



"""simple docstring"""

from typing import TYPE_CHECKING

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


a_			   =					{
    '''configuration_conditional_detr''': [
        '''CONDITIONAL_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''ConditionalDetrConfig''',
        '''ConditionalDetrOnnxConfig''',
    ]
}

try:
			if not is_vision_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			a_			   =					['''ConditionalDetrFeatureExtractor''']
			a_			   =					['''ConditionalDetrImageProcessor''']

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			a_			   =					[
			    '''CONDITIONAL_DETR_PRETRAINED_MODEL_ARCHIVE_LIST''',
			    '''ConditionalDetrForObjectDetection''',
			    '''ConditionalDetrForSegmentation''',
			    '''ConditionalDetrModel''',
			    '''ConditionalDetrPreTrainedModel''',
			]


if TYPE_CHECKING:
			from .configuration_conditional_detr import (
			    CONDITIONAL_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP,
			    ConditionalDetrConfig,
			    ConditionalDetrOnnxConfig,
			)

			try:
						if not is_vision_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .feature_extraction_conditional_detr import ConditionalDetrFeatureExtractor
						from .image_processing_conditional_detr import ConditionalDetrImageProcessor

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_conditional_detr import (
						    CONDITIONAL_DETR_PRETRAINED_MODEL_ARCHIVE_LIST,
						    ConditionalDetrForObjectDetection,
						    ConditionalDetrForSegmentation,
						    ConditionalDetrModel,
						    ConditionalDetrPreTrainedModel,
						)

else:
			import sys

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









"""simple docstring"""

import random







def 							SCREAMING_SNAKE_CASE__      (		SCREAMING_SNAKE_CASE__ :  int				,    SCREAMING_SNAKE_CASE__ :  float				,    SCREAMING_SNAKE_CASE__ :  bool = False			):



					"""simple docstring"""





					snake_case_					:		dict 					=					{i: [] for i in range(SCREAMING_SNAKE_CASE__			)}

					# if probability is greater or equal than 1, then generate a complete graph
					if probability >= 1:
										return complete_graph(SCREAMING_SNAKE_CASE__			)
					# if probability is lower or equal than 0, then return a graph without edges
					if probability <= 0:
										return graph

					# for each couple of nodes, add an edge from u to v
					# if the number randomly generated is greater than probability probability
					for i in range(SCREAMING_SNAKE_CASE__			):
										for j in range(i + 1				,    SCREAMING_SNAKE_CASE__			):
															if random.random() < probability:
																				graph[i].append(SCREAMING_SNAKE_CASE__			)
																				if not directed:
																									# if the graph is undirected, add an edge in from j to i, either
																									graph[j].append(SCREAMING_SNAKE_CASE__			)
					return graph







def 							SCREAMING_SNAKE_CASE__      (		SCREAMING_SNAKE_CASE__ :  int			):



					"""simple docstring"""





					return {
					    i: [j for j in range(SCREAMING_SNAKE_CASE__			) if i != j] for i in range(SCREAMING_SNAKE_CASE__			)
					}


if __name__ == "__main__":
			import doctest

			doctest.testmod()




