

from __future__ import annotations

from typing import Generic, TypeVar

a__				=		TypeVar('''T''')

class 				UpperCAmelCase_		(			Generic[T]   ):
							"""simple docstring"""







							def __init__(			self       ,							_a       )    ->    None:
												_a	:    Any         =		data
												_a	:    Dict         =		self
												_a	:    Union[str, Any]         =		0



class 				UpperCAmelCase_		(			Generic[T]   ):
							"""simple docstring"""







							def __init__(			self       )    ->    None:
												# map from node name to the node object
												_a	:    dict[T, DisjointSetTreeNode[T]]         =		{}


							def 				__lowercase				(			self       ,							_a       )    ->    None:
												# create a new set with x as its member
												_a	:    List[Any]         =		DisjointSetTreeNode(_a       )


							def 				__lowercase				(			self       ,							_a       )    ->    DisjointSetTreeNode[T]:
												# find the set x belongs to (with path-compression)
												_a	:    List[Any]         =		self.map[data]
												if elem_ref != elem_ref.parent:
																	_a	:    int         =		self.find_set(elem_ref.parent.data       )
												return elem_ref.parent


							def 				__lowercase				(			self       ,							_a       ,							_a       )    ->    None:
												# helper function for union operation
												if nodea.rank > nodea.rank:
																	_a	:    Optional[Any]         =		nodea
												else:
																	_a	:    List[Any]         =		nodea
																	if nodea.rank == nodea.rank:
																						nodea.rank += 1




							def 				__lowercase				(			self       ,							_a       ,							_a       )    ->    None:
												# merge 2 disjoint sets
												self.link(self.find_set(_a       )       ,							self.find_set(_a       )       )



class 				UpperCAmelCase_		(			Generic[T]   ):
							"""simple docstring"""







							def __init__(			self       )    ->    None:
												# connections: map from the node to the neighbouring nodes (with weights)
												_a	:    dict[T, dict[T, int]]         =		{}


							def 				__lowercase				(			self       ,							_a       )    ->    None:
												# add a node ONLY if its not present in the graph
												if node not in self.connections:
																	_a	:    Any         =		{}


							def 				__lowercase				(			self       ,							_a       ,							_a       ,							_a       )    ->    None:
												# add an edge with the given weight
												self.add_node(_a       )
												self.add_node(_a       )
												_a	:    int         =		weight
												_a	:    Tuple         =		weight




							def 				__lowercase				(			self       )    ->    GraphUndirectedWeighted[T]:
												_a	:    Optional[int]         =		[]
												_a	:    Optional[int]         =		set()
												for start in self.connections:
																	for end in self.connections[start]:
																						if (start, end) not in seen:
																											seen.add((end, start)       )
																											edges.append((start, end, self.connections[start][end])       )
												edges.sort(key=lambda _a       : x[2]       )

												# creating the disjoint set
												_a	:    str         =		DisjointSetTree[T]()
												for node in self.connections:
																	disjoint_set.make_set(_a       )

												# MST generation
												_a	:    Optional[int]         =		0
												_a	:    Union[str, Any]         =		0
												_a	:    Tuple         =		GraphUndirectedWeighted[T]()
												while num_edges < len(self.connections       ) - 1:
																	_a      ,					_a      ,					_a	:    str         =		edges[index]
																	index += 1
																	_a	:    int         =		disjoint_set.find_set(_a       )
																	_a	:    Dict         =		disjoint_set.find_set(_a       )
																	if parent_u != parent_v:
																						num_edges += 1
																						graph.add_edge(_a       ,							_a       ,							_a       )
																						disjoint_set.union(_a       ,							_a       )
												return graph






from typing import TYPE_CHECKING

from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


a__				=		{'''configuration_mmbt''': ['''MMBTConfig''']}

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			a__				=		['''MMBTForClassification''', '''MMBTModel''', '''ModalEmbeddings''']


if TYPE_CHECKING:
			from .configuration_mmbt import MMBTConfig

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_mmbt import MMBTForClassification, MMBTModel, ModalEmbeddings

else:
			import sys

			a__				=		_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)



