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

    __a			:  Optional[Any]		    =  [[1, 2, 4], [1, 2, 3, 4]]
    __a			:  int		    =  DisjunctiveConstraint(_SCREAMING_SNAKE_CASE       )
    self.assertTrue(isinstance(dc.token_ids ,    _SCREAMING_SNAKE_CASE       )       )

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

    with self.assertRaises(_SCREAMING_SNAKE_CASE       ):
     DisjunctiveConstraint([torch.LongTensor([1, 2, 4]       ), torch.LongTensor([1, 2, 3, 4, 5]       )]       )
   def 				lowerCAmelCase      (self			: Union[str, Any]       ):
    # 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).
    __a			:  Tuple		    =  [[1, 2], [1, 2, 3, 4]]

    with self.assertRaises(_SCREAMING_SNAKE_CASE       ):
     DisjunctiveConstraint(_SCREAMING_SNAKE_CASE       )  # fails here
   def 				lowerCAmelCase      (self			: int       ):
    __a			:  Union[str, Any]		    =  [[1, 2, 3], [1, 2, 4]]

    __a			:  Optional[int]		    =  DisjunctiveConstraint(_SCREAMING_SNAKE_CASE       )

    __a			:  List[Any]		    =  dc.update(1       )
    __a			:  Optional[Any]		    =  stepped is True and completed is False and reset is False
    self.assertTrue(_SCREAMING_SNAKE_CASE       )
    self.assertTrue(not dc.completed       )
    self.assertTrue(dc.current_seq == [1]       )

    __a			:  Any		    =  dc.update(2       )
    __a			:  List[str]		    =  stepped is True and completed is False and reset is False
    self.assertTrue(_SCREAMING_SNAKE_CASE       )
    self.assertTrue(not dc.completed       )
    self.assertTrue(dc.current_seq == [1, 2]       )

    __a			:  Tuple		    =  dc.update(3       )
    __a			:  Optional[Any]		    =  stepped is True and completed is True and reset is False
    self.assertTrue(_SCREAMING_SNAKE_CASE       )
    self.assertTrue(dc.completed       )  # Completed!
    self.assertTrue(dc.current_seq == [1, 2, 3]       )







   def 				lowerCAmelCase      (self			: str       ):
    __a			:  List[Any]		    =  [[1, 2, 3], [1, 2, 4, 5], [1, 2, 5]]

    __a			:  List[Any]		    =  DisjunctiveConstraint(_SCREAMING_SNAKE_CASE       )

    __a			:  str		    =  dc.update(1       )
    self.assertTrue(not dc.completed       )
    self.assertTrue(dc.current_seq == [1]       )

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

    __a			:  Optional[int]		    =  dc.update(4       )
    self.assertTrue(not dc.completed       )
    self.assertTrue(dc.current_seq == [1, 2, 4]       )

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

    dc.reset()

    __a			:  Optional[Any]		    =  dc.update(1       )
    self.assertTrue(not dc.completed       )
    self.assertTrue(dc.remaining() == 3       )
    self.assertTrue(dc.current_seq == [1]       )

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

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


from math import pi, sqrt




def        __UpperCamelCase					(    lowerCAmelCase__							:    float  ):
 if num <= 0:
  raise ValueError('''math domain error'''  )
 if num > 1_71.5:
  raise OverflowError('''math range error'''  )
 elif num - int(lowerCAmelCase__  ) not in (0, 0.5):
  raise NotImplementedError('''num must be an integer or a half-integer'''  )
 elif num == 0.5:
  return sqrt(lowerCAmelCase__  )
 else:
  return 1.0 if num == 1 else (num - 1) * gamma(num - 1  )




def        __UpperCamelCase					(    ):
 assert gamma(0.5  ) == sqrt(lowerCAmelCase__  )
 assert gamma(1  ) == 1.0
 assert gamma(2  ) == 1.0


if __name__ == "__main__":
      from doctest import testmod

      testmod()
      lowercase__          =1.0
      while num:
            lowercase__          =float(input('Gamma of: '))
            print(F"""gamma({num}) = {gamma(num)}""")
            print('\nEnter 0 to exit...')
