


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







def   A   (		A__ ):

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

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

     def remove_punc(A__ ):
          UpperCAmelCase						:				Dict		  =			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(A__ ) ) ) )







def   A   (		A__		,		A__ ):
     UpperCAmelCase						:				int		  =			normalize_answer(A__ ).split()
     UpperCAmelCase						:				List[str]		  =			normalize_answer(A__ ).split()
     UpperCAmelCase						:				List[Any]		  =			Counter(A__ ) & Counter(A__ )
     UpperCAmelCase						:				str		  =			sum(common.values() )
     if num_same == 0:
          return 0
     UpperCAmelCase						:				Union[str, Any]		  =			1.0 * num_same / len(A__ )
     UpperCAmelCase						:				Union[str, Any]		  =			1.0 * num_same / len(A__ )
     UpperCAmelCase						:				Union[str, Any]		  =			(2 * precision * recall) / (precision + recall)
     return fa







def   A   (		A__		,		A__ ):
     return normalize_answer(A__ ) == normalize_answer(A__ )







def   A   (		A__		,		A__		,		A__ ):
     UpperCAmelCase						:				Union[str, Any]		  =			[]
     for ground_truth in ground_truths:
          UpperCAmelCase						:				str		  =			metric_fn(A__		,		A__ )
          scores_for_ground_truths.append(A__ )
     return max(A__ )







def   A   (		A__		,		A__ ):
     UpperCAmelCase						:				List[Any]		  =			0
     UpperCAmelCase						:				Optional[Any]		  =			[]
     for passage in dataset:
          for qa in passage["qas"]:
               total += 1
               if qa["id"] not in predictions:
                    UpperCAmelCase						:				List[str]		  =			f'Unanswered question {qa["id"]} will receive score 0.'
                    print(A__		,		file=sys.stderr )
                    continue

               UpperCAmelCase						:				List[str]		  =			[x["text"] for x in qa["answers"]]
               UpperCAmelCase						:				Optional[int]		  =			predictions[qa["id"]]

               UpperCAmelCase						:				Optional[int]		  =			metric_max_over_ground_truths(A__		,		A__		,		A__ )
               if int(_exact_match ) == 1:
                    correct_ids.append(qa["id"] )
               exact_match += _exact_match

               fa += metric_max_over_ground_truths(A__		,		A__		,		A__ )

     UpperCAmelCase						:				Optional[int]		  =			exact_match / total
     UpperCAmelCase						:				Optional[Any]		  =			fa / total

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


if __name__ == "__main__":
      _snake_case   = "1.0"
      _snake_case   = argparse.ArgumentParser("Official evaluation script for ReCoRD v1.0.")
      parser.add_argument("data_file", help="The dataset file in JSON format.")
      parser.add_argument("pred_file", help="The model prediction file in JSON format.")
      parser.add_argument("--output_correct_ids", action="store_true", help="Output the correctly answered query IDs.")
      _snake_case   = parser.parse_args()

      with open(args.data_file) as data_file:
            _snake_case   = json.load(data_file)
            if dataset_json["version"] != expected_version:
                  print(
                      f'''Evaluation expects v-{expected_version}, but got dataset with v-{dataset_json['version']}''',
                      file=sys.stderr,
                  )
            _snake_case   = dataset_json["data"]

      with open(args.pred_file) as pred_file:
            _snake_case   = json.load(pred_file)

      _snake_case ,						_snake_case   = evaluate(dataset, predictions)

      if args.output_correct_ids:
            print(f'''Output {len(correct_ids)} correctly answered question IDs.''')
            with open("correct_ids.json", "w") as f:
                  json.dump(correct_ids, f)







from __future__ import annotations

from collections.abc import Callable
from typing import Generic, TypeVar

_snake_case   = TypeVar("T")
_snake_case   = TypeVar("U")




class    A_   ( Generic[T, U]     ):







 """simple docstring"""





 def __init__(			self					: List[Any]       ,    _a					: T | None       ,    _a					: U | None				)    ->			Dict:
      UpperCAmelCase						:				str		  =			key
      UpperCAmelCase						:				Dict		  =			val
      UpperCAmelCase						:				int		  =			0
      UpperCAmelCase						:				DoubleLinkedListNode[T, U] | None		  =			None
      UpperCAmelCase						:				DoubleLinkedListNode[T, U] | None		  =			None

 def __repr__(			self					: List[str]				)    ->			str:
      return "Node: key: {}, val: {}, freq: {}, has next: {}, has prev: {}".format(
          self.key       ,    self.val       ,    self.freq       ,    self.next is not None       ,    self.prev is not None				)




class    A_   ( Generic[T, U]     ):







 """simple docstring"""





 def __init__(			self					: Any				)    ->			None:
      UpperCAmelCase						:				DoubleLinkedListNode[T, U]		  =			DoubleLinkedListNode(_a       ,    _a				)
      UpperCAmelCase						:				DoubleLinkedListNode[T, U]		  =			DoubleLinkedListNode(_a       ,    _a				)
      UpperCAmelCase  , UpperCAmelCase						:				Optional[int]		  =			self.rear, self.head
 def __repr__(			self					: int				)    ->			str:
      UpperCAmelCase						:				Union[str, Any]		  =			["DoubleLinkedList"]
      UpperCAmelCase						:				int		  =			self.head
      while node.next is not None:
           rep.append(str(_a				)				)
           UpperCAmelCase						:				Union[str, Any]		  =			node.next
      rep.append(str(self.rear				)				)
      return ",\n    ".join(_a				)
 def   _UpperCamelCase    (			self					: List[Any]       ,    _a					: DoubleLinkedListNode[T, U]				)    ->			None:
      UpperCAmelCase						:				str		  =			self.rear.prev

      # All nodes other than self.head are guaranteed to have non-None previous
      assert previous is not None

      UpperCAmelCase						:				Any		  =			node
      UpperCAmelCase						:				Optional[int]		  =			previous
      UpperCAmelCase						:				Optional[int]		  =			node
      UpperCAmelCase						:				Union[str, Any]		  =			self.rear
      node.freq += 1
      self._position_node(_a				)
 def   _UpperCamelCase    (			self					: Any       ,    _a					: DoubleLinkedListNode[T, U]				)    ->			None:

      while node.prev is not None and node.prev.freq > node.freq:
           # swap node with previous node
           UpperCAmelCase						:				List[str]		  =			node.prev

           UpperCAmelCase						:				Any		  =			previous_node.prev
           UpperCAmelCase						:				int		  =			node.prev
           UpperCAmelCase						:				Tuple		  =			previous_node
           UpperCAmelCase						:				Optional[int]		  =			node

 def   _UpperCamelCase    (			self					: str       ,    _a					: DoubleLinkedListNode[T, U]				)    ->			DoubleLinkedListNode[T, U] | None:

      if node.prev is None or node.next is None:
           return None

      UpperCAmelCase						:				Dict		  =			node.next
      UpperCAmelCase						:				Optional[Any]		  =			node.prev
      UpperCAmelCase						:				List[Any]		  =			None
      UpperCAmelCase						:				int		  =			None
      return node




class    A_   ( Generic[T, U]     ):







 """simple docstring"""





 _UpperCamelCase				: dict[Callable[[T], U], LFUCache[T, U]]      =					{}
 def __init__(			self					: List[Any]       ,    _a					: int				)    ->			int:
      UpperCAmelCase						:				DoubleLinkedList[T, U]		  =			DoubleLinkedList()
      UpperCAmelCase						:				Any		  =			capacity
      UpperCAmelCase						:				Union[str, Any]		  =			0
      UpperCAmelCase						:				Any		  =			0
      UpperCAmelCase						:				Dict		  =			0
      UpperCAmelCase						:				dict[T, DoubleLinkedListNode[T, U]]		  =			{}
 def __repr__(			self					: Union[str, Any]				)    ->			str:
      return (
          f'CacheInfo(hits={self.hits}, misses={self.miss}, '
          f'capacity={self.capacity}, current_size={self.num_keys})'
      )
 def __contains__(			self					: Optional[int]       ,    _a					: T				)    ->			bool:
      return key in self.cache
 def   _UpperCamelCase    (			self					: Optional[int]       ,    _a					: T				)    ->			U | None:

      if key in self.cache:
           self.hits += 1
           UpperCAmelCase						:				DoubleLinkedListNode[T, U]		  =			self.cache[key]
           UpperCAmelCase						:				Optional[int]		  =			self.list.remove(self.cache[key]				)
           assert node == value_node

           # node is guaranteed not None because it is in self.cache
           assert node is not None
           self.list.add(_a				)
           return node.val
      self.miss += 1
      return None
 def   _UpperCamelCase    (			self					: str       ,    _a					: T       ,    _a					: U				)    ->			None:

      if key not in self.cache:
           if self.num_keys >= self.capacity:
                # delete first node when over capacity
                UpperCAmelCase						:				Any		  =			self.list.head.next

                # guaranteed to have a non-None first node when num_keys > 0
                # explain to type checker via assertions
                assert first_node is not None
                assert first_node.key is not None
                assert self.list.remove(_a				) is not None
                # first_node guaranteed to be in list

                del self.cache[first_node.key]
                self.num_keys -= 1
           UpperCAmelCase						:				Optional[Any]		  =			DoubleLinkedListNode(_a       ,    _a				)
           self.list.add(self.cache[key]				)
           self.num_keys += 1

      else:
           UpperCAmelCase						:				Any		  =			self.list.remove(self.cache[key]				)
           assert node is not None  # node guaranteed to be in list
           UpperCAmelCase						:				str		  =			value
           self.list.add(_a				)

 @classmethod
 def   _UpperCamelCase    (			cls					: type[LFUCache[T, U]]       ,    _a					: int = 1_2_8				)    ->			Callable[[Callable[[T], U]], Callable[..., U]]:

      def cache_decorator_inner(_a					: Callable[[T], U]				) -> Callable[..., U]:
           def cache_decorator_wrapper(*_a					: T				) -> U:
                if func not in cls.decorator_function_to_instance_map:
                     UpperCAmelCase						:				List[Any]		  =			LFUCache(_a				)

                UpperCAmelCase						:				List[Any]		  =			cls.decorator_function_to_instance_map[func].get(args[0]				)
                if result is None:
                     UpperCAmelCase						:				List[Any]		  =			func(*_a				)
                     cls.decorator_function_to_instance_map[func].put(args[0]       ,    _a				)
                return result

           def cache_info() -> LFUCache[T, U]:
                return cls.decorator_function_to_instance_map[func]

           setattr(_a       ,    "cache_info"       ,    _a				)  # noqa: B010

           return cache_decorator_wrapper

      return cache_decorator_inner


if __name__ == "__main__":
      import doctest

      doctest.testmod()



