
"""simple docstring"""

import argparse
import json
import re
import string
import sys
from collections import Counter




def       lowercase__  (   lowerCAmelCase			:   List[str]	)	-> Any:






     """simple docstring"""




     def remove_articles(lowerCAmelCase			:   List[str]	):
          return re.sub(r'\b(a|an|the)\b'	,			' '	,			SCREAMING_SNAKE_CASE_	)

     def white_space_fix(lowerCAmelCase			:   Any	):
          return " ".join(text.split()	)

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

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

     return white_space_fix(remove_articles(remove_punc(lower(SCREAMING_SNAKE_CASE_	)	)	)	)




def       lowercase__  (   lowerCAmelCase			:   Dict	,			lowerCAmelCase			:   int	)	-> str:






     """simple docstring"""




     UpperCAmelCase       =   normalize_answer(SCREAMING_SNAKE_CASE_	).split()
     UpperCAmelCase       =   normalize_answer(SCREAMING_SNAKE_CASE_	).split()
     UpperCAmelCase       =   Counter(SCREAMING_SNAKE_CASE_	) & Counter(SCREAMING_SNAKE_CASE_	)
     UpperCAmelCase       =   sum(common.values()	)
     if num_same == 0:
          return 0
     UpperCAmelCase       =   1.0 * num_same / len(SCREAMING_SNAKE_CASE_	)
     UpperCAmelCase       =   1.0 * num_same / len(SCREAMING_SNAKE_CASE_	)
     UpperCAmelCase       =   (2 * precision * recall) / (precision + recall)
     return fa




def       lowercase__  (   lowerCAmelCase			:   Union[str, Any]	,			lowerCAmelCase			:   Dict	)	-> Tuple:






     """simple docstring"""




     return normalize_answer(SCREAMING_SNAKE_CASE_	) == normalize_answer(SCREAMING_SNAKE_CASE_	)




def       lowercase__  (   lowerCAmelCase			:   Union[str, Any]	,			lowerCAmelCase			:   Optional[Any]	,			lowerCAmelCase			:   List[str]	)	-> Tuple:






     """simple docstring"""




     UpperCAmelCase       =   []
     for ground_truth in ground_truths:
          UpperCAmelCase       =   metric_fn(SCREAMING_SNAKE_CASE_	,			SCREAMING_SNAKE_CASE_	)
          scores_for_ground_truths.append(SCREAMING_SNAKE_CASE_	)
     return max(SCREAMING_SNAKE_CASE_	)




def       lowercase__  (   lowerCAmelCase			:   List[Any]	,			lowerCAmelCase			:   Union[str, Any]	)	-> Dict:






     """simple docstring"""




     UpperCAmelCase       =   UpperCAmelCase       =   UpperCAmelCase       =   0
     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(SCREAMING_SNAKE_CASE_	,			file=sys.stderr	)
                         continue
                    UpperCAmelCase       =   [x['text'] for x in qa['answers']]
                    UpperCAmelCase       =   predictions[qa['id']]
                    exact_match += metric_max_over_ground_truths(SCREAMING_SNAKE_CASE_	,			SCREAMING_SNAKE_CASE_	,			SCREAMING_SNAKE_CASE_	)
                    fa += metric_max_over_ground_truths(SCREAMING_SNAKE_CASE_	,			SCREAMING_SNAKE_CASE_	,			SCREAMING_SNAKE_CASE_	)

     UpperCAmelCase       =   100.0 * exact_match / total
     UpperCAmelCase       =   100.0 * fa / total

     return {"exact_match": exact_match, "f1": fa}


if __name__ == "__main__":
   SCREAMING_SNAKE_CASE_         =  '''1.1'''
   SCREAMING_SNAKE_CASE_         =  argparse.ArgumentParser(description='''Evaluation for SQuAD ''' + expected_version)
   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)
      if dataset_json["version"] != expected_version:
         print(
             '''Evaluation expects v-''' + expected_version + ''', but got dataset with v-''' + dataset_json['''version'''],
             file=sys.stderr,
         )
      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"""

SCREAMING_SNAKE_CASE_         =  {
    0: '''underwear''',
    1: '''pants''',
    2: '''belt''',
    3: '''suit''',
    4: '''shoe''',
    5: '''socks''',
    6: '''shirt''',
    7: '''tie''',
    8: '''watch''',
}

SCREAMING_SNAKE_CASE_         =  [[1, 4], [2, 4], [3], [], [], [4], [2, 7], [3], []]

SCREAMING_SNAKE_CASE_         =  [0 for x in range(len(graph))]
SCREAMING_SNAKE_CASE_         =  []




def       lowercase__  (   lowerCAmelCase			:   Optional[int]	,			lowerCAmelCase			:   Any	)	-> List[str]:






    """simple docstring"""




    UpperCAmelCase       =   1
    while stack:
        UpperCAmelCase       =   stack.pop()
        print(lowerCAmelCase	,			clothes[current_clothing]	)
        order += 1




def       lowercase__  (   lowerCAmelCase			:   List[Any]	,			lowerCAmelCase			:   Any	,			lowerCAmelCase			:   Dict	)	-> Optional[Any]:






    """simple docstring"""




    UpperCAmelCase       =   1
    for v in graph[u]:
        if not visited[v]:
            depth_first_search(lowerCAmelCase	,			lowerCAmelCase	,			lowerCAmelCase	)

    stack.append(lowerCAmelCase	)




def       lowercase__  (   lowerCAmelCase			:   Tuple	,			lowerCAmelCase			:   Dict	)	-> Optional[Any]:






    """simple docstring"""




    for v in range(len(lowerCAmelCase	)	):
        if not visited[v]:
            depth_first_search(lowerCAmelCase	,			lowerCAmelCase	,			lowerCAmelCase	)


if __name__ == "__main__":
   topological_sort(graph, visited)
   print(stack)
   print_stack(stack, clothes)



