



'''simple docstring'''
import os

from ...utils import logging
from .utils import DataProcessor, InputExample


snake_case_				:			Any						 =						logging.get_logger(__name__)






class 							lowercase__			(							lowercase     ):





	def __init__(				self      :       Union[str, Any]				,lowerCamelCase__      :       Tuple				,lowerCamelCase__      :       Optional[int]=None				):







							'''simple docstring'''
							_UpperCamelCase      :	Any				       =     language
							_UpperCamelCase      :	int				       =     train_language





	def 			UpperCamelCase_						(				self      :       Optional[int]				,lowerCamelCase__      :       Dict				):







							'''simple docstring'''
							_UpperCamelCase      :	Tuple				       =     self.language if self.train_language is None else self.train_language
							_UpperCamelCase      :	List[Any]				       =     self._read_tsv(os.path.join(lowerCamelCase__				,F'XNLI-MT-1.0/multinli/multinli.train.{lg}.tsv'				)				)
							_UpperCamelCase      :	Union[str, Any]				       =     []
							for i, line in enumerate(lowerCamelCase__				):
													if i == 0:
																			continue
													_UpperCamelCase      :	Optional[Any]				       =     F'train-{i}'
													_UpperCamelCase      :	List[str]				       =     line[0]
													_UpperCamelCase      :	Union[str, Any]				       =     line[1]
													_UpperCamelCase      :	Tuple				       =     'contradiction' if line[2] == 'contradictory' else line[2]
													if not isinstance(lowerCamelCase__				,lowerCamelCase__				):
																			raise ValueError(F'Training input {text_a} is not a string'				)
													if not isinstance(lowerCamelCase__				,lowerCamelCase__				):
																			raise ValueError(F'Training input {text_b} is not a string'				)
													if not isinstance(lowerCamelCase__				,lowerCamelCase__				):
																			raise ValueError(F'Training label {label} is not a string'				)
													examples.append(InputExample(guid=lowerCamelCase__				,text_a=lowerCamelCase__				,text_b=lowerCamelCase__				,label=lowerCamelCase__				)				)
							return examples





	def 			UpperCamelCase_						(				self      :       Optional[Any]				,lowerCamelCase__      :       List[str]				):







							'''simple docstring'''
							_UpperCamelCase      :	Optional[int]				       =     self._read_tsv(os.path.join(lowerCamelCase__				,'XNLI-1.0/xnli.test.tsv'				)				)
							_UpperCamelCase      :	List[str]				       =     []
							for i, line in enumerate(lowerCamelCase__				):
													if i == 0:
																			continue
													_UpperCamelCase      :	Optional[int]				       =     line[0]
													if language != self.language:
																			continue
													_UpperCamelCase      :	Optional[int]				       =     F'test-{i}'
													_UpperCamelCase      :	Optional[int]				       =     line[6]
													_UpperCamelCase      :	List[str]				       =     line[7]
													_UpperCamelCase      :	str				       =     line[1]
													if not isinstance(lowerCamelCase__				,lowerCamelCase__				):
																			raise ValueError(F'Training input {text_a} is not a string'				)
													if not isinstance(lowerCamelCase__				,lowerCamelCase__				):
																			raise ValueError(F'Training input {text_b} is not a string'				)
													if not isinstance(lowerCamelCase__				,lowerCamelCase__				):
																			raise ValueError(F'Training label {label} is not a string'				)
													examples.append(InputExample(guid=lowerCamelCase__				,text_a=lowerCamelCase__				,text_b=lowerCamelCase__				,label=lowerCamelCase__				)				)
							return examples





	def 			UpperCamelCase_						(				self      :       str				):







							'''simple docstring'''
							return ["contradiction", "entailment", "neutral"]
snake_case_				:			int						 =						{
    'xnli': XnliProcessor,
}

snake_case_				:			Tuple						 =						{
    'xnli': 'classification',
}

snake_case_				:			Any						 =						{
    'xnli': 3,
}







'''simple docstring'''
from __future__ import annotations

from queue import Queue






class 							lowercase__			:





	def __init__(				self      :       int				):







							'''simple docstring'''
							_UpperCamelCase      :	dict[int, list[int]]				       =     {}





	def 			UpperCamelCase_						(				self      :       int				):







							'''simple docstring'''
							for i in self.vertices:
													print(lowerCamelCase__				,' : '				,' -> '.join([str(lowerCamelCase__				) for j in self.vertices[i]]				)				)





	def 			UpperCamelCase_						(				self      :       Optional[Any]				,lowerCamelCase__      :       int				,lowerCamelCase__      :       int				):







							'''simple docstring'''
							if from_vertex in self.vertices:
													self.vertices[from_vertex].append(lowerCamelCase__				)
							else:
													_UpperCamelCase      :	Any				       =     [to_vertex]





	def 			UpperCamelCase_						(				self      :       int				,lowerCamelCase__      :       int				):







							'''simple docstring'''
							_UpperCamelCase      :	Dict				       =     set()

							# create a first in first out queue to store all the vertices for BFS
							_UpperCamelCase      :	Queue				       =     Queue()

							# mark the source node as visited and enqueue it
							visited.add(lowerCamelCase__				)
							queue.put(lowerCamelCase__				)

							while not queue.empty():
													_UpperCamelCase      :	Optional[Any]				       =     queue.get()

													# loop through all adjacent vertex and enqueue it if not yet visited
													for adjacent_vertex in self.vertices[vertex]:
																			if adjacent_vertex not in visited:
																									queue.put(lowerCamelCase__				)
																									visited.add(lowerCamelCase__				)
							return visited


if __name__ == "__main__":
					from doctest import testmod

					testmod(verbose=True)

					snake_case_				:			int						 =						Graph()
					g.add_edge(0, 1)
					g.add_edge(0, 2)
					g.add_edge(1, 2)
					g.add_edge(2, 0)
					g.add_edge(2, 3)
					g.add_edge(3, 3)

					g.print_graph()
					# 0  :  1 -> 2
					# 1  :  2
					# 2  :  0 -> 3
					# 3  :  3

					assert sorted(g.bfs(2)) == [0, 1, 2, 3]


