range(UpperCamelCase__    ):
		if not visited[i]:
			dfs(UpperCamelCase__				,       -1				,       UpperCamelCase__				,       id_    )
	return bridges


if __name__ == "__main__":
				import doctest

				doctest.testmod()



