





'''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 SCREAMING_SNAKE_CASE_ (					unittest.TestCase   ):





					"""simple docstring"""


					def 					__magic_name__ ( self	):
										# For consistency across different places the DisjunctiveConstraint is called,
										# dc.token_ids is a list of integers. It is also initialized only by integers.

										lowerCamelCase__       =       [[1, 2, 4], [1, 2, 3, 4]]
										lowerCamelCase__       =       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 					__magic_name__ ( self	):
										# 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).
										lowerCamelCase__       =       [[1, 2], [1, 2, 3, 4]]

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





					def 					__magic_name__ ( self	):
										lowerCamelCase__       =       [[1, 2, 3], [1, 2, 4]]

										lowerCamelCase__       =       DisjunctiveConstraint(__UpperCamelCase	)

										lowerCamelCase__    ,		lowerCamelCase__    ,		lowerCamelCase__       =       dc.update(1	)
										lowerCamelCase__       =       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]	)

										lowerCamelCase__    ,		lowerCamelCase__    ,		lowerCamelCase__       =       dc.update(2	)
										lowerCamelCase__       =       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]	)

										lowerCamelCase__    ,		lowerCamelCase__    ,		lowerCamelCase__       =       dc.update(3	)
										lowerCamelCase__       =       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 					__magic_name__ ( self	):
										lowerCamelCase__       =       [[1, 2, 3], [1, 2, 4, 5], [1, 2, 5]]

										lowerCamelCase__       =       DisjunctiveConstraint(__UpperCamelCase	)

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

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

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

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

										dc.reset()

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

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

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








def    __UpperCamelCase      (    a,     a,     a=False) ->Dict:

					if isinstance(a,     a) and isinstance(a,     a):
										lowerCamelCase__       =       len(set_a.intersection(a))

										if alternative_union:
															lowerCamelCase__       =       len(a) + len(a)
										else:
															lowerCamelCase__       =       len(set_a.union(a))

										return intersection / union

					if isinstance(a,     (list, tuple)) and isinstance(a,     (list, tuple)):
										lowerCamelCase__       =       [element for element in set_a if element in set_b]

										if alternative_union:
															lowerCamelCase__       =       len(a) + len(a)
															return len(a) / union
										else:
															lowerCamelCase__       =       set_a + [element for element in set_b if element not in set_a]
															return len(a) / len(a)

										return len(a) / len(a)
					return None


if __name__ == "__main__":
						A_												=     {"a", "b", "c", "d", "e"}
						A_												=     {"c", "d", "e", "f", "h", "i"}
						print(jaccard_similarity(set_a, set_b))

