

'''simple docstring'''

from __future__ import annotations

from collections import Counter
from random import random




class 	A_			:






     '''simple docstring'''



     def __init__(		self			:					List[Any]	)						->     Union[str, Any]:
      UpperCAmelCase	:     List[str]						 =			{}


     def        UpperCAmelCase_	(		self			:					Tuple					,      lowercase_			:					str	)						->     None:
      UpperCAmelCase	:     int						 =			{}


     def        UpperCAmelCase_	(		self			:					Dict					,      lowercase_			:					str					,      lowercase_			:					str					,      lowercase_			:					float	)						->     None:
      if nodea not in self.connections:
       self.add_node(lowercase_	)
      if nodea not in self.connections:
       self.add_node(lowercase_	)
      UpperCAmelCase	:     Any						 =			probability


     def        UpperCAmelCase_	(		self			:					Union[str, Any]	)						->     list[str]:
      return list(self.connections	)




     def        UpperCAmelCase_	(		self			:					List[str]					,      lowercase_			:					str	)						->     str:
      UpperCAmelCase	:     Any						 =			0
      UpperCAmelCase	:     Union[str, Any]						 =			random()

      for dest in self.connections[node]:
       current_probability += self.connections[node][dest]
       if current_probability > random_value:
        return dest
      return ""




def 				UpperCamelCase(					UpperCAmelCase_  ,	UpperCAmelCase_  ,	UpperCAmelCase_     ):
 UpperCAmelCase	:     Tuple						 =			MarkovChainGraphUndirectedUnweighted()

 for nodea, nodea, probability in transitions:
  graph.add_transition_probability(UpperCAmelCase_  ,	UpperCAmelCase_  ,	UpperCAmelCase_     )

 UpperCAmelCase	:     Tuple						 =			Counter(graph.get_nodes()     )
 UpperCAmelCase	:     Tuple						 =			start

 for _ in range(UpperCAmelCase_     ):
  UpperCAmelCase	:     Optional[Any]						 =			graph.transition(UpperCAmelCase_     )
  visited[node] += 1

 return visited


if __name__ == "__main__":
 import doctest

 doctest.testmod()







'''simple docstring'''

import argparse
import json

from tqdm import tqdm




def 				UpperCamelCase(					):
 UpperCAmelCase	:     List[Any]						 =			argparse.ArgumentParser()

 # Required parameters
 parser.add_argument(
     '--src_path'  ,	type=UpperCAmelCase_  ,	default='biencoder-nq-dev.json'  ,	help='Path to raw DPR training data'  ,	)
 parser.add_argument(
     '--evaluation_set'  ,	type=UpperCAmelCase_  ,	help='where to store parsed evaluation_set file'  ,	)
 parser.add_argument(
     '--gold_data_path'  ,	type=UpperCAmelCase_  ,	help='where to store parsed gold_data_path file'  ,	)
 UpperCAmelCase	:     int						 =			parser.parse_args()

 with open(args.src_path  ,	'r'     ) as src_file, open(args.evaluation_set  ,	'w'     ) as eval_file, open(
     args.gold_data_path  ,	'w'     ) as gold_file:
  UpperCAmelCase	:     int						 =			json.load(UpperCAmelCase_     )
  for dpr_record in tqdm(UpperCAmelCase_     ):
   UpperCAmelCase	:     Any						 =			dpr_record['question']
   UpperCAmelCase	:     List[str]						 =			[context['title'] for context in dpr_record['positive_ctxs']]
   eval_file.write(question + '\n'     )
   gold_file.write('\t'.join(UpperCAmelCase_     ) + '\n'     )


if __name__ == "__main__":
 main()




