




"""simple docstring"""







import re
import string

import numpy as np

import datasets


SCREAMING_SNAKE_CASE_	     =       '\nReturns the rate at which the input predicted strings exactly match their references, ignoring any strings input as part of the regexes_to_ignore list.\n'

SCREAMING_SNAKE_CASE_	     =       '\nArgs:\n    predictions: List of predicted texts.\n    references: List of reference texts.\n    regexes_to_ignore: List, defaults to None. Regex expressions of characters to\n        ignore when calculating the exact matches. Note: these regexes are removed\n        from the input data before the changes based on the options below (e.g. ignore_case,\n        ignore_punctuation, ignore_numbers) are applied.\n    ignore_case: Boolean, defaults to False. If true, turns everything\n        to lowercase so that capitalization differences are ignored.\n    ignore_punctuation: Boolean, defaults to False. If true, removes all punctuation before\n        comparing predictions and references.\n    ignore_numbers: Boolean, defaults to False. If true, removes all punctuation before\n        comparing predictions and references.\nReturns:\n    exact_match: Dictionary containing exact_match rate. Possible values are between 0.0 and 100.0, inclusive.\nExamples:\n    >>> exact_match = datasets.load_metric("exact_match")\n    >>> refs = ["the cat", "theater", "YELLING", "agent007"]\n    >>> preds = ["cat?", "theater", "yelling", "agent"]\n    >>> results = exact_match.compute(references=refs, predictions=preds)\n    >>> print(round(results["exact_match"], 1))\n    25.0\n\n    >>> exact_match = datasets.load_metric("exact_match")\n    >>> refs = ["the cat", "theater", "YELLING", "agent007"]\n    >>> preds = ["cat?", "theater", "yelling", "agent"]\n    >>> results = exact_match.compute(references=refs, predictions=preds, regexes_to_ignore=["the ", "yell"], ignore_case=True, ignore_punctuation=True)\n    >>> print(round(results["exact_match"], 1))\n    50.0\n\n\n    >>> exact_match = datasets.load_metric("exact_match")\n    >>> refs = ["the cat", "theater", "YELLING", "agent007"]\n    >>> preds = ["cat?", "theater", "yelling", "agent"]\n    >>> results = exact_match.compute(references=refs, predictions=preds, regexes_to_ignore=["the ", "yell", "YELL"], ignore_case=True, ignore_punctuation=True)\n    >>> print(round(results["exact_match"], 1))\n    75.0\n\n    >>> exact_match = datasets.load_metric("exact_match")\n    >>> refs = ["the cat", "theater", "YELLING", "agent007"]\n    >>> preds = ["cat?", "theater", "yelling", "agent"]\n    >>> results = exact_match.compute(references=refs, predictions=preds, regexes_to_ignore=["the ", "yell", "YELL"], ignore_case=True, ignore_punctuation=True, ignore_numbers=True)\n    >>> print(round(results["exact_match"], 1))\n    100.0\n\n    >>> exact_match = datasets.load_metric("exact_match")\n    >>> refs = ["The cat sat on the mat.", "Theaters are great.", "It\'s like comparing oranges and apples."]\n    >>> preds = ["The cat sat on the mat?", "Theaters are great.", "It\'s like comparing apples and oranges."]\n    >>> results = exact_match.compute(references=refs, predictions=preds)\n    >>> print(round(results["exact_match"], 1))\n    33.3\n\n'

SCREAMING_SNAKE_CASE_	     =       '\n'

@datasets.utils.file_utils.add_start_docstrings(_DESCRIPTION	, _KWARGS_DESCRIPTION			)
class 				snake_case_			(					datasets.Metric			):







   """simple docstring"""




   def   UpperCAmelCase__			(		self)				->   str:
       return datasets.MetricInfo(
           description=_DESCRIPTION       ,					citation=_CITATION       ,					inputs_description=_KWARGS_DESCRIPTION       ,					features=datasets.Features(
               {
                   '''predictions''': datasets.Value('''string'''       ,					id='''sequence'''),
                   '''references''': datasets.Value('''string'''       ,					id='''sequence'''),
               })       ,					reference_urls=[]       ,					)







   def   UpperCAmelCase__			(		self       ,					lowerCamelCase_       ,					lowerCamelCase_       ,					lowerCamelCase_=None       ,					lowerCamelCase_=False       ,					lowerCamelCase_=False       ,					lowerCamelCase_=False       ,					)				->   Any:
       if regexes_to_ignore is not None:
           for s in regexes_to_ignore:
               UpperCamelCase              =	np.array([re.sub(lowerCamelCase_       ,					''''''       ,					lowerCamelCase_) for x in predictions])
               UpperCamelCase              =	np.array([re.sub(lowerCamelCase_       ,					''''''       ,					lowerCamelCase_) for x in references])
       else:
           UpperCamelCase              =	np.asarray(lowerCamelCase_)
           UpperCamelCase              =	np.asarray(lowerCamelCase_)

       if ignore_case:
           UpperCamelCase              =	np.char.lower(lowerCamelCase_)
           UpperCamelCase              =	np.char.lower(lowerCamelCase_)

       if ignore_punctuation:
           UpperCamelCase              =	string.punctuation.maketrans(''''''       ,					''''''       ,					string.punctuation)
           UpperCamelCase              =	np.char.translate(lowerCamelCase_       ,					table=lowerCamelCase_)
           UpperCamelCase              =	np.char.translate(lowerCamelCase_       ,					table=lowerCamelCase_)

       if ignore_numbers:
           UpperCamelCase              =	string.digits.maketrans(''''''       ,					''''''       ,					string.digits)
           UpperCamelCase              =	np.char.translate(lowerCamelCase_       ,					table=lowerCamelCase_)
           UpperCamelCase              =	np.char.translate(lowerCamelCase_       ,					table=lowerCamelCase_)

       UpperCamelCase              =	predictions == references

       return {"exact_match": np.mean(lowerCamelCase_) * 1_0_0}







def      _snake_case     (__lowercase):
   UpperCamelCase_						=  1
   for i in range(1     ,   num + 1):
      fact *= i
   return fact






def      _snake_case     (__lowercase):
   UpperCamelCase_						=  0
   while number > 0:
      UpperCamelCase_						=  number % 10
      sum_of_digits += last_digit
      UpperCamelCase_						=  number // 10  # Removing the last_digit from the given number
   return sum_of_digits






def      _snake_case     (__lowercase = 100):
   UpperCamelCase_						=  factorial(__lowercase)
   UpperCamelCase_						=  split_and_add(__lowercase)
   return result


if __name__ == "__main__":
 print(solution(int(input("""Enter the Number: """).strip())))





