






"""simple docstring"""



import argparse
import json
import re
import string
import sys

import numpy as np


_UpperCamelCase		:  int						=		0.5
def 						_SCREAMING_SNAKE_CASE			(   __snake_case      :  Optional[Any]		, __snake_case      :  int   ):





  '''simple docstring'''





  lowercase							   =	['.', ',', ';', ':']

  for token in remove_tokens:
    lowercase							   =	ground_truth.replace(__snake_case		, ''   )
    lowercase							   =	prediction.replace(__snake_case		, ''   )

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

  lowercase							   =	ground_truth.intersection(__snake_case   )
  lowercase							   =	ground_truth.union(__snake_case   )
  lowercase							   =	len(__snake_case   ) / len(__snake_case   )
  return jaccard
def 						_SCREAMING_SNAKE_CASE			(   __snake_case      :  Union[str, Any]   ):





  '''simple docstring'''





  def remove_articles(__snake_case      :  Union[str, Any]   ):
    return re.sub(r'\b(a|an|the)\b'		, ' '		, __snake_case   )

  def white_space_fix(__snake_case      :  List[Any]   ):
    return " ".join(text.split()   )

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

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

  return white_space_fix(remove_articles(remove_punc(lower(__snake_case   )   )   )   )
def 						_SCREAMING_SNAKE_CASE			(   __snake_case      :  Any		, __snake_case      :  List[str]		, __snake_case      :  List[str]   ):





  '''simple docstring'''





  lowercase   ,					lowercase   ,					lowercase							   =	0, 0, 0

  lowercase							   =	'Parties' in qa_id

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

      if not match_found:
        fp += 1

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

  return precision, recall
def 						_SCREAMING_SNAKE_CASE			(   __snake_case      :  str   ):





  '''simple docstring'''





  lowercase							   =	precisions[::-1]
  for i in range(1		, len(__snake_case   )   ):
    lowercase							   =	max(precision_best[i - 1]		, precision_best[i]   )
  lowercase							   =	precision_best[::-1]
  return precisions
def 						_SCREAMING_SNAKE_CASE			(   __snake_case      :  str		, __snake_case      :  Dict   ):





  '''simple docstring'''





  lowercase							   =	process_precisions(__snake_case   )
  lowercase							   =	np.trapz(__snake_case		, __snake_case   )
  if np.isnan(__snake_case   ):
    return 0
  return aupr
def 						_SCREAMING_SNAKE_CASE			(   __snake_case      :  Optional[int]		, __snake_case      :  Dict		, __snake_case      :  Any   ):





  '''simple docstring'''





  lowercase							   =	process_precisions(__snake_case   )
  lowercase							   =	0
  for prec, recall in zip(__snake_case		, __snake_case   ):
    if recall >= recall_thresh:
      lowercase							   =	prec
      break
  return prec_at_recall
def 						_SCREAMING_SNAKE_CASE			(   __snake_case      :  Dict		, __snake_case      :  Optional[int]   ):





  '''simple docstring'''





  return normalize_answer(__snake_case   ) == normalize_answer(__snake_case   )
def 						_SCREAMING_SNAKE_CASE			(   __snake_case      :  int		, __snake_case      :  Any		, __snake_case      :  Any   ):





  '''simple docstring'''





  lowercase							   =	0
  for pred in predictions:
    for ground_truth in ground_truths:
      lowercase							   =	metric_fn(__snake_case		, __snake_case   )
      if score == 1:  # break the loop when one prediction matches the ground truth
        break
    if score == 1:
      break
  return score
def 						_SCREAMING_SNAKE_CASE			(   __snake_case      :  Optional[int]		, __snake_case      :  Optional[Any]   ):





  '''simple docstring'''





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

        precisions.append(__snake_case   )
        recalls.append(__snake_case   )

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

        exact_match += metric_max_over_ground_truths(__snake_case		, __snake_case		, __snake_case   )

  lowercase							   =	[x for _, x in sorted(zip(__snake_case		, __snake_case   )   )]
  recalls.sort()

  lowercase							   =	100.0 * fa / total
  lowercase							   =	100.0 * exact_match / total
  lowercase							   =	get_aupr(__snake_case		, __snake_case   )

  lowercase							   =	get_prec_at_recall(__snake_case		, __snake_case		, recall_thresh=0.9   )
  lowercase							   =	get_prec_at_recall(__snake_case		, __snake_case		, 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		:  int						=		argparse.ArgumentParser(description='Evaluation for CUAD')
    parser.add_argument('dataset_file', help='Dataset file')
    parser.add_argument('prediction_file', help='Prediction File')
    _UpperCamelCase		:  Any						=		parser.parse_args()
    with open(args.dataset_file) as dataset_file:
        _UpperCamelCase		:  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 						_SCREAMING_SNAKE_CASE			(   __snake_case      :  Dict		, __snake_case      :  str   ):





  '''simple docstring'''





  lowercase							   =	1
  while b > 0:
    if b & 1:
      res *= a

    a *= a
    b >>= 1

  return res
def 						_SCREAMING_SNAKE_CASE			(   __snake_case      :  int		, __snake_case      :  List[str]		, __snake_case      :  str   ):





  '''simple docstring'''





  lowercase							   =	1
  while b > 0:
    if b & 1:
      lowercase							   =	((res % c) * (a % c)) % c

    a *= a
    b >>= 1

  return res


