

"""simple docstring"""




import unittest

import numpy as np
import torch

from .utils_summarization import build_mask, compute_token_type_ids, process_story, truncate_or_pad





class  lowerCamelCase    (unittest.TestCase      ):

			def        SCREAMING_SNAKE_CASE					(       self					:    Optional[Any]							) ->     str:
						SCREAMING_SNAKE_CASE__										=   1_0

			def        SCREAMING_SNAKE_CASE					(       self					:    Any							) ->     List[str]:
						SCREAMING_SNAKE_CASE__										=   [1, 2, 3, 4]
						SCREAMING_SNAKE_CASE__										=   [1, 2, 3, 4, 0, 0, 0, 0, 0, 0]
						self.assertEqual(truncate_or_pad(__UpperCAmelCase     ,					self.block_size     ,					0							)     ,					__UpperCAmelCase							)

			def        SCREAMING_SNAKE_CASE					(       self					:    Tuple							) ->     int:
						SCREAMING_SNAKE_CASE__										=   [1, 2, 3, 4, 5, 6, 7, 8, 9, 1_0]
						SCREAMING_SNAKE_CASE__										=   [1, 2, 3, 4, 5, 6, 7, 8, 9, 1_0]
						self.assertEqual(truncate_or_pad(__UpperCAmelCase     ,					self.block_size     ,					0							)     ,					__UpperCAmelCase							)

			def        SCREAMING_SNAKE_CASE					(       self					:    int							) ->     str:
						SCREAMING_SNAKE_CASE__										=   [1, 2, 3, 4, 5, 6, 7, 8, 9, 1_0, 1_1, 1_2, 1_3]
						SCREAMING_SNAKE_CASE__										=   [1, 2, 3, 4, 5, 6, 7, 8, 9, 1_0]
						self.assertEqual(truncate_or_pad(__UpperCAmelCase     ,					self.block_size     ,					0							)     ,					__UpperCAmelCase							)

			def        SCREAMING_SNAKE_CASE					(       self					:    str							) ->     Union[str, Any]:
						SCREAMING_SNAKE_CASE__										=   """It was the year of Our Lord one thousand seven hundred and
        seventy-five.\n\nSpiritual revelations were conceded to England at that
        favoured period, as at this."""
						SCREAMING_SNAKE_CASE__				,		SCREAMING_SNAKE_CASE__										=   process_story(__UpperCAmelCase							)
						self.assertEqual(__UpperCAmelCase     ,					[]							)

			def        SCREAMING_SNAKE_CASE					(       self					:    Optional[Any]							) ->     Dict:
						SCREAMING_SNAKE_CASE__										=   """"""
						SCREAMING_SNAKE_CASE__				,		SCREAMING_SNAKE_CASE__										=   process_story(__UpperCAmelCase							)
						self.assertEqual(__UpperCAmelCase     ,					[]							)
						self.assertEqual(__UpperCAmelCase     ,					[]							)

			def        SCREAMING_SNAKE_CASE					(       self					:    List[Any]							) ->     Union[str, Any]:
						SCREAMING_SNAKE_CASE__										=   (
						    """It was the year of Our Lord one thousand seven hundred and """
						    """seventy-five\n\nSpiritual revelations were conceded to England """
						    """at that favoured period, as at this.\n@highlight\n\nIt was the best of times"""
						)
						SCREAMING_SNAKE_CASE__				,		SCREAMING_SNAKE_CASE__										=   process_story(__UpperCAmelCase							)

						SCREAMING_SNAKE_CASE__										=   [
						    """It was the year of Our Lord one thousand seven hundred and seventy-five.""",
						    """Spiritual revelations were conceded to England at that favoured period, as at this.""",
						]
						self.assertEqual(__UpperCAmelCase     ,					__UpperCAmelCase							)

						SCREAMING_SNAKE_CASE__										=   ["""It was the best of times."""]
						self.assertEqual(__UpperCAmelCase     ,					__UpperCAmelCase							)

			def        SCREAMING_SNAKE_CASE					(       self					:    Optional[int]							) ->     Optional[int]:
						SCREAMING_SNAKE_CASE__										=   torch.tensor([1, 2, 3, 4]							)
						SCREAMING_SNAKE_CASE__										=   torch.tensor([1, 1, 1, 1]							)
						np.testing.assert_array_equal(build_mask(__UpperCAmelCase     ,					0							).numpy()     ,					expected.numpy()							)

			def        SCREAMING_SNAKE_CASE					(       self					:    Optional[int]							) ->     Tuple:
						SCREAMING_SNAKE_CASE__										=   torch.tensor([1, 2, 3, 4, 2_3, 2_3, 2_3]							)
						SCREAMING_SNAKE_CASE__										=   torch.tensor([1, 1, 1, 1, 0, 0, 0]							)
						np.testing.assert_array_equal(build_mask(__UpperCAmelCase     ,					2_3							).numpy()     ,					expected.numpy()							)

			def        SCREAMING_SNAKE_CASE					(       self					:    List[str]							) ->     int:
						SCREAMING_SNAKE_CASE__										=   torch.tensor([8, 2, 3, 4, 1, 1, 1]							)
						SCREAMING_SNAKE_CASE__										=   torch.tensor([1, 1, 1, 1, 0, 0, 0]							)
						np.testing.assert_array_equal(build_mask(__UpperCAmelCase     ,					1							).numpy()     ,					expected.numpy()							)





			def        SCREAMING_SNAKE_CASE					(       self					:    List[str]							) ->     Dict:
						SCREAMING_SNAKE_CASE__										=   1_0_1
						SCREAMING_SNAKE_CASE__										=   torch.tensor([[1, 2, 3, 4, 5, 6], [1, 2, 3, 1_0_1, 5, 6], [1, 1_0_1, 3, 4, 1_0_1, 6]]							)
						SCREAMING_SNAKE_CASE__										=   torch.tensor([[1, 1, 1, 1, 1, 1], [1, 1, 1, 0, 0, 0], [1, 0, 0, 0, 1, 1]]							)

						SCREAMING_SNAKE_CASE__										=   compute_token_type_ids(__UpperCAmelCase     ,					__UpperCAmelCase							)
						np.testing.assert_array_equal(__UpperCAmelCase     ,					__UpperCAmelCase							)





"""simple docstring"""




def 						A							(  snake_case__     ):




			'''simple docstring'''


			SCREAMING_SNAKE_CASE__										=   1
			SCREAMING_SNAKE_CASE__										=   2
			while i * i <= n:
						SCREAMING_SNAKE_CASE__										=   0
						while n % i == 0:
									n //= i
									multiplicity += 1
						n_divisors *= multiplicity + 1
						i += 1
			if n > 1:
						n_divisors *= 2
			return n_divisors

def 						A							(  ):




			'''simple docstring'''


			SCREAMING_SNAKE_CASE__										=   1
			SCREAMING_SNAKE_CASE__										=   1

			while True:
						i += 1
						t_num += i

						if count_divisors(snake_case__     ) > 5_00:
									break

			return t_num


if __name__ == "__main__":
						print(solution())


