

'''simple docstring'''

import os
from collections import namedtuple

import pytest

from datasets import ClassLabel, Features, Sequence, Value
from datasets.commands.test import TestCommand
from datasets.info import DatasetInfo, DatasetInfosDict


lowercase__         =      namedtuple(
    "_TestCommandArgs",
    [
        "dataset",
        "name",
        "cache_dir",
        "data_dir",
        "all_configs",
        "save_infos",
        "ignore_verifications",
        "force_redownload",
        "clear_cache",
    ],
    defaults=[None, None, None, False, False, False, False, False],
)




def 				UpperCamelCase(					UpperCAmelCase_  ,	UpperCAmelCase_     ):
 return (abs(source - target     ) / target) < 0.01




@pytest.mark.integration
def 				UpperCamelCase(					UpperCAmelCase_     ):
 UpperCAmelCase	:     Union[str, Any]						 =			_TestCommandArgs(dataset=UpperCAmelCase_  ,	all_configs=UpperCAmelCase_  ,	save_infos=UpperCAmelCase_     )
 UpperCAmelCase	:     Dict						 =			TestCommand(*UpperCAmelCase_     )
 test_command.run()
 UpperCAmelCase	:     Optional[int]						 =			os.path.join(UpperCAmelCase_  ,	'README.md'     )
 assert os.path.exists(UpperCAmelCase_     )
 UpperCAmelCase	:     List[str]						 =			DatasetInfosDict.from_directory(UpperCAmelCase_     )
 UpperCAmelCase	:     int						 =			DatasetInfosDict(
     {
         'default': DatasetInfo(
             features=Features(
                 {
                     'tokens': Sequence(Value('string'     )     ),
                     'ner_tags': Sequence(
                         ClassLabel(names=['O', 'B-PER', 'I-PER', 'B-ORG', 'I-ORG', 'B-LOC', 'I-LOC']     )     ),
                     'langs': Sequence(Value('string'     )     ),
                     'spans': Sequence(Value('string'     )     ),
                 }     )  ,	splits=[
                 {
                     'name': 'train',
                     'num_bytes': 2_35_15_63,
                     'num_examples': 1_00_00,
                 },
                 {
                     'name': 'validation',
                     'num_bytes': 23_84_18,
                     'num_examples': 10_00,
                 },
             ]  ,	download_size=3_94_06_80  ,	dataset_size=2_58_99_81  ,	)
     }     )
 assert dataset_infos.keys() == expected_dataset_infos.keys()
 for key in DatasetInfo._INCLUDED_INFO_IN_YAML:
  UpperCAmelCase ,			UpperCAmelCase	:     Tuple						 =			getattr(dataset_infos['default']  ,	UpperCAmelCase_     ), getattr(expected_dataset_infos['default']  ,	UpperCAmelCase_     )
  if key == "num_bytes":
   assert is_apercent_close(UpperCAmelCase_  ,	UpperCAmelCase_     )
  elif key == "splits":
   assert list(UpperCAmelCase_     ) == list(UpperCAmelCase_     )
   for split in result:
    assert result[split].name == expected[split].name
    assert result[split].num_examples == expected[split].num_examples
    assert is_apercent_close(result[split].num_bytes  ,	expected[split].num_bytes     )
  else:
   result == expected







'''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()




