

import argparse
import json
import re
import string
import sys
from collections import Counter


def 			__UpperCamelCase    (lowerCAmelCase					:  Tuple     )     ->  Optional[int]:





      def remove_articles(lowerCAmelCase					:  Any     ):
            return re.sub(r'\b(a|an|the)\b',    ' ',    __a     )

      def white_space_fix(lowerCAmelCase					:  Optional[int]     ):
            return " ".join(text.split()     )

      def remove_punc(lowerCAmelCase					:  Any     ):
            A    =				set(string.punctuation     )
            return "".join(ch for ch in text if ch not in exclude     )

      def lower(lowerCAmelCase					:  Optional[Any]     ):
            return text.lower()

      return white_space_fix(remove_articles(remove_punc(lower(__a     )     )     )     )


def 			__UpperCamelCase    (lowerCAmelCase					:  Optional[Any],    lowerCAmelCase					:  Dict     )     ->  str:
      A    =				normalize_answer(__a     ).split()
      A    =				normalize_answer(__a     ).split()
      A    =				Counter(__a     ) & Counter(__a     )
      A    =				sum(common.values()     )
      if num_same == 0:
            return 0
      A    =				1.0 * num_same / len(__a     )
      A    =				1.0 * num_same / len(__a     )
      A    =				(2 * precision * recall) / (precision + recall)
      return fa


def 			__UpperCamelCase    (lowerCAmelCase					:  int,    lowerCAmelCase					:  Optional[int]     )     ->  Tuple:
      return normalize_answer(__a     ) == normalize_answer(__a     )


def 			__UpperCamelCase    (lowerCAmelCase					:  Dict,    lowerCAmelCase					:  str,    lowerCAmelCase					:  Tuple     )     ->  str:
      A    =				[]
      for ground_truth in ground_truths:
            A    =				metric_fn(__a,    __a     )
            scores_for_ground_truths.append(__a     )
      return max(__a     )


def 			__UpperCamelCase    (lowerCAmelCase					:  List[Any],    lowerCAmelCase					:  Optional[int]     )     ->  Dict:
      A    =				0
      A    =				[]
      for passage in dataset:
            for qa in passage["qas"]:
                  total += 1
                  if qa["id"] not in predictions:
                        A    =				f'''Unanswered question {qa["id"]} will receive score 0.'''
                        print(__a,    file=sys.stderr     )
                        continue

                  A    =				[x['''text'''] for x in qa['''answers''']]
                  A    =				predictions[qa['''id''']]

                  A    =				metric_max_over_ground_truths(__a,    __a,    __a     )
                  if int(_exact_match     ) == 1:
                        correct_ids.append(qa['id']     )
                  exact_match += _exact_match

                  fa += metric_max_over_ground_truths(__a,    __a,    __a     )

      A    =				exact_match / total
      A    =				fa / total

      return {"exact_match": exact_match, "f1": fa}, correct_ids


if __name__ == "__main__":
  _UpperCAmelCase    	=			"1.0"
  _UpperCAmelCase    	=			argparse.ArgumentParser("Official evaluation script for ReCoRD v1.0.")
  parser.add_argument("data_file", help="The dataset file in JSON format.")
  parser.add_argument("pred_file", help="The model prediction file in JSON format.")
  parser.add_argument("--output_correct_ids", action="store_true", help="Output the correctly answered query IDs.")
  _UpperCAmelCase    	=			parser.parse_args()

  with open(args.data_file) as data_file:
    _UpperCAmelCase    	=			json.load(data_file)
    if dataset_json["version"] != expected_version:
      print(
          F'''Evaluation expects v-{expected_version}, but got dataset with v-{dataset_json["version"]}''',
          file=sys.stderr,
      )
    _UpperCAmelCase    	=			dataset_json["data"]

  with open(args.pred_file) as pred_file:
    _UpperCAmelCase    	=			json.load(pred_file)

  _UpperCAmelCase	,						_UpperCAmelCase    	=			evaluate(dataset, predictions)

  if args.output_correct_ids:
    print(F'''Output {len(correct_ids)} correctly answered question IDs.''')
    with open("correct_ids.json", "w") as f:
      json.dump(correct_ids, f)






from ..utils import requires_backends


_UpperCAmelCase    	=			None



class        _UpperCAmelCase :
  '''simple docstring'''







  def __init__( self	: List[str]		,						*UpperCamelCase__	: str		,						**UpperCamelCase__	: Any ):
        requires_backends(self		,						['detectron2'] )







  @classmethod
  def 	UpperCamelCase       ( cls	: Dict		,						*UpperCamelCase__	: Tuple		,						**UpperCamelCase__	: List[Any] ):
        requires_backends(cls		,						['detectron2'] )



