



'''simple docstring'''

from __future__ import annotations

from typing import Generic, TypeVar

a							   =				TypeVar('T')






class 						a_		(     Generic[T]    ):


							def __init__(				self   :						Optional[Any]      ,						a_   :						T			)			->					None:
										snake_case:    Dict      							=data
										snake_case:    str      							=self
										snake_case:    List[str]      							=0






class 						a_		(     Generic[T]    ):


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


							def    UpperCamelCase     (				self   :						List[str]      ,						a_   :						T			)			->					None:
										# create a new set with x as its member
										snake_case:    Any      							=DisjointSetTreeNode(a_			)


							def    UpperCamelCase     (				self   :						List[str]      ,						a_   :						T			)			->					DisjointSetTreeNode[T]:
										# find the set x belongs to (with path-compression)
										snake_case:    Optional[int]      							=self.map[data]
										if elem_ref != elem_ref.parent:
													snake_case:    Dict      							=self.find_set(elem_ref.parent.data			)
										return elem_ref.parent


							def    UpperCamelCase     (				self   :						Optional[int]      ,						a_   :						DisjointSetTreeNode[T]      ,						a_   :						DisjointSetTreeNode[T]			)			->					None:
										# helper function for union operation
										if nodea.rank > nodea.rank:
													snake_case:    Optional[Any]      							=nodea
										else:
													snake_case:    List[Any]      							=nodea
													if nodea.rank == nodea.rank:
																nodea.rank += 1




							def    UpperCamelCase     (				self   :						List[str]      ,						a_   :						T      ,						a_   :						T			)			->					None:
										# merge 2 disjoint sets
										self.link(self.find_set(a_			)      ,						self.find_set(a_			)			)






class 						a_		(     Generic[T]    ):


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


							def    UpperCamelCase     (				self   :						Any      ,						a_   :						T			)			->					None:
										# add a node ONLY if its not present in the graph
										if node not in self.connections:
													snake_case:    int      							={}


							def    UpperCamelCase     (				self   :						Optional[Any]      ,						a_   :						T      ,						a_   :						T      ,						a_   :						int			)			->					None:
										# add an edge with the given weight
										self.add_node(a_			)
										self.add_node(a_			)
										snake_case:    Tuple      							=weight
										snake_case:    Optional[Any]      							=weight




							def    UpperCamelCase     (				self   :						int			)			->					GraphUndirectedWeighted[T]:
										snake_case:    List[str]      							=[]
										snake_case:    Dict      							=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
										snake_case:    int      							=DisjointSetTree[T]()
										for node in self.connections:
													disjoint_set.make_set(a_			)

										# MST generation
										snake_case:    Optional[Any]      							=0
										snake_case:    str      							=0
										snake_case:    Dict      							=GraphUndirectedWeighted[T]()
										while num_edges < len(self.connections			) - 1:
													snake_case							,  snake_case							,  snake_case:    Dict      							=edges[index]
													index += 1
													snake_case:    Any      							=disjoint_set.find_set(a_			)
													snake_case:    int      							=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









'''simple docstring'''

from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
    is_vision_available,
)


a							   =				{
    'configuration_owlvit': [
        'OWLVIT_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'OwlViTConfig',
        'OwlViTOnnxConfig',
        'OwlViTTextConfig',
        'OwlViTVisionConfig',
    ],
    'processing_owlvit': ['OwlViTProcessor'],
}


try:
	if not is_vision_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	a							   =				['OwlViTFeatureExtractor']
	a							   =				['OwlViTImageProcessor']

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	a							   =				[
	    'OWLVIT_PRETRAINED_MODEL_ARCHIVE_LIST',
	    'OwlViTModel',
	    'OwlViTPreTrainedModel',
	    'OwlViTTextModel',
	    'OwlViTVisionModel',
	    'OwlViTForObjectDetection',
	]

if TYPE_CHECKING:
	from .configuration_owlvit import (
	    OWLVIT_PRETRAINED_CONFIG_ARCHIVE_MAP,
	    OwlViTConfig,
	    OwlViTOnnxConfig,
	    OwlViTTextConfig,
	    OwlViTVisionConfig,
	)
	from .processing_owlvit import OwlViTProcessor

	try:
		if not is_vision_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .feature_extraction_owlvit import OwlViTFeatureExtractor
		from .image_processing_owlvit import OwlViTImageProcessor

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_owlvit import (
		    OWLVIT_PRETRAINED_MODEL_ARCHIVE_LIST,
		    OwlViTForObjectDetection,
		    OwlViTModel,
		    OwlViTPreTrainedModel,
		    OwlViTTextModel,
		    OwlViTVisionModel,
		)

else:
	import sys

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




