



"""simple docstring"""






import unittest

from transformers import is_torch_available
from transformers.testing_utils import require_torch


if is_torch_available():
     import torch

     from transformers.generation import DisjunctiveConstraint



@require_torch
class     UpperCAmelCase    (	unittest.TestCase  ):



   def    __UpperCAmelCase    (       self    :	Any				):



     """simple docstring"""
     # For consistency across different places the DisjunctiveConstraint is called,
     # dc.token_ids is a list of integers. It is also initialized only by integers.

     _snake_case   	=      [[1, 2, 4], [1, 2, 3, 4]]
     _snake_case   	=      DisjunctiveConstraint(__lowerCamelCase				)
     self.assertTrue(isinstance(dc.token_ids							,       __lowerCamelCase				)				)

     with self.assertRaises(__lowerCamelCase				):
       DisjunctiveConstraint(torch.LongTensor([[1, 2, 4], [1, 2, 3]]				)				)

     with self.assertRaises(__lowerCamelCase				):
       DisjunctiveConstraint([torch.LongTensor([1, 2, 4]				), torch.LongTensor([1, 2, 3, 4, 5]				)]				)



   def    __UpperCAmelCase    (       self    :	Tuple				):



     """simple docstring"""
     # We can't have constraints that are complete subsets of another. This leads to a preverse
     # interpretation of "constraint fulfillment": does generating [1,2,3] fulfill the constraint?
     # It would mean that it generated [1,2] which fulfills it, but it's in the middle of potentially
     # fulfilling [1,2,3,4]. If we believe that [1,2,3] does fulfill the constraint, then the algorithm
     # will necessarily never reach [1,2,3,4], giving users a false sense of control (better to just not allow it).
     _snake_case   	=      [[1, 2], [1, 2, 3, 4]]

     with self.assertRaises(__lowerCamelCase				):
       DisjunctiveConstraint(__lowerCamelCase				)  # fails here



   def    __UpperCAmelCase    (       self    :	Any				):



     """simple docstring"""
     _snake_case   	=      [[1, 2, 3], [1, 2, 4]]

     _snake_case   	=      DisjunctiveConstraint(__lowerCamelCase				)

     _snake_case	,     _snake_case	,     _snake_case   	=      dc.update(1				)
     _snake_case   	=      stepped is True and completed is False and reset is False
     self.assertTrue(__lowerCamelCase				)
     self.assertTrue(not dc.completed				)
     self.assertTrue(dc.current_seq == [1]				)

     _snake_case	,     _snake_case	,     _snake_case   	=      dc.update(2				)
     _snake_case   	=      stepped is True and completed is False and reset is False
     self.assertTrue(__lowerCamelCase				)
     self.assertTrue(not dc.completed				)
     self.assertTrue(dc.current_seq == [1, 2]				)

     _snake_case	,     _snake_case	,     _snake_case   	=      dc.update(3				)
     _snake_case   	=      stepped is True and completed is True and reset is False
     self.assertTrue(__lowerCamelCase				)
     self.assertTrue(dc.completed				)  # Completed!
     self.assertTrue(dc.current_seq == [1, 2, 3]				)





   def    __UpperCAmelCase    (       self    :	List[str]				):



     """simple docstring"""
     _snake_case   	=      [[1, 2, 3], [1, 2, 4, 5], [1, 2, 5]]

     _snake_case   	=      DisjunctiveConstraint(__lowerCamelCase				)

     _snake_case	,     _snake_case	,     _snake_case   	=      dc.update(1				)
     self.assertTrue(not dc.completed				)
     self.assertTrue(dc.current_seq == [1]				)

     _snake_case	,     _snake_case	,     _snake_case   	=      dc.update(2				)
     self.assertTrue(not dc.completed				)
     self.assertTrue(dc.current_seq == [1, 2]				)

     _snake_case	,     _snake_case	,     _snake_case   	=      dc.update(4				)
     self.assertTrue(not dc.completed				)
     self.assertTrue(dc.current_seq == [1, 2, 4]				)

     _snake_case	,     _snake_case	,     _snake_case   	=      dc.update(5				)
     self.assertTrue(dc.completed				)  # Completed!
     self.assertTrue(dc.current_seq == [1, 2, 4, 5]				)

     dc.reset()

     _snake_case	,     _snake_case	,     _snake_case   	=      dc.update(1				)
     self.assertTrue(not dc.completed				)
     self.assertTrue(dc.remaining() == 3				)
     self.assertTrue(dc.current_seq == [1]				)

     _snake_case	,     _snake_case	,     _snake_case   	=      dc.update(2				)
     self.assertTrue(not dc.completed				)
     self.assertTrue(dc.remaining() == 2				)
     self.assertTrue(dc.current_seq == [1, 2]				)

     _snake_case	,     _snake_case	,     _snake_case   	=      dc.update(5				)
     self.assertTrue(dc.completed				)  # Completed!
     self.assertTrue(dc.remaining() == 0				)
     self.assertTrue(dc.current_seq == [1, 2, 5]				)










"""simple docstring"""






from itertools import product




def 			snake_case		(		lowerCAmelCase_  ,						lowerCAmelCase_	)						->				list[int]:
  _snake_case   	=      sides_number
  _snake_case   	=      max_face_number * dice_number
  _snake_case   	=      [0] * (max_total + 1)

  _snake_case   	=      1
  _snake_case   	=      range(lowerCAmelCase_  ,						max_face_number + 1	)
  for dice_numbers in product(lowerCAmelCase_  ,						repeat=lowerCAmelCase_	):
    _snake_case   	=      sum(lowerCAmelCase_	)
    totals_frequencies[total] += 1

  return totals_frequencies




def 			snake_case		(		)						->				float:
  _snake_case   	=      total_frequency_distribution(
      sides_number=4  ,						dice_number=9	)
  _snake_case   	=      total_frequency_distribution(
      sides_number=6  ,						dice_number=6	)

  _snake_case   	=      0
  _snake_case   	=      9
  _snake_case   	=      4 * 9
  _snake_case   	=      6
  for peter_total in range(lowerCAmelCase_  ,						max_peter_total + 1	):
    peter_wins_count += peter_totals_frequencies[peter_total] * sum(
        colin_totals_frequencies[min_colin_total:peter_total]	)

  _snake_case   	=      (4**9) * (6**6)
  _snake_case   	=      peter_wins_count / total_games_number

  _snake_case   	=      round(lowerCAmelCase_  ,						ndigits=7	)

  return rounded_peter_win_probability


if __name__ == "__main__":
     print(F"{solution() = }")





