


"""simple docstring"""


import os
import unittest

from transformers import MPNetTokenizerFast
from transformers.models.mpnet.tokenization_mpnet import VOCAB_FILES_NAMES, MPNetTokenizer
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class snake_case					(     _UpperCamelCase   , unittest.TestCase):
		__UpperCamelCase							=	MPNetTokenizer
		__UpperCamelCase							=	MPNetTokenizerFast
		__UpperCamelCase							=	True
		__UpperCamelCase							=	True







		def        a_       (    self					:				Optional[Any]						)				->  Any:





						'''simple docstring'''







						super().setUp()

						_A         =	[
						    "[UNK]",
						    "[CLS]",
						    "[SEP]",
						    "[PAD]",
						    "[MASK]",
						    "want",
						    "##want",
						    "##ed",
						    "wa",
						    "un",
						    "runn",
						    "##ing",
						    ",",
						    "low",
						    "lowest",
						]
						_A         =	os.path.join(self.tmpdirname			,      VOCAB_FILES_NAMES["vocab_file"]						)
						with open(self.vocab_file			,      "w"			,      encoding="utf-8"						) as vocab_writer:
										vocab_writer.write("".join([x + "\n" for x in vocab_tokens]						)						)







		def        a_       (    self					:				List[str]			,      a__					:				Any						)				->  int:





						'''simple docstring'''







						_A         =	"UNwant\u00E9d,running"
						_A         =	"unwanted, running"
						return input_text, output_text







		def        a_       (    self					:				Tuple						)				->  Dict:





						'''simple docstring'''







						_A         =	self.tokenizer_class(self.vocab_file						)

						_A         =	tokenizer.tokenize("UNwant\u00E9d,running"						)
						self.assertListEqual(a__			,      ["un", "##want", "##ed", ",", "runn", "##ing"]						)
						self.assertListEqual(tokenizer.convert_tokens_to_ids(a__						)			,      [9, 6, 7, 12, 10, 11]						)







		@slow
		def        a_       (    self					:				Tuple						)				->  Any:





						'''simple docstring'''







						_A         =	self.tokenizer_class.from_pretrained("microsoft/mpnet-base"						)

						_A         =	tokenizer.encode("sequence builders"			,      add_special_tokens=a__						)
						_A         =	tokenizer.encode("multi-sequence build"			,      add_special_tokens=a__						)

						_A         =	tokenizer.build_inputs_with_special_tokens(a__						)
						_A         =	tokenizer.build_inputs_with_special_tokens(a__			,      a__						)

						assert encoded_sentence == [0] + text + [2]
						assert encoded_pair == [0] + text + [2] + [2] + text_a + [2]


from __future__ import annotations

class  a     :


						def __init__(				self  ,    A_		):







										'''simple docstring'''


										_UpperCAmelCase				:						List[Any]       						=			vertices
										_UpperCAmelCase				:						List[str]       						=			[[0] * vertices for _ in range(A_		)]


						def 				_UpperCAmelCase (				self  ,    A_		):







										'''simple docstring'''


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


						def 				_UpperCAmelCase (				self  ,    A_  ,    A_		):







										'''simple docstring'''


										_UpperCAmelCase				:						Tuple       						=			1e7
										_UpperCAmelCase				:						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:
																		_UpperCAmelCase				:						List[Any]       						=			distances_from_source[vertex]
																		_UpperCAmelCase				:						Tuple       						=			vertex
										return min_index





						def 				_UpperCAmelCase (				self  ,    A_		):







										'''simple docstring'''


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

										for _ in range(self.vertices		):
														_UpperCAmelCase				:						str       						=			self.minimum_distance(A_  ,    A_		)
														_UpperCAmelCase				:						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]
																		):
																						_UpperCAmelCase				:						str       						=			distances[u] + self.graph[u][v]

										self.print_solution(A_		)


if __name__ == "__main__":
					SCREAMING_SNAKE_CASE_						=					Graph(9)
					SCREAMING_SNAKE_CASE_						=					[
					    [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)


