






"""simple docstring"""


import argparse
import json

from tqdm import tqdm




def       snake_case  ():







  '''simple docstring'''

  a					:      Any    =       argparse.ArgumentParser()

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


if __name__ == "__main__":
   main()












"""simple docstring"""


import os
import unittest

from transformers.models.bartpho.tokenization_bartpho import VOCAB_FILES_NAMES, BartphoTokenizer
from transformers.testing_utils import get_tests_dir

from ...test_tokenization_common import TokenizerTesterMixin


_UpperCamelCase    :   int   			=						get_tests_dir('fixtures/test_sentencepiece_bpe.model')






class 						snake_case  (  UpperCAmelCase       ,			unittest.TestCase	):
    __magic_name__   					=					BartphoTokenizer
    __magic_name__   					=					False
    __magic_name__   					=					True





    def     lowerCamelCase__				(							self     : List[Any]      ):


      '''simple docstring'''




      super().setUp()

      a					:      Any    =       ['▁This', '▁is', '▁a', '▁t', 'est']
      a					:      List[Any]    =       dict(zip(A    ,		range(len(A      )      )      )      )
      a					:      int    =       {'unk_token': '<unk>'}

      a					:      Tuple    =       os.path.join(self.tmpdirname    ,		VOCAB_FILES_NAMES['monolingual_vocab_file']      )
      with open(self.monolingual_vocab_file    ,		'w'    ,		encoding='utf-8'      ) as fp:
        for token in vocab_tokens:
          fp.write(F'''{token} {vocab_tokens[token]}\n'''      )

      a					:      Optional[int]    =       BartphoTokenizer(A    ,		self.monolingual_vocab_file    ,		**self.special_tokens_map      )
      tokenizer.save_pretrained(self.tmpdirname      )





    def     lowerCamelCase__				(							self     : Dict    ,		**A     : str      ):


      '''simple docstring'''




      kwargs.update(self.special_tokens_map      )
      return BartphoTokenizer.from_pretrained(self.tmpdirname    ,		**A      )





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


      '''simple docstring'''




      a					:      Tuple    =       'This is a là test'
      a					:      List[Any]    =       'This is a<unk><unk> test'
      return input_text, output_text





    def     lowerCamelCase__				(							self     : Optional[Any]      ):


      '''simple docstring'''




      a					:      Tuple    =       BartphoTokenizer(A    ,		self.monolingual_vocab_file    ,		**self.special_tokens_map      )
      a					:      int    =       'This is a là test'
      a					:      int    =       '▁This ▁is ▁a ▁l à ▁t est'.split()
      a					:      str    =       tokenizer.tokenize(A      )
      self.assertListEqual(A    ,		A      )

      a					:      Union[str, Any]    =       tokens + [tokenizer.unk_token]
      a					:      Dict    =       [4, 5, 6, 3, 3, 7, 8, 3]
      self.assertListEqual(tokenizer.convert_tokens_to_ids(A      )    ,		A      )




