




'''simple docstring'''
import argparse
import json
import re
import string
import sys

import numpy as np


_SCREAMING_SNAKE_CASE =	0.5





def  lowerCamelCase(       SCREAMING_SNAKE_CASE_					,SCREAMING_SNAKE_CASE_    )		->		List[str]:
			A_       		=   ['''.''', ''',''', ''';''', ''':''']

			for token in remove_tokens:
						A_       		=   ground_truth.replace(__a					,''    )
						A_       		=   prediction.replace(__a					,''    )

			A_       		=   ground_truth.lower(), prediction.lower()
			A_       		=   ground_truth.replace('/'					,' '    ), prediction.replace('/'					,' '    )
			A_       		=   set(ground_truth.split(' '    )    ), set(prediction.split(' '    )    )

			A_       		=   ground_truth.intersection(__a    )
			A_       		=   ground_truth.union(__a    )
			A_       		=   len(__a    ) / len(__a    )
			return jaccard





def  lowerCamelCase(       SCREAMING_SNAKE_CASE_    )		->		List[str]:





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

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

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

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

			return white_space_fix(remove_articles(remove_punc(lower(__a    )    )    )    )





def  lowerCamelCase(       SCREAMING_SNAKE_CASE_					,SCREAMING_SNAKE_CASE_					,SCREAMING_SNAKE_CASE_    )		->		List[str]:
			A_       		=   0, 0, 0

			A_       		=   '''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
									A_       		=   False
									for pred in predictions:
												if substr_ok:
															A_       		=   get_jaccard(__a					,__a    ) >= IOU_THRESH or ground_truth in pred
												else:
															A_       		=   get_jaccard(__a					,__a    ) >= IOU_THRESH
												if is_match:
															A_       		=   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.)
									A_       		=   False
									for ground_truth in ground_truths:
												assert len(__a    ) > 0
												if substr_ok:
															A_       		=   get_jaccard(__a					,__a    ) >= IOU_THRESH or ground_truth in pred
												else:
															A_       		=   get_jaccard(__a					,__a    ) >= IOU_THRESH
												if is_match:
															A_       		=   True

									if not match_found:
												fp += 1

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

			return precision, recall





def  lowerCamelCase(       SCREAMING_SNAKE_CASE_    )		->		List[str]:
			A_       		=   precisions[::-1]
			for i in range(1					,len(__a    )    ):
						A_       		=   max(precision_best[i - 1]					,precision_best[i]    )
			A_       		=   precision_best[::-1]
			return precisions





def  lowerCamelCase(       SCREAMING_SNAKE_CASE_					,SCREAMING_SNAKE_CASE_    )		->		Optional[Any]:
			A_       		=   process_precisions(__a    )
			A_       		=   np.trapz(__a					,__a    )
			if np.isnan(__a    ):
						return 0
			return aupr





def  lowerCamelCase(       SCREAMING_SNAKE_CASE_					,SCREAMING_SNAKE_CASE_					,SCREAMING_SNAKE_CASE_    )		->		Dict:
			A_       		=   process_precisions(__a    )
			A_       		=   0
			for prec, recall in zip(__a					,__a    ):
						if recall >= recall_thresh:
									A_       		=   prec
									break
			return prec_at_recall





def  lowerCamelCase(       SCREAMING_SNAKE_CASE_					,SCREAMING_SNAKE_CASE_    )		->		Union[str, Any]:
			return normalize_answer(__a    ) == normalize_answer(__a    )





def  lowerCamelCase(       SCREAMING_SNAKE_CASE_					,SCREAMING_SNAKE_CASE_					,SCREAMING_SNAKE_CASE_    )		->		Any:
			A_       		=   0
			for pred in predictions:
						for ground_truth in ground_truths:
									A_       		=   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(       SCREAMING_SNAKE_CASE_					,SCREAMING_SNAKE_CASE_    )		->		str:
			A_       		=   0
			A_       		=   []
			A_       		=   []
			for article in dataset:
						for paragraph in article["paragraphs"]:
									for qa in paragraph["qas"]:
												total += 1
												if qa["id"] not in predictions:
															A_       		=   '''Unanswered question ''' + qa['''id'''] + ''' will receive score 0.'''
															print(__a					,file=sys.stderr    )
															continue
												A_       		=   [x['''text'''] for x in qa['''answers''']]
												A_       		=   predictions[qa['''id''']]
												A_       		=   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    )

			A_       		=   [x for _, x in sorted(zip(__a					,__a    )    )]
			recalls.sort()

			A_       		=   100.0 * fa / total
			A_       		=   100.0 * exact_match / total
			A_       		=   get_aupr(__a					,__a    )

			A_       		=   get_prec_at_recall(__a					,__a					,recall_thresh=0.9    )
			A_       		=   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__":
							_SCREAMING_SNAKE_CASE =	argparse.ArgumentParser(description="Evaluation for CUAD")
							parser.add_argument("dataset_file", help="Dataset file")
							parser.add_argument("prediction_file", help="Prediction File")
							_SCREAMING_SNAKE_CASE =	parser.parse_args()
							with open(args.dataset_file) as dataset_file:
														_SCREAMING_SNAKE_CASE =	json.load(dataset_file)
														_SCREAMING_SNAKE_CASE =	dataset_json["data"]
							with open(args.prediction_file) as prediction_file:
														_SCREAMING_SNAKE_CASE =	json.load(prediction_file)
							print(json.dumps(evaluate(dataset, predictions)))











'''simple docstring'''
from typing import Dict, List, Optional, Tuple

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


_SCREAMING_SNAKE_CASE =	logging.get_logger(__name__)
class      __UpperCAmelCase							(    lowerCAmelCase							):



					'''simple docstring'''





					_UpperCamelCase  	=		["""input_ids""", """attention_mask"""]



					def __init__(  self    :	str			,					_lowercase    :	List[Any]="[PAD]"			,					_lowercase    :	Any="[BOS]"			,					_lowercase    :	Any="[EOS]"			,					_lowercase    :	str="[MASK]"			,					_lowercase    :	str="[CLS]"			,					_lowercase    :	Optional[Any]="[SEP]"			,					_lowercase    :	List[str]=2_048			,					**_lowercase    :	int			,					)						->       None:
								A_       		=   AddedToken(_lowercase			,					lstrip=_lowercase			,					rstrip=_lowercase) if isinstance(_lowercase			,					_lowercase) else pad_token
								A_       		=   AddedToken(_lowercase			,					lstrip=_lowercase			,					rstrip=_lowercase) if isinstance(_lowercase			,					_lowercase) else bos_token
								A_       		=   AddedToken(_lowercase			,					lstrip=_lowercase			,					rstrip=_lowercase) if isinstance(_lowercase			,					_lowercase) else eos_token
								A_       		=   AddedToken(_lowercase			,					lstrip=_lowercase			,					rstrip=_lowercase) if isinstance(_lowercase			,					_lowercase) else mask_token
								A_       		=   AddedToken(_lowercase			,					lstrip=_lowercase			,					rstrip=_lowercase) if isinstance(_lowercase			,					_lowercase) else cls_token
								A_       		=   AddedToken(_lowercase			,					lstrip=_lowercase			,					rstrip=_lowercase) if isinstance(_lowercase			,					_lowercase) else sep_token

								super().__init__(
								    pad_token=_lowercase			,					bos_token=_lowercase			,					eos_token=_lowercase			,					mask_token=_lowercase			,					cls_token=_lowercase			,					sep_token=_lowercase			,					model_max_length=_lowercase			,					**_lowercase			,					)

								A_       		=   2**8  # utf is 8 bits

								# define special tokens dict
								A_       		=   {
								    self.pad_token: 0,
								    self.bos_token: 1,
								    self.eos_token: 2,
								    self.mask_token: 3,
								    self.cls_token: 4,
								    self.sep_token: 5,
								}
								A_       		=   len(self.special_tokens_encoder)
								A_       		=   {v: k for k, v in self.special_tokens_encoder.items()}



					def 						__snake_case	(  self    :	List[str])						->       Dict[str, int]:
								A_       		=   self.special_tokens_encoder.copy()
								vocab.update(self.added_tokens_encoder)
								for i in range(self._utf_vocab_size):
											A_       		=   chr(_lowercase)
											A_       		=   i + len(self.special_tokens_encoder)
								return vocab



					@property
					def 						__snake_case	(  self    :	int)						->       Dict:
								return self._utf_vocab_size + self._num_special_tokens



					def 						__snake_case	(  self    :	Union[str, Any]			,					_lowercase    :	List[int]			,					_lowercase    :	Optional[List[int]] = None			,					_lowercase    :	bool = False)						->       List[int]:
								if already_has_special_tokens:
											return super().get_special_tokens_mask(
											    token_ids_a=_lowercase			,					token_ids_a=_lowercase			,					already_has_special_tokens=_lowercase)

								# normal case: some special tokens
								if token_ids_a is None:
											return [1] + [0] * len(_lowercase) + [1]
								return [1] + ([0] * len(_lowercase)) + [1] + ([0] * len(_lowercase)) + [1]



					def 						__snake_case	(  self    :	int			,					_lowercase    :	List[int]			,					_lowercase    :	Optional[List[int]] = None)						->       List[int]:
								if token_ids_a is None:
											return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
								else:
											return [self.cls_token_id] + token_ids_a + [self.sep_token_id] + token_ids_a + [self.sep_token_id]



					def 						__snake_case	(  self    :	str			,					_lowercase    :	str)						->       List[str]:
								A_       		=   [chr(_lowercase) for i in text.encode('utf-8')]
								return tokens



					def 						__snake_case	(  self    :	Union[str, Any]			,					_lowercase    :	Optional[Any])						->       Tuple:
								if token in self.special_tokens_encoder:
											A_       		=   self.special_tokens_encoder[token]
								elif token in self.added_tokens_encoder:
											A_       		=   self.added_tokens_encoder[token]
								elif len(_lowercase) != 1:
											A_       		=   self.unk_token_id
								else:
											A_       		=   ord(_lowercase) + self._num_special_tokens
								return token_id



					def 						__snake_case	(  self    :	str			,					_lowercase    :	List[str])						->       Dict:
								if index in self.special_tokens_decoder:
											A_       		=   self.special_tokens_decoder[index]
								elif index in self.added_tokens_decoder:
											A_       		=   self.added_tokens_decoder[index]
								else:
											A_       		=   chr(index - self._num_special_tokens)
								return token



					def 						__snake_case	(  self    :	str			,					_lowercase    :	Dict)						->       int:
								A_       		=   B''
								for token in tokens:
											if token in self.special_tokens_decoder:
														A_       		=   self.special_tokens_decoder[token].encode('utf-8')
											elif token in self.added_tokens_decoder:
														A_       		=   self.special_tokens_decoder[token].encode('utf-8')
											elif token in self.special_tokens_encoder:
														A_       		=   token.encode('utf-8')
											elif token in self.added_tokens_encoder:
														A_       		=   token.encode('utf-8')
											else:
														A_       		=   bytes([ord(_lowercase)])
											bstring += tok_string
								A_       		=   bstring.decode('utf-8'			,					errors='replace')
								return string



					def 						__snake_case	(  self    :	Optional[int]			,					_lowercase    :	str			,					_lowercase    :	Optional[str] = None)						->       Tuple[str]:
								return ()




