



'''simple docstring'''




from __future__ import annotations

from typing import Any







class      _lowerCAmelCase							:


	def __init__(self	,				lowercase							):
				A_     :						List[Any]     =					num_of_nodes
				A_     :						list[list[int]]     =					[]
				A_     :						dict[int, int]     =					{}


	def    _a     (self	,				lowercase	,				lowercase	,				lowercase							):
				self.m_edges.append([u_node, v_node, weight]							)


	def    _a     (self	,				lowercase							):

				if self.m_component[u_node] == u_node:
							return u_node
				return self.find_component(self.m_component[u_node]							)


	def    _a     (self	,				lowercase							):

				if self.m_component[u_node] != u_node:
							for k in self.m_component:
										A_     :						Tuple     =					self.find_component(lowercase							)


	def    _a     (self	,				lowercase	,				lowercase	,				lowercase							):

				if component_size[u_node] <= component_size[v_node]:
							A_     :						Tuple     =					v_node
							component_size[v_node] += component_size[u_node]
							self.set_component(lowercase							)

				elif component_size[u_node] >= component_size[v_node]:
							A_     :						Dict     =					self.find_component(lowercase							)
							component_size[u_node] += component_size[v_node]
							self.set_component(lowercase							)


	def    _a     (self							):
				A_     :						Dict     =					[]
				A_     :						int     =					0

				A_     :						list[Any]     =					[-1] * self.m_num_of_nodes

				# A list of components (initialized to all of the nodes)
				for node in range(self.m_num_of_nodes							):
							self.m_component.update({node: node}							)
							component_size.append(1							)

				A_     :						Optional[Any]     =					self.m_num_of_nodes

				while num_of_components > 1:
							for edge in self.m_edges:
										A_,   A_,   A_     :						int     =					edge

										A_     :						Optional[int]     =					self.m_component[u]
										A_     :						Optional[int]     =					self.m_component[v]

										if u_component != v_component:

													for component in (u_component, v_component):
																if (
																    minimum_weight_edge[component] == -1
																    or minimum_weight_edge[component][2] > w
																):
																			A_     :						List[Any]     =					[u, v, w]

							for edge in minimum_weight_edge:
										if isinstance(lowercase	,				lowercase							):
													A_,   A_,   A_     :						str     =					edge

													A_     :						Any     =					self.m_component[u]
													A_     :						List[str]     =					self.m_component[v]

													if u_component != v_component:
																mst_weight += w
																self.union(lowercase	,				lowercase	,				lowercase							)
																print(F'Added edge [{u} - {v}]\nAdded weight: {w}\n'							)
																num_of_components -= 1

							A_     :						Dict     =					[-1] * self.m_num_of_nodes
				print(F'The total weight of the minimal spanning tree is: {mst_weight}'							)






def      a      (			):
			'''simple docstring'''







if __name__ == "__main__":
						import doctest

						doctest.testmod()




'''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    _a     (self							):
				A_     :						Dict     =					10


	def    _a     (self							):
				A_     :						str     =					[1, 2, 3, 4]
				A_     :						List[str]     =					[1, 2, 3, 4, 0, 0, 0, 0, 0, 0]
				self.assertEqual(truncate_or_pad(lowercase	,				self.block_size	,				0							)	,				lowercase							)


	def    _a     (self							):
				A_     :						str     =					[1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
				A_     :						Tuple     =					[1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
				self.assertEqual(truncate_or_pad(lowercase	,				self.block_size	,				0							)	,				lowercase							)


	def    _a     (self							):
				A_     :						List[Any]     =					[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13]
				A_     :						str     =					[1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
				self.assertEqual(truncate_or_pad(lowercase	,				self.block_size	,				0							)	,				lowercase							)


	def    _a     (self							):
				A_     :						Any     =					"""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_     :						Optional[int]     =					process_story(lowercase							)
				self.assertEqual(lowercase	,				[]							)


	def    _a     (self							):
				A_     :						Union[str, Any]     =					""""""
				A_,   A_     :						Union[str, Any]     =					process_story(lowercase							)
				self.assertEqual(lowercase	,				[]							)
				self.assertEqual(lowercase	,				[]							)


	def    _a     (self							):
				A_     :						List[Any]     =					(
				    """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_     :						int     =					process_story(lowercase							)

				A_     :						List[Any]     =					[
				    """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(lowercase	,				lowercase							)

				A_     :						Tuple     =					["""It was the best of times."""]
				self.assertEqual(lowercase	,				lowercase							)


	def    _a     (self							):
				A_     :						Dict     =					torch.tensor([1, 2, 3, 4]							)
				A_     :						Union[str, Any]     =					torch.tensor([1, 1, 1, 1]							)
				np.testing.assert_array_equal(build_mask(lowercase	,				0							).numpy()	,				expected.numpy()							)


	def    _a     (self							):
				A_     :						Union[str, Any]     =					torch.tensor([1, 2, 3, 4, 23, 23, 23]							)
				A_     :						List[str]     =					torch.tensor([1, 1, 1, 1, 0, 0, 0]							)
				np.testing.assert_array_equal(build_mask(lowercase	,				23							).numpy()	,				expected.numpy()							)


	def    _a     (self							):
				A_     :						Optional[Any]     =					torch.tensor([8, 2, 3, 4, 1, 1, 1]							)
				A_     :						Tuple     =					torch.tensor([1, 1, 1, 1, 0, 0, 0]							)
				np.testing.assert_array_equal(build_mask(lowercase	,				1							).numpy()	,				expected.numpy()							)


	def    _a     (self							):
				A_     :						List[str]     =					101
				A_     :						str     =					torch.tensor([[1, 2, 3, 4, 5, 6], [1, 2, 3, 101, 5, 6], [1, 101, 3, 4, 101, 6]]							)
				A_     :						int     =					torch.tensor([[1, 1, 1, 1, 1, 1], [1, 1, 1, 0, 0, 0], [1, 0, 0, 0, 1, 1]]							)

				A_     :						Optional[Any]     =					compute_token_type_ids(lowercase	,				lowercase							)
				np.testing.assert_array_equal(lowercase	,				lowercase							)