snake_case__				= {}
def       __magic_name__(  __UpperCAmelCase ,						__UpperCAmelCase ,						__UpperCAmelCase		)						->    int:



      '''simple docstring'''

      if late == 3 or absent == 2:
            return 0

      # if we have no days left, and have not failed any other rules,
      # we have a prize string
      if days == 0:
            return 1

      # No easy solution, so now we need to do the recursive calculation

      # First, check if the combination is already in the cache, and
      # if yes, return the stored value from there since we already
      # know the number of possible prize strings from this point on
      _lowerCamelCase			    =				(days, absent, late)
      if key in cache:
            return cache[key]

      # now we calculate the three possible ways that can unfold from
      # this point on, depending on our attendance today

      # 1) if we are late (but not absent), the "absent" counter stays as
      # it is, but the "late" counter increases by one
      _lowerCamelCase			    =				_calculate(days - 1 ,						__UpperCAmelCase ,						late + 1		)

      # 2) if we are absent, the "absent" counter increases by 1, and the
      # "late" counter resets to 0
      _lowerCamelCase			    =				_calculate(days - 1 ,						absent + 1 ,						0		)

      # 3) if we are on time, this resets the "late" counter and keeps the
      # absent counter
      _lowerCamelCase			    =				_calculate(days - 1 ,						__UpperCAmelCase ,						0		)

      _lowerCamelCase			    =				state_late + state_absent + state_ontime

      _lowerCamelCase			    =				prizestrings
      return prizestrings
def       __magic_name__(  __UpperCAmelCase = 30		)						->    int:



      '''simple docstring'''

      return _calculate(__UpperCAmelCase ,						absent=0 ,						late=0		)


if __name__ == "__main__":
     print(solution())
import os
import tempfile
import unittest

from transformers.models.marian.convert_marian_tatoeba_to_pytorch import DEFAULT_REPO, TatoebaConverter
from transformers.testing_utils import slow
from transformers.utils import cached_property



@unittest.skipUnless(os.path.exists(__lowercase )   ,  'Tatoeba directory does not exist.' )
class  UpperCamelCase				( unittest.TestCase ):

     '''simple docstring'''

     @cached_property
     def 		UpperCamelCase_						(					self						) ->				int:






           """simple docstring"""
           _lowerCamelCase			    =				tempfile.mkdtemp()
           return TatoebaConverter(save_dir=A_						)



     @slow
     def 		UpperCamelCase_						(					self						) ->				Any:






           """simple docstring"""
           self.resolver.convert_models(['''heb-eng''']						)





     @slow
     def 		UpperCamelCase_						(					self						) ->				Tuple:






           """simple docstring"""
           _lowerCamelCase    ,					_lowerCamelCase			    =				self.resolver.write_model_card('''opus-mt-he-en'''				,				dry_run=A_						)
           assert mmeta["long_pair"] == "heb-eng"