
"""simple docstring"""



def 	__snake_case  (    SCREAMING_SNAKE_CASE:					Optional[Any]     ,  SCREAMING_SNAKE_CASE:					str						):






							"""simple docstring"""



							print('\nThe shortest path matrix using Floyd Warshall algorithm\n'						)
							for i in range(_lowerCAmelCase						):
														for j in range(_lowerCAmelCase						):
																					if dist[i][j] != float('inf'						):
																												print(int(dist[i][j]						)     ,  end='\t'						)
																					else:
																												print('INF'     ,  end='\t'						)
														print()






def 	__snake_case  (    SCREAMING_SNAKE_CASE:					Tuple     ,  SCREAMING_SNAKE_CASE:					Tuple						):






							"""simple docstring"""



							_lowerCAmelCase  	=			[[float('inf'						) for _ in range(_lowerCAmelCase						)] for _ in range(_lowerCAmelCase						)]

							for i in range(_lowerCAmelCase						):
														for j in range(_lowerCAmelCase						):
																					_lowerCAmelCase  	=			graph[i][j]

																					# check vertex k against all other vertices (i, j)
							for k in range(_lowerCAmelCase						):
														# looping through rows of graph array
														for i in range(_lowerCAmelCase						):
																					# looping through columns of graph array
																					for j in range(_lowerCAmelCase						):
																												if (
																												    dist[i][k] != float('inf'						)
																												    and dist[k][j] != float('inf'						)
																												    and dist[i][k] + dist[k][j] < dist[i][j]
																												):
																																			_lowerCAmelCase  	=			dist[i][k] + dist[k][j]

							_print_dist(_lowerCAmelCase     ,  _lowerCAmelCase						)
							return dist, v


if __name__ == "__main__":
						_snake_case          =						int(input('''Enter number of vertices: '''))
						_snake_case          =						int(input('''Enter number of edges: '''))

						_snake_case          =						[[float('''inf''') for i in range(v)] for j in range(v)]

						for i in range(v):
												_snake_case          =						0.0

												# src and dst are indices that must be within the array size graph[e][v]
												# failure to follow this will result in an error
						for i in range(e):
												print('''\nEdge ''', i + 1)
												_snake_case          =						int(input('''Enter source:'''))
												_snake_case          =						int(input('''Enter destination:'''))
												_snake_case          =						float(input('''Enter weight:'''))
												_snake_case          =						weight

						floyd_warshall(graph, v)

						# Example Input
						# Enter number of vertices: 3
						# Enter number of edges: 2

						# # generated graph from vertex and edge inputs
						# [[inf, inf, inf], [inf, inf, inf], [inf, inf, inf]]
						# [[0.0, inf, inf], [inf, 0.0, inf], [inf, inf, 0.0]]

						# specify source, destination and weight for edge #1
						# Edge  1
						# Enter source:1
						# Enter destination:2
						# Enter weight:2

						# specify source, destination and weight for edge #2
						# Edge  2
						# Enter source:2
						# Enter destination:1
						# Enter weight:1

						# # Expected Output from the vertice, edge and src, dst, weight inputs!!
						# 0		INF	INF
						# INF	0	2
						# INF	1	0








"""simple docstring"""



import unittest

from datasets import load_dataset

from transformers import BloomTokenizerFast
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class        _SCREAMING_SNAKE_CASE  (  UpperCAmelCase      ,				unittest.TestCase							):






				'''simple docstring'''



				SCREAMING_SNAKE_CASE_:							str							=					None
				SCREAMING_SNAKE_CASE_:							List[str]							=					BloomTokenizerFast
				SCREAMING_SNAKE_CASE_:							List[str]							=					BloomTokenizerFast
				SCREAMING_SNAKE_CASE_:							Any							=					True
				SCREAMING_SNAKE_CASE_:							List[Any]							=					False
				SCREAMING_SNAKE_CASE_:							Optional[int]							=					"tokenizer_file"
				SCREAMING_SNAKE_CASE_:							str							=					{"bos_token": "<s>", "eos_token": "</s>", "unk_token": "<unk>", "pad_token": "<pad>"}


				def 				__lowerCamelCase	(					self	:			Tuple  )		->  str:







											"""simple docstring"""




											super().setUp()
											_lowerCAmelCase  	=			BloomTokenizerFast.from_pretrained('bigscience/tokenizer'  )
											tokenizer.save_pretrained(self.tmpdirname  )


				def 				__lowerCamelCase	(					self	:			List[str]				,     **UpperCAmelCase_	:			Any  )		->  Optional[Any]:







											"""simple docstring"""




											kwargs.update(self.special_tokens_map  )
											return BloomTokenizerFast.from_pretrained(self.tmpdirname				,     **UpperCAmelCase_  )


				def 				__lowerCamelCase	(					self	:			List[Any]  )		->  str:







											"""simple docstring"""




											_lowerCAmelCase  	=			self.get_rust_tokenizer()

											_lowerCAmelCase  	=			['The quick brown fox</s>', 'jumps over the lazy dog</s>']
											_lowerCAmelCase  	=			[[2_175, 23_714, 73_173, 144_252, 2], [77, 132_619, 3_478, 368, 109_586, 35_433, 2]]

											_lowerCAmelCase  	=			tokenizer.batch_encode_plus(UpperCAmelCase_  )['input_ids']
											self.assertListEqual(UpperCAmelCase_				,     UpperCAmelCase_  )

											_lowerCAmelCase  	=			tokenizer.batch_decode(UpperCAmelCase_  )
											self.assertListEqual(UpperCAmelCase_				,     UpperCAmelCase_  )


				def 				__lowerCamelCase	(					self	:			Any				,     UpperCAmelCase_	:			List[str]=6  )		->  Any:







											"""simple docstring"""




											for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
																		with self.subTest(F"""{tokenizer.__class__.__name__} ({pretrained_name})"""  ):
																									_lowerCAmelCase  	=			self.rust_tokenizer_class.from_pretrained(UpperCAmelCase_				,     **UpperCAmelCase_  )
																									# tokenizer_r.pad_token = None # Hotfixing padding = None
																									# Simple input
																									_lowerCAmelCase  	=			'This is a simple input'
																									_lowerCAmelCase  	=			['This is a simple input 1', 'This is a simple input 2']
																									_lowerCAmelCase  	=			('This is a simple input', 'This is a pair')
																									_lowerCAmelCase  	=			[
																									    ('This is a simple input 1', 'This is a simple input 2'),
																									    ('This is a simple pair 1', 'This is a simple pair 2'),
																									]

																									# Simple input tests
																									try:
																																tokenizer_r.encode(UpperCAmelCase_				,     max_length=UpperCAmelCase_  )
																																tokenizer_r.encode_plus(UpperCAmelCase_				,     max_length=UpperCAmelCase_  )

																																tokenizer_r.batch_encode_plus(UpperCAmelCase_				,     max_length=UpperCAmelCase_  )
																																tokenizer_r.encode(UpperCAmelCase_				,     max_length=UpperCAmelCase_  )
																																tokenizer_r.batch_encode_plus(UpperCAmelCase_				,     max_length=UpperCAmelCase_  )
																									except ValueError:
																																self.fail('Bloom Tokenizer should be able to deal with padding'  )

																									_lowerCAmelCase  	=			None  # Hotfixing padding = None
																									self.assertRaises(UpperCAmelCase_				,     tokenizer_r.encode				,     UpperCAmelCase_				,     max_length=UpperCAmelCase_				,     padding='max_length'  )

																									# Simple input
																									self.assertRaises(UpperCAmelCase_				,     tokenizer_r.encode_plus				,     UpperCAmelCase_				,     max_length=UpperCAmelCase_				,     padding='max_length'  )

																									# Simple input
																									self.assertRaises(
																									    UpperCAmelCase_				,     tokenizer_r.batch_encode_plus				,     UpperCAmelCase_				,     max_length=UpperCAmelCase_				,     padding='max_length'				,     )

																									# Pair input
																									self.assertRaises(UpperCAmelCase_				,     tokenizer_r.encode				,     UpperCAmelCase_				,     max_length=UpperCAmelCase_				,     padding='max_length'  )

																									# Pair input
																									self.assertRaises(UpperCAmelCase_				,     tokenizer_r.encode_plus				,     UpperCAmelCase_				,     max_length=UpperCAmelCase_				,     padding='max_length'  )

																									# Pair input
																									self.assertRaises(
																									    UpperCAmelCase_				,     tokenizer_r.batch_encode_plus				,     UpperCAmelCase_				,     max_length=UpperCAmelCase_				,     padding='max_length'				,     )


				def 				__lowerCamelCase	(					self	:			str  )		->  Any:







											"""simple docstring"""




											_lowerCAmelCase  	=			self.get_rust_tokenizer()
											_lowerCAmelCase  	=			load_dataset('xnli'				,     'all_languages'				,     split='test'				,     streaming=UpperCAmelCase_  )

											_lowerCAmelCase  	=			next(iter(UpperCAmelCase_  )  )['premise']  # pick up one data
											_lowerCAmelCase  	=			list(sample_data.values()  )

											_lowerCAmelCase  	=			list(map(tokenizer.encode				,     UpperCAmelCase_  )  )
											_lowerCAmelCase  	=			[tokenizer.decode(UpperCAmelCase_				,     clean_up_tokenization_spaces=UpperCAmelCase_  ) for x in output_tokens]
											self.assertListEqual(UpperCAmelCase_				,     UpperCAmelCase_  )







				def 				__lowerCamelCase	(					self	:			Tuple  )		->  List[Any]:







											"""simple docstring"""




											self.assertGreaterEqual(len(self.tokenizer_class.pretrained_vocab_files_map  )				,     1  )
											self.assertGreaterEqual(len(list(self.tokenizer_class.pretrained_vocab_files_map.values()  )[0]  )				,     1  )






