"""simple docstring"""




import argparse
import json
import re
import string
import sys

import numpy as np


UpperCAmelCase       :    Optional[int]									=			0.5



def 				__a       (			_lowercase							, _lowercase						):







					"""simple docstring"""





					lowerCamelCase__		:   Optional[int]  				=					['.', ',', ';', ':']

					for token in remove_tokens:
										lowerCamelCase__		:   Optional[Any]  				=					ground_truth.replace(__UpperCAmelCase							, ''''''						)
										lowerCamelCase__		:   Any  				=					prediction.replace(__UpperCAmelCase							, ''''''						)

					lowerCamelCase__		:   Optional[Any]  				=					ground_truth.lower(), prediction.lower()
					lowerCamelCase__		:   Tuple  				=					ground_truth.replace('''/'''							, ''' '''						), prediction.replace('''/'''							, ''' '''						)
					lowerCamelCase__		:   Tuple  				=					set(ground_truth.split(''' '''						)						), set(prediction.split(''' '''						)						)

					lowerCamelCase__		:   Union[str, Any]  				=					ground_truth.intersection(__UpperCAmelCase						)
					lowerCamelCase__		:   str  				=					ground_truth.union(__UpperCAmelCase						)
					lowerCamelCase__		:   str  				=					len(__UpperCAmelCase						) / len(__UpperCAmelCase						)
					return jaccard



def 				__a       (			_lowercase						):







					"""simple docstring"""





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

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

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

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

					return white_space_fix(remove_articles(remove_punc(lower(__UpperCAmelCase						)						)						)						)



def 				__a       (			_lowercase							, _lowercase							, _lowercase						):







					"""simple docstring"""





					lowerCamelCase__		:   int  				=					0, 0, 0

					lowerCamelCase__		:   Dict  				=					'Parties' in qa_id

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

															if not match_found:
																				fp += 1

					lowerCamelCase__		:   str  				=					tp / (tp + fp) if tp + fp > 0 else np.nan
					lowerCamelCase__		:   Optional[Any]  				=					tp / (tp + fn) if tp + fn > 0 else np.nan

					return precision, recall



def 				__a       (			_lowercase						):







					"""simple docstring"""





					lowerCamelCase__		:   List[str]  				=					precisions[::-1]
					for i in range(1							, len(__UpperCAmelCase						)						):
										lowerCamelCase__		:   List[Any]  				=					max(precision_best[i - 1]							, precision_best[i]						)
					lowerCamelCase__		:   List[str]  				=					precision_best[::-1]
					return precisions



def 				__a       (			_lowercase							, _lowercase						):







					"""simple docstring"""





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



def 				__a       (			_lowercase							, _lowercase							, _lowercase						):







					"""simple docstring"""





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



def 				__a       (			_lowercase							, _lowercase						):







					"""simple docstring"""





					return normalize_answer(__UpperCAmelCase						) == normalize_answer(__UpperCAmelCase						)



def 				__a       (			_lowercase							, _lowercase							, _lowercase						):







					"""simple docstring"""





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



def 				__a       (			_lowercase							, _lowercase						):







					"""simple docstring"""





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

																				precisions.append(__UpperCAmelCase						)
																				recalls.append(__UpperCAmelCase						)

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

																				exact_match += metric_max_over_ground_truths(__UpperCAmelCase							, __UpperCAmelCase							, __UpperCAmelCase						)

					lowerCamelCase__		:   int  				=					[x for _, x in sorted(zip(__UpperCAmelCase							, __UpperCAmelCase						)						)]
					recalls.sort()

					lowerCamelCase__		:   Tuple  				=					100.0 * fa / total
					lowerCamelCase__		:   Tuple  				=					100.0 * exact_match / total
					lowerCamelCase__		:   Tuple  				=					get_aupr(__UpperCAmelCase							, __UpperCAmelCase						)

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







"""simple docstring"""







def   __lowerCAmelCase(		__UpperCAmelCase  ,__UpperCAmelCase      ):






	"""simple docstring"""





	if n == 0:
		return 1

	elif n % 2 == 1:
		return binary_exponentiation(__UpperCAmelCase  ,n - 1      ) * a

	else:
		_lowercase			:     Dict      					=				binary_exponentiation(__UpperCAmelCase  ,n / 2      )
		return b * b


if __name__ == "__main__":
						try:
												SCREAMING_SNAKE_CASE						=    int(input('Enter Base : ').strip())
												SCREAMING_SNAKE_CASE						=    int(input('Enter Power : ').strip())
						except ValueError:
												print('Invalid literal for integer')

						SCREAMING_SNAKE_CASE						=    binary_exponentiation(BASE, POWER)
						print(f"""{BASE}^({POWER}) : {RESULT}""")



