





import argparse
import json
import re
import string
import sys

import numpy as np


UpperCamelCase__ :			Dict       	=			0.5




def  A_(      A					,   A ):
	UpperCAmelCase_		    =  [""".""", """,""", """;""", """:"""]

	for token in remove_tokens:
		UpperCAmelCase_		    =  ground_truth.replace(lowerCAmelCase__					,   """""" )
		UpperCAmelCase_		    =  prediction.replace(lowerCAmelCase__					,   """""" )

	UpperCAmelCase_    ,						UpperCAmelCase_		    =  ground_truth.lower(), prediction.lower()
	UpperCAmelCase_    ,						UpperCAmelCase_		    =  ground_truth.replace("""/"""					,   """ """ ), prediction.replace("""/"""					,   """ """ )
	UpperCAmelCase_    ,						UpperCAmelCase_		    =  set(ground_truth.split(""" """ ) ), set(prediction.split(""" """ ) )

	UpperCAmelCase_		    =  ground_truth.intersection(lowerCAmelCase__ )
	UpperCAmelCase_		    =  ground_truth.union(lowerCAmelCase__ )
	UpperCAmelCase_		    =  len(lowerCAmelCase__ ) / len(lowerCAmelCase__ )
	return jaccard




def  A_(      A ):



	def remove_articles(A ):
		return re.sub(R"""\b(a|an|the)\b"""					,   """ """					,   lowerCAmelCase__ )

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

	def remove_punc(A ):
		UpperCAmelCase_		    =  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(lowerCAmelCase__ ) ) ) )




def  A_(      A					,   A					,   A ):
	UpperCAmelCase_    ,						UpperCAmelCase_    ,						UpperCAmelCase_		    =  0, 0, 0

	UpperCAmelCase_		    =  """Parties""" in qa_id

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

			if not match_found:
				fp += 1

	UpperCAmelCase_		    =  tp / (tp + fp) if tp + fp > 0 else np.nan
	UpperCAmelCase_		    =  tp / (tp + fn) if tp + fn > 0 else np.nan

	return precision, recall




def  A_(      A ):
	UpperCAmelCase_		    =  precisions[::-1]
	for i in range(1					,   len(lowerCAmelCase__ ) ):
		UpperCAmelCase_		    =  max(precision_best[i - 1]					,   precision_best[i] )
	UpperCAmelCase_		    =  precision_best[::-1]
	return precisions




def  A_(      A					,   A ):
	UpperCAmelCase_		    =  process_precisions(lowerCAmelCase__ )
	UpperCAmelCase_		    =  np.trapz(lowerCAmelCase__					,   lowerCAmelCase__ )
	if np.isnan(lowerCAmelCase__ ):
		return 0
	return aupr




def  A_(      A					,   A					,   A ):
	UpperCAmelCase_		    =  process_precisions(lowerCAmelCase__ )
	UpperCAmelCase_		    =  0
	for prec, recall in zip(lowerCAmelCase__					,   lowerCAmelCase__ ):
		if recall >= recall_thresh:
			UpperCAmelCase_		    =  prec
			break
	return prec_at_recall




def  A_(      A					,   A ):
	return normalize_answer(lowerCAmelCase__ ) == normalize_answer(lowerCAmelCase__ )




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




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

				precisions.append(lowerCAmelCase__ )
				recalls.append(lowerCAmelCase__ )

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

				exact_match += metric_max_over_ground_truths(lowerCAmelCase__					,   lowerCAmelCase__					,   lowerCAmelCase__ )

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

	UpperCAmelCase_		    =  100.0 * fa / total
	UpperCAmelCase_		    =  100.0 * exact_match / total
	UpperCAmelCase_		    =  get_aupr(lowerCAmelCase__					,   lowerCAmelCase__ )

	UpperCAmelCase_		    =  get_prec_at_recall(lowerCAmelCase__					,   lowerCAmelCase__					,   recall_thresh=0.9 )
	UpperCAmelCase_		    =  get_prec_at_recall(lowerCAmelCase__					,   lowerCAmelCase__					,   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__ :			str       	=			argparse.ArgumentParser(description="""Evaluation for CUAD""")
				parser.add_argument("""dataset_file""", help="""Dataset file""")
				parser.add_argument("""prediction_file""", help="""Prediction File""")
				UpperCamelCase__ :			Optional[int]       	=			parser.parse_args()
				with open(args.dataset_file) as dataset_file:
								UpperCamelCase__ :			Optional[int]       	=			json.load(dataset_file)
								UpperCamelCase__ :			str       	=			dataset_json["data"]
				with open(args.prediction_file) as prediction_file:
								UpperCamelCase__ :			Union[str, Any]       	=			json.load(prediction_file)
				print(json.dumps(evaluate(dataset, predictions)))






'''simple docstring'''






def 						_A					(lowerCAmelCase__	:int					,    lowerCAmelCase__	:int		) ->	int:




     '''simple docstring'''



     if a < b:
          return gcd(lowerCAmelCase__					,    lowerCAmelCase__		)
     if a % b == 0:
          return b
     return gcd(lowerCAmelCase__					,    a % b		)






def 						_A					(lowerCAmelCase__	:int					,    lowerCAmelCase__	:int					,    lowerCAmelCase__	:int		) ->	int:




     '''simple docstring'''



     if y == 0:
          return 1
     _a         =				power(lowerCAmelCase__					,    y // 2					,    lowerCAmelCase__		) % mod
     _a         =				(temp * temp) % mod
     if y % 2 == 1:
          _a         =				(temp * x) % mod
     return temp






def 						_A					(lowerCAmelCase__	:int		) ->	bool:




     '''simple docstring'''



     _a         =				2
     while b < n:
          if gcd(lowerCAmelCase__					,    lowerCAmelCase__		) == 1 and power(lowerCAmelCase__					,    n - 1					,    lowerCAmelCase__		) != 1:
               return False
          b += 1
     return True


if __name__ == "__main__":
 a_       :     Any 							=     int(input("Enter number: ").strip())
 if is_carmichael_number(number):
  print(f'''{number} is a Carmichael Number.''')
 else:
  print(f'''{number} is not a Carmichael Number.''')

