






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







def 						a_      (__A			)							->	Dict:



					"""simple docstring"""

					def remove_articles(__A			):
										return re.sub(r"\b(a|an|the)\b"							,					" "							,					__A			)

					def white_space_fix(__A			):
										return " ".join(text.split()			)

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

					def lower(__A			):
										return text.lower()

					return white_space_fix(remove_articles(remove_punc(lower(__A			)			)			)			)







def 						a_      (__A							,					__A			)							->	List[Any]:



					"""simple docstring"""
					__a				:	Dict			=				normalize_answer(__A			).split()
					__a				:	str			=				normalize_answer(__A			).split()
					__a				:	List[str]			=				Counter(__A			) & Counter(__A			)
					__a				:	str			=				sum(common.values()			)
					if num_same == 0:
										return 0
					__a				:	Any			=				1.0 * num_same / len(__A			)
					__a				:	Dict			=				1.0 * num_same / len(__A			)
					__a				:	Union[str, Any]			=				(2 * precision * recall) / (precision + recall)
					return fa







def 						a_      (__A							,					__A			)							->	str:



					"""simple docstring"""
					return normalize_answer(__A			) == normalize_answer(__A			)







def 						a_      (__A							,					__A							,					__A			)							->	List[str]:



					"""simple docstring"""
					__a				:	Dict			=				[]
					for ground_truth in ground_truths:
										__a				:	List[Any]			=				metric_fn(__A							,					__A			)
										scores_for_ground_truths.append(__A			)
					return max(__A			)







def 						a_      (__A							,					__A			)							->	Optional[int]:



					"""simple docstring"""
					__a				:	int			=				0
					__a				:	Tuple			=				[]
					for passage in dataset:
										for qa in passage["qas"]:
															total += 1
															if qa["id"] not in predictions:
																				__a				:	List[Any]			=				f'Unanswered question {qa["id"]} will receive score 0.'
																				print(__A							,					file=sys.stderr			)
																				continue

															__a				:	Optional[Any]			=				[x["text"] for x in qa["answers"]]
															__a				:	Optional[int]			=				predictions[qa["id"]]

															__a				:	Tuple			=				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				:	str			=				exact_match / total
					__a				:	Dict			=				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)













import unittest
from dataclasses import dataclass
from typing import Optional

from transformers.utils import ModelOutput




@dataclass
class        snake_case_					(						__UpperCamelCase			):

						"""simple docstring"""



						snake_case__   					=			42
						snake_case__   					=			None
						snake_case__   					=			None




class        snake_case_					(						unittest.TestCase			):

						"""simple docstring"""



						def 					UpperCAmelCase__				(self:				Optional[Any]      )						->    Tuple:




											'''simple docstring'''



											__a				:	List[str]			=				ModelOutputTest(a=30      )
											self.assertEqual(x.a   ,				30      )
											self.assertIsNone(x.b      )
											self.assertIsNone(x.c      )
											with self.assertRaises(__UpperCAmelCase      ):
																__a				:	Tuple			=				x.d



						def 					UpperCAmelCase__				(self:				Dict      )						->    Union[str, Any]:




											'''simple docstring'''



											__a				:	Union[str, Any]			=				ModelOutputTest(a=30   ,				b=10      )
											self.assertEqual(x[0]   ,				30      )
											self.assertEqual(x[1]   ,				10      )
											self.assertEqual(x[:2]   ,				(30, 10)      )
											self.assertEqual(x[:]   ,				(30, 10)      )

											__a				:	int			=				ModelOutputTest(a=30   ,				c=10      )
											self.assertEqual(x[0]   ,				30      )
											self.assertEqual(x[1]   ,				10      )
											self.assertEqual(x[:2]   ,				(30, 10)      )
											self.assertEqual(x[:]   ,				(30, 10)      )



						def 					UpperCAmelCase__				(self:				Optional[Any]      )						->    List[Any]:




											'''simple docstring'''



											__a				:	Optional[Any]			=				ModelOutputTest(a=30   ,				b=10      )
											self.assertEqual(x["a"]   ,				30      )
											self.assertEqual(x["b"]   ,				10      )
											with self.assertRaises(__UpperCAmelCase      ):
																__a				:	List[str]			=				x["c"]

											__a				:	Union[str, Any]			=				ModelOutputTest(a=30   ,				c=10      )
											self.assertEqual(x["a"]   ,				30      )
											self.assertEqual(x["c"]   ,				10      )
											with self.assertRaises(__UpperCAmelCase      ):
																__a				:	int			=				x["b"]



						def 					UpperCAmelCase__				(self:				Union[str, Any]      )						->    Optional[int]:




											'''simple docstring'''



											__a				:	Union[str, Any]			=				ModelOutputTest(a=30      )
											self.assertEqual(list(x.keys()      )   ,				["a"]      )
											self.assertEqual(list(x.values()      )   ,				[30]      )
											self.assertEqual(list(x.items()      )   ,				[("a", 30)]      )
											self.assertEqual(list(__UpperCAmelCase      )   ,				["a"]      )

											__a				:	List[str]			=				ModelOutputTest(a=30   ,				b=10      )
											self.assertEqual(list(x.keys()      )   ,				["a", "b"]      )
											self.assertEqual(list(x.values()      )   ,				[30, 10]      )
											self.assertEqual(list(x.items()      )   ,				[("a", 30), ("b", 10)]      )
											self.assertEqual(list(__UpperCAmelCase      )   ,				["a", "b"]      )

											__a				:	str			=				ModelOutputTest(a=30   ,				c=10      )
											self.assertEqual(list(x.keys()      )   ,				["a", "c"]      )
											self.assertEqual(list(x.values()      )   ,				[30, 10]      )
											self.assertEqual(list(x.items()      )   ,				[("a", 30), ("c", 10)]      )
											self.assertEqual(list(__UpperCAmelCase      )   ,				["a", "c"]      )

											with self.assertRaises(__UpperCAmelCase      ):
																__a				:	Dict			=				x.update({"d": 20}      )
											with self.assertRaises(__UpperCAmelCase      ):
																del x["a"]
											with self.assertRaises(__UpperCAmelCase      ):
																__a				:	Any			=				x.pop("a"      )
											with self.assertRaises(__UpperCAmelCase      ):
																__a				:	Any			=				x.setdefault("d"   ,				32      )



						def 					UpperCAmelCase__				(self:				Optional[Any]      )						->    Optional[Any]:




											'''simple docstring'''



											__a				:	Optional[Any]			=				ModelOutputTest(a=30      )
											__a				:	int			=				10
											self.assertEqual(x.a   ,				10      )
											self.assertEqual(x["a"]   ,				10      )



						def 					UpperCAmelCase__				(self:				Optional[Any]      )						->    Any:




											'''simple docstring'''



											__a				:	Optional[int]			=				ModelOutputTest(a=30      )
											__a				:	int			=				10
											self.assertEqual(x.a   ,				10      )
											self.assertEqual(x["a"]   ,				10      )



						def 					UpperCAmelCase__				(self:				List[str]      )						->    Any:




											'''simple docstring'''



											__a				:	Dict			=				ModelOutputTest({"a": 30, "b": 10}      )
											self.assertEqual(list(x.keys()      )   ,				["a", "b"]      )
											self.assertEqual(x.a   ,				30      )
											self.assertEqual(x.b   ,				10      )



						def 					UpperCAmelCase__				(self:				Optional[Any]      )						->    List[str]:




											'''simple docstring'''



											__a				:	List[Any]			=				ModelOutputTest([("a", 30), ("b", 10)]      )
											self.assertEqual(list(x.keys()      )   ,				["a", "b"]      )
											self.assertEqual(x.a   ,				30      )
											self.assertEqual(x.b   ,				10      )

											with self.assertRaises(__UpperCAmelCase      ):
																__a				:	List[Any]			=				ModelOutputTest([("a", 30), (10, 10)]      )

											__a				:	Optional[Any]			=				ModelOutputTest(a=(30, 30)      )
											self.assertEqual(list(x.keys()      )   ,				["a"]      )
											self.assertEqual(x.a   ,				(30, 30)      )





