





UpperCAmelCase						:   List[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  _SCREAMING_SNAKE_CASE				(   a					,						a					,						a					,						a  )      ->      Any:
					__A	:						Union[str, Any]       =				[False] * len(_UpperCamelCase  )
					__A	:						str       =				[s]
					__A	:						Tuple       =				True

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

					return visited[t]







def  _SCREAMING_SNAKE_CASE				(   a					,						a					,						a  )      ->      Dict:
					__A	:						Any       =				[-1] * (len(_UpperCamelCase  ))
					__A	:						Tuple       =				0
					__A	:						Dict       =				[]
					__A	:						Union[str, Any]       =				[i[:] for i in graph]  # Record original cut, copy.
					while bfs(_UpperCamelCase					,						_UpperCamelCase					,						_UpperCamelCase					,						_UpperCamelCase  ):
										__A	:						int       =				float('Inf'  )
										__A	:						Optional[int]       =				sink

										while s != source:
															# Find the minimum value in select path
															__A	:						Optional[Any]       =				min(_UpperCamelCase					,						graph[parent[s]][s]  )
															__A	:						List[str]       =				parent[s]

										max_flow += path_flow
										__A	:						str       =				sink

										while v != source:
															__A	:						int       =				parent[v]
															graph[u][v] -= path_flow
															graph[v][u] += path_flow
															__A	:						Tuple       =				parent[v]

					for i in range(len(_UpperCamelCase  )  ):
										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"""






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      lowerCamelCase__   (     A     ,    unittest.TestCase				):







					"""simple docstring"""


					__a	       =							None
					__a	       =							BloomTokenizerFast
					__a	       =							BloomTokenizerFast
					__a	       =							True
					__a	       =							False
					__a	       =							"""tokenizer_file"""
					__a	       =							{"""bos_token""": """<s>""", """eos_token""": """</s>""", """unk_token""": """<unk>""", """pad_token""": """<pad>"""}






					def lowerCamelCase__							(       self    : int  ):
												'''simple docstring'''






												super().setUp()
												__UpperCAmelCase   :						Any      							=					BloomTokenizerFast.from_pretrained("""bigscience/tokenizer"""  )
												tokenizer.save_pretrained(self.tmpdirname  )






					def lowerCamelCase__							(       self    : Any ,       **UpperCamelCase    : Optional[int]  ):
												'''simple docstring'''






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






					def lowerCamelCase__							(       self    : Optional[Any]  ):
												'''simple docstring'''






												__UpperCAmelCase   :						Any      							=					self.get_rust_tokenizer()

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

												__UpperCAmelCase   :						Dict      							=					tokenizer.batch_encode_plus(UpperCamelCase  )["""input_ids"""]
												self.assertListEqual(UpperCamelCase ,       UpperCamelCase  )

												__UpperCAmelCase   :						int      							=					tokenizer.batch_decode(UpperCamelCase  )
												self.assertListEqual(UpperCamelCase ,       UpperCamelCase  )






					def lowerCamelCase__							(       self    : int ,       UpperCamelCase    : Any=6  ):
												'''simple docstring'''






												for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
																			with self.subTest(f'''{tokenizer.__class__.__name__} ({pretrained_name})'''  ):
																										__UpperCAmelCase   :						Optional[int]      							=					self.rust_tokenizer_class.from_pretrained(UpperCamelCase ,       **UpperCamelCase  )
																										# tokenizer_r.pad_token = None # Hotfixing padding = None
																										# Simple input
																										__UpperCAmelCase   :						Dict      							=					"""This is a simple input"""
																										__UpperCAmelCase   :						str      							=					["""This is a simple input 1""", """This is a simple input 2"""]
																										__UpperCAmelCase   :						List[str]      							=					("""This is a simple input""", """This is a pair""")
																										__UpperCAmelCase   :						Dict      							=					[
																										    ("""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"""  )

																										__UpperCAmelCase   :						Union[str, Any]      							=					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    : Any  ):
												'''simple docstring'''






												__UpperCAmelCase   :						Union[str, Any]      							=					self.get_rust_tokenizer()
												__UpperCAmelCase   :						Optional[Any]      							=					load_dataset("""xnli""" ,       """all_languages""" ,       split="""test""" ,       streaming=UpperCamelCase  )

												__UpperCAmelCase   :						Optional[Any]      							=					next(iter(UpperCamelCase  )  )["""premise"""]  # pick up one data
												__UpperCAmelCase   :						Any      							=					list(sample_data.values()  )

												__UpperCAmelCase   :						Optional[Any]      							=					list(map(tokenizer.encode ,       UpperCamelCase  )  )
												__UpperCAmelCase   :						List[Any]      							=					[tokenizer.decode(UpperCamelCase ,       clean_up_tokenization_spaces=UpperCamelCase  ) for x in output_tokens]
												self.assertListEqual(UpperCamelCase ,       UpperCamelCase  )






					def lowerCamelCase__							(       self    : Optional[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  )
