






"""simple docstring"""







from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments


def      UpperCamelCase       ( )     ->       Optional[Any]:
				lowercase    :      Optional[int]       = HfArgumentParser(lowerCAmelCase__ )
				lowercase    :      Tuple       = parser.parse_args_into_dataclasses()[0]
				lowercase    :      List[Any]       = TensorFlowBenchmark(args=lowerCAmelCase__ )
				try:
								lowercase    :      List[str]       = parser.parse_args_into_dataclasses()[0]
				except ValueError as e:
								lowercase    :      Any       = """Arg --no_{0} is no longer used, please use --no-{0} instead."""
								lowercase    :      str       = """ """.join(str(lowerCAmelCase__ ).split(""" """ )[:-1] )
								lowercase    :      List[Any]       = """"""
								lowercase    :      Dict       = eval(str(lowerCAmelCase__ ).split(""" """ )[-1] )
								lowercase    :      List[Any]       = []
								for arg in depreciated_args:
												# arg[2:] removes '--'
												if arg[2:] in TensorFlowBenchmark.deprecated_args:
																# arg[5:] removes '--no_'
																full_error_msg += arg_error_msg.format(arg[5:] )
												else:
																wrong_args.append(lowerCAmelCase__ )
								if len(lowerCAmelCase__ ) > 0:
												lowercase    :      Any       = full_error_msg + begin_error_msg + str(lowerCAmelCase__ )
								raise ValueError(lowerCAmelCase__ )
				benchmark.run()


if __name__ == "__main__":
				main()

"""simple docstring"""






from dataclasses import dataclass, field
from typing import ClassVar, Dict

from ..features import Features, Sequence, Value
from .base import TaskTemplate





@dataclass(frozen=lowerCAmelCase      )
class 					_A		(			lowerCAmelCase      ):
      # `task` is not a ClassVar since we want it to be part of the `asdict` output for JSON serialization
      snake_case__     :  str				    =      field(default='question-answering-extractive'    ,       metadata={'include_in_asdict_even_if_is_default': True}      )
      snake_case__     :  ClassVar[Features]				    =      Features({'question': Value('string'      ), 'context': Value('string'      )}      )
      snake_case__     :  ClassVar[Features]				    =      Features(
          {
              'answers': Sequence(
                  {
                      'text': Value('string'      ),
                      'answer_start': Value('int32'      ),
                  }      )
          }      )
      snake_case__     :  str				    =      "question"
      snake_case__     :  str				    =      "context"
      snake_case__     :  str				    =      "answers"

      @property
      def 							A__			(		self		):







            """simple docstring"""



            return {self.question_column: "question", self.context_column: "context", self.answers_column: "answers"}



