



import unittest

import numpy as np
def 		UpperCamelCase	(   snake_case__       :    np.ndarray       ,     snake_case__       :    np.ndarray       ,     snake_case__       :    np.ndarray       ,     snake_case__       :    np.ndarray | None = None       ,     )	->     np.ndarray:
   UpperCamelCase    :  Optional[Any]							=	np.shape(snake_case__	)
   UpperCamelCase    :  List[str]							=	np.shape(snake_case__	)
   UpperCamelCase    :  Optional[Any]							=	np.shape(snake_case__	)

   if shape_a[0] != shape_b[0]:
      UpperCamelCase    :  str							=	(
          'Expected the same number of rows for A and B. '
          F"""Instead found A of size {shape_a} and B of size {shape_b}"""
      )
      raise ValueError(snake_case__	)

   if shape_b[1] != shape_c[1]:
      UpperCamelCase    :  str							=	(
          'Expected the same number of columns for B and C. '
          F"""Instead found B of size {shape_b} and C of size {shape_c}"""
      )
      raise ValueError(snake_case__	)

   UpperCamelCase    :  List[str]							=	pseudo_inv
   if a_inv is None:
      try:
         UpperCamelCase    :  str							=	np.linalg.inv(snake_case__	)
      except np.linalg.LinAlgError:
         raise ValueError(
             'Input matrix A is not invertible. Cannot compute Schur complement.'	)

   return mat_c - mat_b.T @ a_inv @ mat_b



class 				lowerCAmelCase_		(  unittest.TestCase							):
       def 					snake_case_       (			self       )     ->		None:
          UpperCamelCase    :  str							=	np.array([[1, 2, 1], [2, 1, 2], [3, 2, 4]]       )
          UpperCamelCase    :  List[Any]							=	np.array([[0, 3], [3, 0], [2, 3]]       )
          UpperCamelCase    :  Tuple							=	np.array([[2, 1], [6, 3]]       )

          UpperCamelCase    :  Optional[Any]							=	schur_complement(SCREAMING_SNAKE_CASE_,			SCREAMING_SNAKE_CASE_,			SCREAMING_SNAKE_CASE_       )

          UpperCamelCase    :  Optional[Any]							=	np.block([[a, b], [b.T, c]]       )

          UpperCamelCase    :  Optional[int]							=	np.linalg.det(SCREAMING_SNAKE_CASE_       )
          UpperCamelCase    :  str							=	np.linalg.det(SCREAMING_SNAKE_CASE_       )
          UpperCamelCase    :  int							=	np.linalg.det(SCREAMING_SNAKE_CASE_       )

          self.assertAlmostEqual(SCREAMING_SNAKE_CASE_,			det_a * det_s       )
       def 					snake_case_       (			self       )     ->		None:
          UpperCamelCase    :  Tuple							=	np.array([[1, 2, 1], [2, 1, 2], [3, 2, 4]]       )
          UpperCamelCase    :  Dict							=	np.array([[0, 3], [3, 0], [2, 3]]       )
          UpperCamelCase    :  str							=	np.array([[2, 1], [6, 3]]       )

          with self.assertRaises(SCREAMING_SNAKE_CASE_       ):
             schur_complement(SCREAMING_SNAKE_CASE_,			SCREAMING_SNAKE_CASE_,			SCREAMING_SNAKE_CASE_       )






       def 					snake_case_       (			self       )     ->		None:
          UpperCamelCase    :  Dict							=	np.array([[1, 2, 1], [2, 1, 2], [3, 2, 4]]       )
          UpperCamelCase    :  Optional[Any]							=	np.array([[0, 3], [3, 0], [2, 3]]       )
          UpperCamelCase    :  str							=	np.array([[2, 1, 3], [6, 3, 5]]       )

          with self.assertRaises(SCREAMING_SNAKE_CASE_       ):
             schur_complement(SCREAMING_SNAKE_CASE_,			SCREAMING_SNAKE_CASE_,			SCREAMING_SNAKE_CASE_       )


if __name__ == "__main__":
    import doctest

    doctest.testmod()
    unittest.main()








import argparse
import json

from tqdm import tqdm
def 		UpperCamelCase	(   )	->     Optional[int]:
   UpperCamelCase    :  List[Any]							=	argparse.ArgumentParser()

   # Required parameters
   parser.add_argument(
       '--src_path'       ,     type=snake_case__       ,     default='biencoder-nq-dev.json'       ,     help='Path to raw DPR training data'       ,     )
   parser.add_argument(
       '--evaluation_set'       ,     type=snake_case__       ,     help='where to store parsed evaluation_set file'       ,     )
   parser.add_argument(
       '--gold_data_path'       ,     type=snake_case__       ,     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(snake_case__	)
      for dpr_record in tqdm(snake_case__	):
         UpperCamelCase    :  Union[str, Any]							=	dpr_record['question']
         UpperCamelCase    :  Dict							=	[context['title'] for context in dpr_record['positive_ctxs']]
         eval_file.write(question + '\n'	)
         gold_file.write('\t'.join(snake_case__	) + '\n'	)


if __name__ == "__main__":
    main()



