
"""simple docstring"""



import argparse
import json

from tqdm import tqdm






def 						__snake_case	(     ):






							"""simple docstring"""



							_lowerCAmelCase							=      argparse.ArgumentParser()

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


if __name__ == "__main__":
	main()










from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


SCREAMING_SNAKE_CASE			: List[Any]				   =					{
    "configuration_poolformer": [
        "POOLFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "PoolFormerConfig",
        "PoolFormerOnnxConfig",
    ]
}

try:
 if not is_vision_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 SCREAMING_SNAKE_CASE			: List[str]				   =					["PoolFormerFeatureExtractor"]
 SCREAMING_SNAKE_CASE			: List[Any]				   =					["PoolFormerImageProcessor"]

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 SCREAMING_SNAKE_CASE			: List[Any]				   =					[
     "POOLFORMER_PRETRAINED_MODEL_ARCHIVE_LIST",
     "PoolFormerForImageClassification",
     "PoolFormerModel",
     "PoolFormerPreTrainedModel",
 ]


if TYPE_CHECKING:
 from .configuration_poolformer import (
     POOLFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
     PoolFormerConfig,
     PoolFormerOnnxConfig,
 )

 try:
  if not is_vision_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .feature_extraction_poolformer import PoolFormerFeatureExtractor
  from .image_processing_poolformer import PoolFormerImageProcessor

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_poolformer import (
      POOLFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
      PoolFormerForImageClassification,
      PoolFormerModel,
      PoolFormerPreTrainedModel,
  )


else:
 import sys

 SCREAMING_SNAKE_CASE			: str				   =					_LazyModule(__name__, globals()["__file__"], _import_structure)


