




def 			a   (_lowerCAmelCase     ):
							SCREAMING_SNAKE_CASE_   	=    len(_lowerCAmelCase     )
							for i in range(1  ,    _lowerCAmelCase     ):
														SCREAMING_SNAKE_CASE_   	=    collection[i]
														SCREAMING_SNAKE_CASE_   	=    0
														SCREAMING_SNAKE_CASE_   	=    i - 1

														while low <= high:
																					SCREAMING_SNAKE_CASE_   	=    (low + high) // 2
																					if val < collection[mid]:
																												SCREAMING_SNAKE_CASE_   	=    mid - 1
																					else:
																												SCREAMING_SNAKE_CASE_   	=    mid + 1
														for j in range(_lowerCAmelCase  ,    _lowerCAmelCase  ,    -1     ):
																					SCREAMING_SNAKE_CASE_   	=    collection[j - 1]
														SCREAMING_SNAKE_CASE_   	=    val
							return collection


if __name__ == "__main__":
			__SCREAMING_SNAKE_CASE 						=input("""Enter numbers separated by a comma:\n""").strip()
			__SCREAMING_SNAKE_CASE 						=[int(item) for item in user_input.split(""",""")]
			print(binary_insertion_sort(unsorted))








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  __magic_name__						(  unittest.TestCase):
				'''simple docstring'''







				def     _A							(							self:   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(_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     _A							(							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).
											SCREAMING_SNAKE_CASE_   	=    [[1, 2], [1, 2, 3, 4]]

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


				def     _A							(							self:   Dict		):
											SCREAMING_SNAKE_CASE_   	=    [[1, 2, 3], [1, 2, 4]]

											SCREAMING_SNAKE_CASE_   	=    DisjunctiveConstraint(_lowerCamelCase		)

											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(_lowerCamelCase		)
											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(_lowerCamelCase		)
											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(_lowerCamelCase		)
											self.assertTrue(dc.completed		)  # Completed!
											self.assertTrue(dc.current_seq == [1, 2, 3]		)





				def     _A							(							self:   Optional[int]		):
											SCREAMING_SNAKE_CASE_   	=    [[1, 2, 3], [1, 2, 4, 5], [1, 2, 5]]

											SCREAMING_SNAKE_CASE_   	=    DisjunctiveConstraint(_lowerCamelCase		)

											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]		)


