"""simple docstring"""





def 				a_     (      _lowerCAmelCase  : str   , _lowerCAmelCase  : str     ):





       '''simple docstring'''

       lowercase__			:		Optional[Any]       =	len(_lowerCAmelCase     )
       lowercase__			:		Any       =	len(_lowerCAmelCase     )
       lowercase__			:		Optional[Any]       =	[[False for _ in range(m + 1     )] for _ in range(n + 1     )]
       lowercase__			:		Any       =	True
       for i in range(_lowerCAmelCase     ):
              for j in range(m + 1     ):
                     if dp[i][j]:
                            if j < m and a[i].upper() == b[j]:
                                   lowercase__			:		Tuple       =	True
                            if a[i].islower():
                                   lowercase__			:		Optional[int]       =	True
       return dp[n][m]


if __name__ == "__main__":
       import doctest

       doctest.testmod()





"""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):

	"""simple docstring"""





	def   UpperCAmelCase_      ( self			:				Optional[int]   )       ->	List[str]:
						# For consistency across different places the DisjunctiveConstraint is called,
						# dc.token_ids is a list of integers. It is also initialized only by integers.

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

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

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




	def   UpperCAmelCase_      ( self			:				Any   )       ->	int:
						# 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).
						__SCREAMING_SNAKE_CASE						   =				[[1, 2], [1, 2, 3, 4]]

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




	def   UpperCAmelCase_      ( self			:				List[Any]   )       ->	Any:
						__SCREAMING_SNAKE_CASE						   =				[[1, 2, 3], [1, 2, 4]]

						__SCREAMING_SNAKE_CASE						   =				DisjunctiveConstraint(UpperCAmelCase__   )

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

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

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




	def   UpperCAmelCase_      ( self			:				str   )       ->	List[str]:
						__SCREAMING_SNAKE_CASE						   =				[[1, 2, 3], [1, 2, 4, 5], [1, 2, 5]]

						__SCREAMING_SNAKE_CASE						   =				DisjunctiveConstraint(UpperCAmelCase__   )

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

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

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

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

						dc.reset()

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

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

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