






"""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        _SCREAMING_SNAKE_CASE						(  unittest.TestCase							):





       """simple docstring"""





       def  lowercase		(   self:     Optional[Any]    ):

            '''simple docstring'''

            a__          =  10




       def  lowercase		(   self:     Tuple    ):

            '''simple docstring'''

            a__          =  [1, 2, 3, 4]
            a__          =  [1, 2, 3, 4, 0, 0, 0, 0, 0, 0]
            self.assertEqual(truncate_or_pad(__A				,		self.block_size				,		0    )				,		__A    )




       def  lowercase		(   self:     int    ):

            '''simple docstring'''

            a__          =  [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
            a__          =  [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
            self.assertEqual(truncate_or_pad(__A				,		self.block_size				,		0    )				,		__A    )




       def  lowercase		(   self:     Optional[Any]    ):

            '''simple docstring'''

            a__          =  [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13]
            a__          =  [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
            self.assertEqual(truncate_or_pad(__A				,		self.block_size				,		0    )				,		__A    )




       def  lowercase		(   self:     List[str]    ):

            '''simple docstring'''

            a__          =  '''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.'''
            a__       ,a__          =  process_story(__A    )
            self.assertEqual(__A				,		[]    )




       def  lowercase		(   self:     Optional[int]    ):

            '''simple docstring'''

            a__          =  ''''''
            a__       ,a__          =  process_story(__A    )
            self.assertEqual(__A				,		[]    )
            self.assertEqual(__A				,		[]    )




       def  lowercase		(   self:     Union[str, Any]    ):

            '''simple docstring'''

            a__          =  (
                '''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'''
            )
            a__       ,a__          =  process_story(__A    )

            a__          =  [
                '''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(__A				,		__A    )

            a__          =  ['''It was the best of times.''']
            self.assertEqual(__A				,		__A    )




       def  lowercase		(   self:     Optional[Any]    ):

            '''simple docstring'''

            a__          =  torch.tensor([1, 2, 3, 4]    )
            a__          =  torch.tensor([1, 1, 1, 1]    )
            np.testing.assert_array_equal(build_mask(__A				,		0    ).numpy()				,		expected.numpy()    )




       def  lowercase		(   self:     List[str]    ):

            '''simple docstring'''

            a__          =  torch.tensor([1, 2, 3, 4, 23, 23, 23]    )
            a__          =  torch.tensor([1, 1, 1, 1, 0, 0, 0]    )
            np.testing.assert_array_equal(build_mask(__A				,		23    ).numpy()				,		expected.numpy()    )




       def  lowercase		(   self:     List[Any]    ):

            '''simple docstring'''

            a__          =  torch.tensor([8, 2, 3, 4, 1, 1, 1]    )
            a__          =  torch.tensor([1, 1, 1, 1, 0, 0, 0]    )
            np.testing.assert_array_equal(build_mask(__A				,		1    ).numpy()				,		expected.numpy()    )





       def  lowercase		(   self:     List[Any]    ):

            '''simple docstring'''

            a__          =  101
            a__          =  torch.tensor([[1, 2, 3, 4, 5, 6], [1, 2, 3, 101, 5, 6], [1, 101, 3, 4, 101, 6]]    )
            a__          =  torch.tensor([[1, 1, 1, 1, 1, 1], [1, 1, 1, 0, 0, 0], [1, 0, 0, 0, 1, 1]]    )

            a__          =  compute_token_type_ids(__A				,		__A    )
            np.testing.assert_array_equal(__A				,		__A    )










"""simple docstring"""







class        _SCREAMING_SNAKE_CASE						:





							"""simple docstring"""





							def __init__(   self:     Any    ):

												'''simple docstring'''

												a__          =  {}




							def  lowercase		(   self:     Optional[int]    ):

												'''simple docstring'''

												print(self.vertex    )
												for i in self.vertex:
																	print(__A				,		''' -> '''				,		''' -> '''.join([str(__A    ) for j in self.vertex[i]]    )    )




							def  lowercase		(   self:     Union[str, Any]				,		__A:     int				,		__A:     int    ):

												'''simple docstring'''

												if from_vertex in self.vertex:
																	self.vertex[from_vertex].append(__A    )
												else:
																	# else make a new vertex
																	a__          =  [to_vertex]




							def  lowercase		(   self:     Dict    ):

												'''simple docstring'''

												a__          =  [False] * len(self.vertex    )

												# call the recursive helper function
												for i in range(len(self.vertex    )    ):
																	if not visited[i]:
																						self.dfs_recursive(__A				,		__A    )





							def  lowercase		(   self:     Optional[int]				,		__A:     int				,		__A:     list    ):

												'''simple docstring'''

												a__          =  True

												print(__A				,		end=''' '''    )

												# Recur for all the vertices that are adjacent to this node
												for i in self.vertex:
																	if not visited[i]:
																						self.dfs_recursive(__A				,		__A    )


if __name__ == "__main__":
	__a       :	Any             = Graph()
	g.add_edge(0, 1)
	g.add_edge(0, 2)
	g.add_edge(1, 2)
	g.add_edge(2, 0)
	g.add_edge(2, 3)
	g.add_edge(3, 3)

	g.print_graph()
	print('DFS:')
	g.dfs()

	# OUTPUT:
	# 0  ->  1 -> 2
	# 1  ->  2
	# 2  ->  0 -> 3
	# 3  ->  3
	# DFS:
	#  0 1 2 3


