






import argparse
import json

from tqdm import tqdm

def  SCREAMING_SNAKE_CASE							(       )      ->					Tuple:
     a     =				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"		, )
     a     =				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:
          a     =				json.load(__UpperCamelCase)
          for dpr_record in tqdm(__UpperCamelCase):
               a     =				dpr_record["question"]
               a     =				[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()







from math import isqrt

def  SCREAMING_SNAKE_CASE							(       __UpperCamelCase)      ->					bool:
     return all(number % divisor != 0 for divisor in range(2		, isqrt(__UpperCamelCase) + 1))

def  SCREAMING_SNAKE_CASE							(       __UpperCamelCase = 10**6)      ->					int:
     a     =				0
     a     =				1
     a     =				7
     while prime_candidate < max_prime:
          primes_count += is_prime(__UpperCamelCase)

          cube_index += 1
          prime_candidate += 6 * cube_index

     return primes_count


if __name__ == "__main__":
   print(F'{solution() = }')

