
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 						UpperCAmelCase	(		unittest.TestCase				):



   @slow
   def        _SCREAMING_SNAKE_CASE     (self	:      Any				)	->			int:


          '''simple docstring'''


          snake_case :     int           =   CamembertModel.from_pretrained("camembert-base"				)
          model.to(snake_case__				)

          snake_case :     List[str]           =   torch.tensor(
              [[5, 1_21, 11, 6_60, 16, 7_30, 2_55_43, 1_10, 83, 6]]					,		device=snake_case__					,		dtype=torch.long					,		)  # J'aime le camembert !
          with torch.no_grad():
                 snake_case :     Any           =   model(snake_case__				)["last_hidden_state"]
          snake_case :     Optional[Any]           =   torch.Size((1, 10, 7_68)				)
          self.assertEqual(output.shape					,		snake_case__				)
          # compare the actual values for a slice.
          snake_case :     Dict           =   torch.tensor(
              [[[-0.0254, 0.0235, 0.1027], [0.0606, -0.1811, -0.0418], [-0.1561, -0.1127, 0.2687]]]					,		device=snake_case__					,		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]					,		snake_case__					,		atol=1e-4				)				)







from __future__ import annotations






class 						UpperCAmelCase	:



   def __init__(self	:      List[str]					,		snake_case__	:      int				)	->			None:


          '''simple docstring'''


          snake_case :     Any           =   vertices
          snake_case :     str           =   [[0] * vertices for _ in range(snake_case__				)]



   def        _SCREAMING_SNAKE_CASE     (self	:      str					,		snake_case__	:      list[int]				)	->			None:


          '''simple docstring'''


          print("Vertex \t Distance from Source"				)
          for vertex in range(self.vertices				):
                 print(snake_case__					,		"\t\t"					,		distances_from_source[vertex]				)



   def        _SCREAMING_SNAKE_CASE     (self	:      Optional[int]					,		snake_case__	:      list[int]					,		snake_case__	:      list[bool]				)	->			int:


          '''simple docstring'''


          snake_case :     Union[str, Any]           =   1e7
          snake_case :     Any           =   0

          # Search not nearest vertex not in the shortest path tree
          for vertex in range(self.vertices				):
                 if distances_from_source[vertex] < minimum and visited[vertex] is False:
                        snake_case :     Union[str, Any]           =   distances_from_source[vertex]
                        snake_case :     str           =   vertex
          return min_index



   def        _SCREAMING_SNAKE_CASE     (self	:      Optional[Any]					,		snake_case__	:      int				)	->			None:


          '''simple docstring'''


          snake_case :     Optional[int]           =   [int(1e7				)] * self.vertices  # distances from the source
          snake_case :     Dict           =   0
          snake_case :     Union[str, Any]           =   [False] * self.vertices

          for _ in range(self.vertices				):
                 snake_case :     Dict           =   self.minimum_distance(snake_case__					,		snake_case__				)
                 snake_case :     List[str]           =   True

                 # Update dist value of the adjacent vertices
                 # of the picked vertex only if the current
                 # distance is greater than new distance and
                 # the vertex in not in the shortest path tree
                 for v in range(self.vertices				):
                        if (
                            self.graph[u][v] > 0
                            and visited[v] is False
                            and distances[v] > distances[u] + self.graph[u][v]
                        ):
                               snake_case :     Union[str, Any]           =   distances[u] + self.graph[u][v]

          self.print_solution(snake_case__				)


if __name__ == "__main__":
   __lowerCamelCase							= Graph(9)
   __lowerCamelCase							= [
       [0, 4, 0, 0, 0, 0, 0, 8, 0],
       [4, 0, 8, 0, 0, 0, 0, 11, 0],
       [0, 8, 0, 7, 0, 4, 0, 0, 2],
       [0, 0, 7, 0, 9, 14, 0, 0, 0],
       [0, 0, 0, 9, 0, 10, 0, 0, 0],
       [0, 0, 4, 14, 10, 0, 2, 0, 0],
       [0, 0, 0, 0, 0, 2, 0, 1, 6],
       [8, 11, 0, 0, 0, 0, 1, 0, 7],
       [0, 0, 2, 0, 0, 0, 6, 7, 0],
   ]
   graph.dijkstra(0)





