
import argparse
import json

from tqdm import tqdm




def 	_SCREAMING_SNAKE_CASE					(		)					->    int:






							'''simple docstring'''





							__UpperCamelCase	:   int			   =					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"						,  )
							__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	:   Tuple			   =					json.load(_lowerCamelCase)
														for dpr_record in tqdm(_lowerCamelCase):
																					__UpperCamelCase	:   List[str]			   =					dpr_record["question"]
																					__UpperCamelCase	:   List[Any]			   =					[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


lowercase  :					List[str]													=       {'configuration_vit_msn': ['VIT_MSN_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ViTMSNConfig']}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowercase  :					Optional[Any]													=       [
		    'VIT_MSN_PRETRAINED_MODEL_ARCHIVE_LIST',
		    'ViTMSNModel',
		    'ViTMSNForImageClassification',
		    'ViTMSNPreTrainedModel',
		]

if TYPE_CHECKING:
		from .configuration_vit_msn import VIT_MSN_PRETRAINED_CONFIG_ARCHIVE_MAP, ViTMSNConfig

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_vit_msn import (
				    VIT_MSN_PRETRAINED_MODEL_ARCHIVE_LIST,
				    ViTMSNForImageClassification,
				    ViTMSNModel,
				    ViTMSNPreTrainedModel,
				)

else:
		import sys

		lowercase  :					Optional[Any]													=       _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)