




UpperCamelCase__ :   Optional[Any]						=							[
    [0, 16, 13, 0, 0, 0],
    [0, 0, 10, 12, 0, 0],
    [0, 4, 0, 0, 14, 0],
    [0, 0, 9, 0, 0, 20],
    [0, 0, 0, 7, 0, 4],
    [0, 0, 0, 0, 0, 0],
]





def        __UpperCAmelCase						(							lowerCamelCase_ :     Union[str, Any]  ,							lowerCamelCase_ :     List[str]  ,							lowerCamelCase_ :     str  ,							lowerCamelCase_ :     str  )       ->  Union[str, Any]:







			"""simple docstring"""





			SCREAMING_SNAKE_CASE_   : Optional[Any]					  =      [False] * len(lowerCamelCase_  )
			SCREAMING_SNAKE_CASE_   : Optional[Any]					  =      [s]
			SCREAMING_SNAKE_CASE_   : List[Any]					  =      True

			while queue:
						SCREAMING_SNAKE_CASE_   : List[str]					  =      queue.pop(0  )
						for ind in range(len(graph[u]  )  ):
									if visited[ind] is False and graph[u][ind] > 0:
												queue.append(lowerCamelCase_  )
												SCREAMING_SNAKE_CASE_   : Dict					  =      True
												SCREAMING_SNAKE_CASE_   : Optional[Any]					  =      u

			return visited[t]





def        __UpperCAmelCase						(							lowerCamelCase_ :     List[Any]  ,							lowerCamelCase_ :     int  ,							lowerCamelCase_ :     Any  )       ->  int:







			"""simple docstring"""





			SCREAMING_SNAKE_CASE_   : Any					  =      [-1] * (len(lowerCamelCase_  ))
			SCREAMING_SNAKE_CASE_   : Union[str, Any]					  =      0
			SCREAMING_SNAKE_CASE_   : Any					  =      []
			SCREAMING_SNAKE_CASE_   : Optional[int]					  =      [i[:] for i in graph]  # Record original cut, copy.
			while bfs(lowerCamelCase_  ,							lowerCamelCase_  ,							lowerCamelCase_  ,							lowerCamelCase_  ):
						SCREAMING_SNAKE_CASE_   : Optional[int]					  =      float('Inf'  )
						SCREAMING_SNAKE_CASE_   : Dict					  =      sink

						while s != source:
									# Find the minimum value in select path
									SCREAMING_SNAKE_CASE_   : int					  =      min(lowerCamelCase_  ,							graph[parent[s]][s]  )
									SCREAMING_SNAKE_CASE_   : Tuple					  =      parent[s]

						max_flow += path_flow
						SCREAMING_SNAKE_CASE_   : Any					  =      sink

						while v != source:
									SCREAMING_SNAKE_CASE_   : Union[str, Any]					  =      parent[v]
									graph[u][v] -= path_flow
									graph[v][u] += path_flow
									SCREAMING_SNAKE_CASE_   : Union[str, Any]					  =      parent[v]

			for i in range(len(lowerCamelCase_  )  ):
						for j in range(len(graph[0]  )  ):
									if graph[i][j] == 0 and temp[i][j] > 0:
												res.append((i, j)  )

			return res


if __name__ == "__main__":
						print(mincut(test_graph, source=0, sink=5))




'''simple docstring'''






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 lowercase_       (		unittest.TestCase			):







   """simple docstring"""

   @slow
   def 	__UpperCAmelCase   (      self      :			List[str]     )  ->			Any:
        _A    		=  TFCamembertModel.from_pretrained('jplu/tf-camembert-base'     )

        _A    		=  tf.convert_to_tensor(
            [[5, 1_21, 11, 6_60, 16, 7_30, 2_55_43, 1_10, 83, 6]], dtype=tf.intaa, )  # J'aime le camembert !"

        _A    		=  model(UpperCamelCase__     )['last_hidden_state']
        _A    		=  tf.TensorShape((1, 10, 7_68)     )
        self.assertEqual(output.shape, UpperCamelCase__     )
        # compare the actual values for a slice.
        _A    		=  tf.convert_to_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]]], 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     )     )



