




"""simple docstring"""




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







def       __UpperCAmelCase      (				__UpperCamelCase					):






			def remove_articles(__UpperCamelCase					):
						return re.sub(R'''\b(a|an|the)\b'''					,							''' '''					,							snake_case__					)

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

			def remove_punc(__UpperCamelCase					):
						__lowercase	:       Optional[Any]				=   set(string.punctuation					)
						return "".join(ch for ch in text if ch not in exclude					)

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

			return white_space_fix(remove_articles(remove_punc(lower(snake_case__					)					)					)					)







def       __UpperCAmelCase      (				__UpperCamelCase					,							__UpperCamelCase					):
			__lowercase	:       Dict				=   normalize_answer(snake_case__					).split()
			__lowercase	:       Dict				=   normalize_answer(snake_case__					).split()
			__lowercase	:       Any				=   Counter(snake_case__					) & Counter(snake_case__					)
			__lowercase	:       str				=   sum(common.values()					)
			if num_same == 0:
						return 0
			__lowercase	:       str				=   1.0 * num_same / len(snake_case__					)
			__lowercase	:       Tuple				=   1.0 * num_same / len(snake_case__					)
			__lowercase	:       Union[str, Any]				=   (2 * precision * recall) / (precision + recall)
			return fa







def       __UpperCAmelCase      (				__UpperCamelCase					,							__UpperCamelCase					):
			return normalize_answer(snake_case__					) == normalize_answer(snake_case__					)







def       __UpperCAmelCase      (				__UpperCamelCase					,							__UpperCamelCase					,							__UpperCamelCase					):
			__lowercase	:       List[Any]				=   []
			for ground_truth in ground_truths:
						__lowercase	:       Dict				=   metric_fn(snake_case__					,							snake_case__					)
						scores_for_ground_truths.append(snake_case__					)
			return max(snake_case__					)







def       __UpperCAmelCase      (				__UpperCamelCase					,							__UpperCamelCase					):
			__lowercase	:       List[Any]				=   0
			for article in dataset:
						for paragraph in article["paragraphs"]:
									for qa in paragraph["qas"]:
												total += 1
												if qa["id"] not in predictions:
															__lowercase	:       List[Any]				=   '''Unanswered question ''' + qa['''id'''] + ''' will receive score 0.'''
															print(snake_case__					,							file=sys.stderr					)
															continue
												__lowercase	:       Dict				=   [x['''text'''] for x in qa['''answers''']]
												__lowercase	:       Union[str, Any]				=   predictions[qa['''id''']]
												exact_match += metric_max_over_ground_truths(snake_case__					,							snake_case__					,							snake_case__					)
												fa += metric_max_over_ground_truths(snake_case__					,							snake_case__					,							snake_case__					)

			__lowercase	:       List[str]				=   100.0 * exact_match / total
			__lowercase	:       Optional[int]				=   100.0 * fa / total

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


if __name__ == "__main__":
							a_            =   '1.1'
							a_            =   argparse.ArgumentParser(description='Evaluation for SQuAD ' + expected_version)
							parser.add_argument('dataset_file', help='Dataset file')
							parser.add_argument('prediction_file', help='Prediction File')
							a_            =   parser.parse_args()
							with open(args.dataset_file) as dataset_file:
														a_            =   json.load(dataset_file)
														if dataset_json["version"] != expected_version:
																					print(
																					    'Evaluation expects v-' + expected_version + ', but got dataset with v-' + dataset_json['version'],
																					    file=sys.stderr,
																					)
														a_            =   dataset_json['data']
							with open(args.prediction_file) as prediction_file:
														a_            =   json.load(prediction_file)
							print(json.dumps(evaluate(dataset, predictions)))









"""simple docstring"""




from collections.abc import Callable

a_            =   Callable[[float], float]  # type alias for a real -> real function







def       __UpperCAmelCase      (				__UpperCamelCase					,							__UpperCamelCase					,							__UpperCamelCase					,							):
			__lowercase	:       str				=   float(__UpperCamelCase					)
			while True:
						try:
									__lowercase	:       Dict				=   prev_guess - function(__UpperCamelCase					) / derivative(__UpperCamelCase					)
						except ZeroDivisionError:
									raise ZeroDivisionError('''Could not find root'''					) from None
						if abs(prev_guess - next_guess					) < 10**-5:
									return next_guess
						__lowercase	:       List[Any]				=   next_guess







def       __UpperCAmelCase      (				__UpperCamelCase					):
			return (x**3) - (2 * x) - 5







def       __UpperCAmelCase      (				__UpperCamelCase					):
			return 3 * (x**2) - 2


if __name__ == "__main__":
			print(newton(f, fa, 3))



