






"""simple docstring"""





import math







class 						_a  :





   '''simple docstring'''






   def __init__(       self					, UpperCAmelCase_					, UpperCAmelCase_					, UpperCAmelCase_					, UpperCAmelCase_)			->   Optional[int]:




          '''simple docstring'''




          lowercase__:							Union[str, Any]         =     x
          lowercase__:							str         =     y
          lowercase__:							Optional[Any]         =     step_size
          lowercase__:							Union[str, Any]         =     function_to_optimize





   def __lowercase							(       self)			->   int:




          '''simple docstring'''




          return self.function(self.x					, self.y)





   def __lowercase							(       self)			->   str:




          '''simple docstring'''




          lowercase__:							str         =     self.step_size
          return [
              SearchProblem(UpperCAmelCase_					, UpperCAmelCase_					, UpperCAmelCase_					, self.function)
              for x, y in (
                  (self.x - step_size, self.y - step_size),
                  (self.x - step_size, self.y),
                  (self.x - step_size, self.y + step_size),
                  (self.x, self.y - step_size),
                  (self.x, self.y + step_size),
                  (self.x + step_size, self.y - step_size),
                  (self.x + step_size, self.y),
                  (self.x + step_size, self.y + step_size),
              )
          ]





   def __hash__(       self)			->   Optional[int]:




          '''simple docstring'''




          return hash(str(self))





   def __eq__(       self					, UpperCAmelCase_)			->   List[Any]:




          '''simple docstring'''




          if isinstance(UpperCAmelCase_					, UpperCAmelCase_):
                 return hash(str(self)) == hash(str(UpperCAmelCase_))
          return False





   def __str__(       self)			->   Dict:




          '''simple docstring'''




          return F"""x: {self.x} y: {self.y}"""







def 							A(    snake_case_		,  snake_case_ = True		,  snake_case_ = math.inf		,  snake_case_ = -math.inf		,  snake_case_ = math.inf		,  snake_case_ = -math.inf		,  snake_case_ = False		,  snake_case_ = 10000		,  ):
       """simple docstring"""





       lowercase__:							Dict         =     search_prob
       lowercase__:							Dict         =     []  # list to store the current score at each iteration
       lowercase__:							Union[str, Any]         =     0
       lowercase__:							Union[str, Any]         =     False
       lowercase__:							Union[str, Any]         =     set()
       while not solution_found and iterations < max_iter:
              visited.add(snake_case_						)
              iterations += 1
              lowercase__:							Tuple         =     current_state.score()
              scores.append(snake_case_						)
              lowercase__:							List[str]         =     current_state.get_neighbors()
              lowercase__:							Dict         =     -math.inf
              lowercase__:							List[Any]         =     math.inf
              lowercase__:							Dict         =     None  # to hold the next best neighbor
              for neighbor in neighbors:
                     if neighbor in visited:
                            continue  # do not want to visit the same state again
                     if (
                         neighbor.x > max_x
                         or neighbor.x < min_x
                         or neighbor.y > max_y
                         or neighbor.y < min_y
                     ):
                            continue  # neighbor outside our bounds
                     lowercase__:							Tuple         =     neighbor.score() - current_score
                     if find_max:  # finding max
                            # going to direction with greatest ascent
                            if change > max_change and change > 0:
                                   lowercase__:							str         =     change
                                   lowercase__:							List[str]         =     neighbor
                     else:  # finding min
                            # to direction with greatest descent
                            if change < min_change and change < 0:
                                   lowercase__:							Optional[int]         =     change
                                   lowercase__:							Tuple         =     neighbor
              if next_state is not None:
                     # we found at least one neighbor which improved the current state
                     lowercase__:							int         =     next_state
              else:
                     # since we have no neighbor that improves the solution we stop the search
                     lowercase__:							str         =     True

       if visualization:
              from matplotlib import pyplot as plt

              plt.plot(range(snake_case_						)		,  snake_case_						)
              plt.xlabel("Iterations"						)
              plt.ylabel("Function values"						)
              plt.show()

       return current_state


if __name__ == "__main__":
  import doctest

  doctest.testmod()






  def 							A(    snake_case_		,  snake_case_						):
         """simple docstring"""





         return (x**2) + (y**2)

  # starting the problem with initial coordinates (3, 4)
  UpperCamelCase					=     SearchProblem(x=3, y=4, step_size=1, function_to_optimize=test_fa)
  UpperCamelCase					=     hill_climbing(prob, find_max=False)
  print(
      """The minimum score for f(x, y) = x^2 + y^2 found via hill climbing: """
      F"{local_min.score()}"
  )

  # starting the problem with initial coordinates (12, 47)
  UpperCamelCase					=     SearchProblem(x=12, y=47, step_size=1, function_to_optimize=test_fa)
  UpperCamelCase					=     hill_climbing(
      prob, find_max=False, max_x=1_00, min_x=5, max_y=50, min_y=-5, visualization=True
  )
  print(
      """The minimum score for f(x, y) = x^2 + y^2 with the domain 100 > x > 5 """
      F"and 50 > y > - 5 found via hill climbing: {local_min.score()}"
  )






  def 							A(    snake_case_		,  snake_case_						):
         """simple docstring"""





         return (3 * x**2) - (6 * y)

  UpperCamelCase					=     SearchProblem(x=3, y=4, step_size=1, function_to_optimize=test_fa)
  UpperCamelCase					=     hill_climbing(prob, find_max=True)







  print(
      """The maximum score for f(x, y) = x^2 + y^2 found via hill climbing: """
      F"{local_min.score()}"
  )














"""simple docstring"""





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






def 							A(    snake_case_						):
       """simple docstring"""





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

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

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

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

       return white_space_fix(remove_articles(remove_punc(lower(snake_case_						)						)						)						)






def 							A(    snake_case_		,  snake_case_						):
       """simple docstring"""





       lowercase__:							Dict         =     normalize_answer(snake_case_						).split()
       lowercase__:							List[str]         =     normalize_answer(snake_case_						).split()
       lowercase__:							Optional[int]         =     Counter(snake_case_						) & Counter(snake_case_						)
       lowercase__:							Any         =     sum(common.values()						)
       if num_same == 0:
              return 0
       lowercase__:							Any         =     1.0 * num_same / len(snake_case_						)
       lowercase__:							List[Any]         =     1.0 * num_same / len(snake_case_						)
       lowercase__:							int         =     (2 * precision * recall) / (precision + recall)
       return fa






def 							A(    snake_case_		,  snake_case_						):
       """simple docstring"""





       return normalize_answer(snake_case_						) == normalize_answer(snake_case_						)






def 							A(    snake_case_		,  snake_case_		,  snake_case_						):
       """simple docstring"""





       lowercase__:							int         =     []
       for ground_truth in ground_truths:
              lowercase__:							str         =     metric_fn(snake_case_		,  snake_case_						)
              scores_for_ground_truths.append(snake_case_						)
       return max(snake_case_						)






def 							A(    snake_case_		,  snake_case_						):
       """simple docstring"""





       lowercase__:							Optional[int]         =     0
       for article in dataset:
              for paragraph in article["paragraphs"]:
                     for qa in paragraph["qas"]:
                            total += 1
                            if qa["id"] not in predictions:
                                   lowercase__:							Union[str, Any]         =     "Unanswered question " + qa["id"] + " will receive score 0."
                                   print(snake_case_		,  file=sys.stderr						)
                                   continue
                            lowercase__:							List[Any]         =     [x["text"] for x in qa["answers"]]
                            lowercase__:							Optional[Any]         =     predictions[qa["id"]]
                            exact_match += metric_max_over_ground_truths(snake_case_		,  snake_case_		,  snake_case_						)
                            fa += metric_max_over_ground_truths(snake_case_		,  snake_case_		,  snake_case_						)

       lowercase__:							Union[str, Any]         =     1_00.0 * exact_match / total
       lowercase__:							str         =     1_00.0 * fa / total

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


if __name__ == "__main__":
  UpperCamelCase					=     """1.1"""
  UpperCamelCase					=     argparse.ArgumentParser(description="""Evaluation for SQuAD """ + expected_version)
  parser.add_argument("""dataset_file""", help="""Dataset file""")
  parser.add_argument("""prediction_file""", help="""Prediction File""")
  UpperCamelCase					=     parser.parse_args()
  with open(args.dataset_file) as dataset_file:
    UpperCamelCase					=     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,
      )
    UpperCamelCase					=     dataset_json["""data"""]
  with open(args.prediction_file) as prediction_file:
    UpperCamelCase					=     json.load(prediction_file)
  print(json.dumps(evaluate(dataset, predictions)))






