



from transformers import SqueezeBertTokenizer, SqueezeBertTokenizerFast
from transformers.testing_utils import require_tokenizers, slow

from ..bert.test_tokenization_bert import BertTokenizationTest





@require_tokenizers
class    __lowerCAmelCase					(	lowerCamelCase__			):
				__lowerCamelCase					=							SqueezeBertTokenizer
				__lowerCamelCase					=							SqueezeBertTokenizerFast
				__lowerCamelCase					=							True




				def 				snake_case  (				self		,							**_snake_case						):



									"""simple docstring"""





									return SqueezeBertTokenizerFast.from_pretrained(self.tmpdirname		,							**_snake_case						)




				@slow
				def 				snake_case  (				self						):



									"""simple docstring"""





									_lowerCAmelCase         =       SqueezeBertTokenizer.from_pretrained("""squeezebert/squeezebert-mnli-headless"""						)

									_lowerCAmelCase         =       tokenizer.encode("""sequence builders"""		,							add_special_tokens=_snake_case						)
									_lowerCAmelCase         =       tokenizer.encode("""multi-sequence build"""		,							add_special_tokens=_snake_case						)

									_lowerCAmelCase         =       tokenizer.build_inputs_with_special_tokens(_snake_case						)
									_lowerCAmelCase         =       tokenizer.build_inputs_with_special_tokens(_snake_case		,							_snake_case						)

									assert encoded_sentence == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id]
									assert encoded_pair == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id] + text_a + [
									    tokenizer.sep_token_id
									]








# A Bipartite Graph is a graph whose vertices can be divided into two independent sets,
# U and V such that every edge (u, v) either connects a vertex from U to V or a vertex
# from V to U. In other words, for every edge (u, v), either u belongs to U and v to V,
# or u belongs to V and v to U. We can also say that there is no edge that connects
# vertices of same set.
from queue import Queue


def 						_UpperCAmelCase							( snake_case     ):





					"""simple docstring"""

					_lowerCAmelCase         =       Queue()
					_lowerCAmelCase         =       [False] * len(snake_case     )
					_lowerCAmelCase         =       [-1] * len(snake_case     )

					def bfs():
										while not queue.empty():
															_lowerCAmelCase         =       queue.get()
															_lowerCAmelCase         =       True

															for neighbour in graph[u]:
																				if neighbour == u:
																									return False

																				if color[neighbour] == -1:
																									_lowerCAmelCase         =       1 - color[u]
																									queue.put(snake_case     )

																				elif color[neighbour] == color[u]:
																									return False

										return True

					for i in range(len(snake_case     )     ):
										if not visited[i]:
															queue.put(snake_case     )
															_lowerCAmelCase         =       0
															if bfs() is False:
																				return False

					return True


if __name__ == "__main__":
	# Adjacency List of graph
	print(check_bipartite({0: [1, 3], 1: [0, 2], 2: [1, 3], 3: [0, 2]}))



