


"""simple docstring"""
from __future__ import annotations

from queue import Queue





class   __A  :





							'''simple docstring'''

							def __init__(					self				:   Optional[int]							)       ->None:



														"""simple docstring"""



														snake_case_     							=		{}



							def 		lowerCAmelCase							(					self				:   int							)       ->None:



														"""simple docstring"""



														for i in self.vertices:
																					print(__UpperCAmelCase		,							""" : """		,							""" -> """.join([str(__UpperCAmelCase							) for j in self.vertices[i]]							)							)



							def 		lowerCAmelCase							(					self				:   List[str]		,							UpperCAmelCase_				:   Tuple		,							UpperCAmelCase_				:   int							)       ->None:



														"""simple docstring"""



														if from_vertex in self.vertices:
																					self.vertices[from_vertex].append(__UpperCAmelCase							)
														else:
																					snake_case_     							=		[to_vertex]



							def 		lowerCAmelCase							(					self				:   List[Any]		,							UpperCAmelCase_				:   str							)       ->set[int]:



														"""simple docstring"""



														snake_case_     							=		set()

														# create a first in first out queue to store all the vertices for BFS
														snake_case_     							=		Queue()

														# mark the source node as visited and enqueue it
														visited.add(__UpperCAmelCase							)
														queue.put(__UpperCAmelCase							)

														while not queue.empty():
																					snake_case_     							=		queue.get()

																					# loop through all adjacent vertex and enqueue it if not yet visited
																					for adjacent_vertex in self.vertices[vertex]:
																												if adjacent_vertex not in visited:
																																			queue.put(__UpperCAmelCase							)
																																			visited.add(__UpperCAmelCase							)
														return visited


if __name__ == "__main__":
				from doctest import testmod

				testmod(verbose=True)

				__SCREAMING_SNAKE_CASE				:     int		=     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()
				# 0  :  1 -> 2
				# 1  :  2
				# 2  :  0 -> 3
				# 3  :  3

				assert sorted(g.bfs(2)) == [0, 1, 2, 3]





"""simple docstring"""


from typing import TYPE_CHECKING

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


__A					=			{
    'configuration_donut_swin': ['DONUT_SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP', 'DonutSwinConfig'],
    'processing_donut': ['DonutProcessor'],
}

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			__A					=			[
			    'DONUT_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST',
			    'DonutSwinModel',
			    'DonutSwinPreTrainedModel',
			]

try:
			if not is_vision_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			__A					=			['DonutFeatureExtractor']
			__A					=			['DonutImageProcessor']


if TYPE_CHECKING:
			from .configuration_donut_swin import DONUT_SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP, DonutSwinConfig
			from .processing_donut import DonutProcessor

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_donut_swin import (
						    DONUT_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST,
						    DonutSwinModel,
						    DonutSwinPreTrainedModel,
						)

			try:
						if not is_vision_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .feature_extraction_donut import DonutFeatureExtractor
						from .image_processing_donut import DonutImageProcessor

else:
			import sys

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



