



import argparse
import json
import re
import string
import sys

import numpy as np


UpperCamelCase_									=   0.5







def       lowerCamelCase_  (    _a       :						str   ,		_a       :						str    ):



    '''simple docstring'''




    UpperCAmelCase_     :       List[Any]  		=					[""".""", """,""", """;""", """:"""]

    for token in remove_tokens:
        UpperCAmelCase_     :       Dict  		=					ground_truth.replace(_a   ,		""""""    )
        UpperCAmelCase_     :       List[Any]  		=					prediction.replace(_a   ,		""""""    )

    UpperCAmelCase_		, UpperCAmelCase_     :       Any  		=					ground_truth.lower(), prediction.lower()
    UpperCAmelCase_		, UpperCAmelCase_     :       Dict  		=					ground_truth.replace("""/"""   ,		""" """    ), prediction.replace("""/"""   ,		""" """    )
    UpperCAmelCase_		, UpperCAmelCase_     :       Tuple  		=					set(ground_truth.split(""" """    )    ), set(prediction.split(""" """    )    )

    UpperCAmelCase_     :       Tuple  		=					ground_truth.intersection(_a    )
    UpperCAmelCase_     :       Optional[Any]  		=					ground_truth.union(_a    )
    UpperCAmelCase_     :       Tuple  		=					len(_a    ) / len(_a    )
    return jaccard







def       lowerCamelCase_  (    _a       :						Optional[int]    ):



    '''simple docstring'''




    def remove_articles(_a       :						Optional[int]    ):
        return re.sub(r"""\b(a|an|the)\b"""   ,		""" """   ,		_a    )

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

    def remove_punc(_a       :						List[str]    ):
        UpperCAmelCase_     :       Tuple  		=					set(string.punctuation    )
        return "".join(ch for ch in text if ch not in exclude    )

    def lower(_a       :						int    ):
        return text.lower()

    return white_space_fix(remove_articles(remove_punc(lower(_a    )    )    )    )







def       lowerCamelCase_  (    _a       :						Union[str, Any]   ,		_a       :						Optional[int]   ,		_a       :						int    ):



    '''simple docstring'''




    UpperCAmelCase_		, UpperCAmelCase_		, UpperCAmelCase_     :       List[str]  		=					0, 0, 0

    UpperCAmelCase_     :       int  		=					"""Parties""" in qa_id

    # first check if ground truth is empty
    if len(_a    ) == 0:
        if len(_a    ) > 0:
            fp += len(_a    )  # false positive for each one
    else:
        for ground_truth in ground_truths:
            assert len(_a    ) > 0
            # check if there is a match
            UpperCAmelCase_     :       int  		=					False
            for pred in predictions:
                if substr_ok:
                    UpperCAmelCase_     :       int  		=					get_jaccard(_a   ,		_a    ) >= IOU_THRESH or ground_truth in pred
                else:
                    UpperCAmelCase_     :       Tuple  		=					get_jaccard(_a   ,		_a    ) >= IOU_THRESH
                if is_match:
                    UpperCAmelCase_     :       Union[str, Any]  		=					True

            if match_found:
                tp += 1
            else:
                fn += 1

        # now also get any fps by looping through preds
        for pred in predictions:
            # Check if there's a match. if so, don't count (don't want to double count based on the above)
            # but if there's no match, then this is a false positive.
            # (Note: we get the true positives in the above loop instead of this loop so that we don't double count
            # multiple predictions that are matched with the same answer.)
            UpperCAmelCase_     :       List[Any]  		=					False
            for ground_truth in ground_truths:
                assert len(_a    ) > 0
                if substr_ok:
                    UpperCAmelCase_     :       str  		=					get_jaccard(_a   ,		_a    ) >= IOU_THRESH or ground_truth in pred
                else:
                    UpperCAmelCase_     :       Union[str, Any]  		=					get_jaccard(_a   ,		_a    ) >= IOU_THRESH
                if is_match:
                    UpperCAmelCase_     :       str  		=					True

            if not match_found:
                fp += 1

    UpperCAmelCase_     :       Tuple  		=					tp / (tp + fp) if tp + fp > 0 else np.nan
    UpperCAmelCase_     :       Union[str, Any]  		=					tp / (tp + fn) if tp + fn > 0 else np.nan

    return precision, recall







def       lowerCamelCase_  (    _a       :						Optional[int]    ):



    '''simple docstring'''




    UpperCAmelCase_     :       str  		=					precisions[::-1]
    for i in range(1   ,		len(_a    )    ):
        UpperCAmelCase_     :       Dict  		=					max(precision_best[i - 1]   ,		precision_best[i]    )
    UpperCAmelCase_     :       str  		=					precision_best[::-1]
    return precisions







def       lowerCamelCase_  (    _a       :						List[str]   ,		_a       :						str    ):



    '''simple docstring'''




    UpperCAmelCase_     :       Optional[int]  		=					process_precisions(_a    )
    UpperCAmelCase_     :       Tuple  		=					np.trapz(_a   ,		_a    )
    if np.isnan(_a    ):
        return 0
    return aupr







def       lowerCamelCase_  (    _a       :						Union[str, Any]   ,		_a       :						Optional[Any]   ,		_a       :						Union[str, Any]    ):



    '''simple docstring'''




    UpperCAmelCase_     :       Optional[Any]  		=					process_precisions(_a    )
    UpperCAmelCase_     :       List[Any]  		=					0
    for prec, recall in zip(_a   ,		_a    ):
        if recall >= recall_thresh:
            UpperCAmelCase_     :       Union[str, Any]  		=					prec
            break
    return prec_at_recall







def       lowerCamelCase_  (    _a       :						List[Any]   ,		_a       :						Tuple    ):



    '''simple docstring'''




    return normalize_answer(_a    ) == normalize_answer(_a    )







def       lowerCamelCase_  (    _a       :						Optional[int]   ,		_a       :						Optional[Any]   ,		_a       :						Optional[int]    ):



    '''simple docstring'''




    UpperCAmelCase_     :       Dict  		=					0
    for pred in predictions:
        for ground_truth in ground_truths:
            UpperCAmelCase_     :       Tuple  		=					metric_fn(_a   ,		_a    )
            if score == 1:  # break the loop when one prediction matches the ground truth
                break
        if score == 1:
            break
    return score







def       lowerCamelCase_  (    _a       :						Optional[int]   ,		_a       :						List[Any]    ):



    '''simple docstring'''




    UpperCAmelCase_     :       str  		=					0
    UpperCAmelCase_     :       int  		=					[]
    UpperCAmelCase_     :       Any  		=					[]
    for article in dataset:
        for paragraph in article["paragraphs"]:
            for qa in paragraph["qas"]:
                total += 1
                if qa["id"] not in predictions:
                    UpperCAmelCase_     :       str  		=					"""Unanswered question """ + qa["""id"""] + """ will receive score 0."""
                    print(_a   ,		file=sys.stderr    )
                    continue
                UpperCAmelCase_     :       Dict  		=					[x["""text"""] for x in qa["""answers"""]]
                UpperCAmelCase_     :       Any  		=					predictions[qa["""id"""]]
                UpperCAmelCase_		, UpperCAmelCase_     :       List[str]  		=					compute_precision_recall(_a   ,		_a   ,		qa["""id"""]    )

                precisions.append(_a    )
                recalls.append(_a    )

                if precision == 0 and recall == 0:
                    fa += 0
                else:
                    fa += 2 * (precision * recall) / (precision + recall)

                exact_match += metric_max_over_ground_truths(_a   ,		_a   ,		_a    )

    UpperCAmelCase_     :       Any  		=					[x for _, x in sorted(zip(_a   ,		_a    )    )]
    recalls.sort()

    UpperCAmelCase_     :       List[str]  		=					1_0_0.0 * fa / total
    UpperCAmelCase_     :       Tuple  		=					1_0_0.0 * exact_match / total
    UpperCAmelCase_     :       Union[str, Any]  		=					get_aupr(_a   ,		_a    )

    UpperCAmelCase_     :       Optional[Any]  		=					get_prec_at_recall(_a   ,		_a   ,		recall_thresh=0.9    )
    UpperCAmelCase_     :       List[Any]  		=					get_prec_at_recall(_a   ,		_a   ,		recall_thresh=0.8    )

    return {
        "exact_match": exact_match,
        "f1": fa,
        "aupr": aupr,
        "prec_at_80_recall": prec_at_aa_recall,
        "prec_at_90_recall": prec_at_aa_recall,
    }


if __name__ == "__main__":
      UpperCamelCase_									=   argparse.ArgumentParser(description='''Evaluation for CUAD''')
      parser.add_argument('''dataset_file''', help='''Dataset file''')
      parser.add_argument('''prediction_file''', help='''Prediction File''')
      UpperCamelCase_									=   parser.parse_args()
      with open(args.dataset_file) as dataset_file:
            UpperCamelCase_									=   json.load(dataset_file)
            UpperCamelCase_									=   dataset_json['''data''']
      with open(args.prediction_file) as prediction_file:
            UpperCamelCase_									=   json.load(prediction_file)
      print(json.dumps(evaluate(dataset, predictions)))




"""simple docstring"""






import math



def 			A__		(					_UpperCAmelCase    :      int	)							->	bool:

	'''simple docstring'''


	if 1 < number < 4:
		# 2 and 3 are primes
		return True
	elif number < 2 or number % 2 == 0 or number % 3 == 0:
		# Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
		return False

	# All primes number are in format of 6k +/- 1
	for i in range(5				,    int(math.sqrt(_UpperCAmelCase	) + 1	)				,    6	):
		if number % i == 0 or number % (i + 2) == 0:
			return False
	return True



def 			A__		(					_UpperCAmelCase    :      int = 60_08_51_47_51_43	)							->	int:

	'''simple docstring'''


	try:
		snake_case__  :						List[Any]		=      int(_UpperCAmelCase	)
	except (TypeError, ValueError):
		raise TypeError("Parameter n must be int or castable to int."	)
	if n <= 0:
		raise ValueError("Parameter n must be greater than or equal to one."	)
	snake_case__  :						int		=      0
	if is_prime(_UpperCAmelCase	):
		return n
	while n % 2 == 0:
		n //= 2
	if is_prime(_UpperCAmelCase	):
		return n
	for i in range(3				,    int(math.sqrt(_UpperCAmelCase	)	) + 1				,    2	):
		if n % i == 0:
			if is_prime(n // i	):
				snake_case__  :						int		=      n // i
				break
			elif is_prime(_UpperCAmelCase	):
				snake_case__  :						List[Any]		=      i
	return max_number


if __name__ == "__main__":
					print(f"{solution() = }")





