
"""simple docstring"""







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowercase_         =       {
    "configuration_timesformer": ["TIMESFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "TimesformerConfig"],
}

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowercase_         =       [
           "TIMESFORMER_PRETRAINED_MODEL_ARCHIVE_LIST",
           "TimesformerModel",
           "TimesformerForVideoClassification",
           "TimesformerPreTrainedModel",
       ]

if TYPE_CHECKING:
       from .configuration_timesformer import TIMESFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, TimesformerConfig

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_timesformer import (
                  TIMESFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
                  TimesformerForVideoClassification,
                  TimesformerModel,
                  TimesformerPreTrainedModel,
              )

else:
       import sys

       lowercase_         =       _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)



"""simple docstring"""







import argparse
import json

from tqdm import tqdm




def       A_      (       )  ->				str:


     """simple docstring"""







     UpperCAmelCase_    :     List[Any]            =	argparse.ArgumentParser()

     # Required parameters
     parser.add_argument(
         """--src_path"""    ,			type=lowercase    ,			default="""biencoder-nq-dev.json"""    ,			help="""Path to raw DPR training data"""    ,			)
     parser.add_argument(
         """--evaluation_set"""    ,			type=lowercase    ,			help="""where to store parsed evaluation_set file"""    ,			)
     parser.add_argument(
         """--gold_data_path"""    ,			type=lowercase    ,			help="""where to store parsed gold_data_path file"""    ,			)
     UpperCAmelCase_    :     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:
          UpperCAmelCase_    :     List[Any]            =	json.load(lowercase   )
          for dpr_record in tqdm(lowercase   ):
               UpperCAmelCase_    :     List[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(lowercase   ) + """\n"""   )


if __name__ == "__main__":
       main()

