"""simple docstring"""






import copy
import inspect

from transformers.testing_utils import require_torch, torch_device
from transformers.utils.backbone_utils import BackboneType
@require_torch
class     snake_case	:




					"""simple docstring"""

					snake_case__       =			()
					snake_case__       =			True







					def 		__lowerCAmelCase						(    self       :     Dict      ):
									UpperCAmelCase__					=							self.config_class

									# test default config
									UpperCAmelCase__					=							config_class()
									self.assertIsNotNone(lowerCamelCase__      )
									UpperCAmelCase__					=							['stem'] + [f'''stage{idx}''' for idx in range(1   ,len(config.depths      ) + 1      )]
									self.assertEqual(config.stage_names   ,lowerCamelCase__      )
									self.assertTrue(set(config.out_features      ).issubset(set(config.stage_names      )      )      )

									# Test out_features and out_indices are correctly set
									# out_features and out_indices both None
									UpperCAmelCase__					=							config_class(out_features=lowerCamelCase__   ,out_indices=lowerCamelCase__      )
									self.assertEqual(config.out_features   ,[config.stage_names[-1]]      )
									self.assertEqual(config.out_indices   ,[len(config.stage_names      ) - 1]      )

									# out_features and out_indices both set
									UpperCAmelCase__					=							config_class(out_features=['stem', 'stage1']   ,out_indices=[0, 1]      )
									self.assertEqual(config.out_features   ,['stem', 'stage1']      )
									self.assertEqual(config.out_indices   ,[0, 1]      )

									# Only out_features set
									UpperCAmelCase__					=							config_class(out_features=['stage1', 'stage3']      )
									self.assertEqual(config.out_features   ,['stage1', 'stage3']      )
									self.assertEqual(config.out_indices   ,[1, 3]      )

									# Only out_indices set
									UpperCAmelCase__					=							config_class(out_indices=[0, 2]      )
									self.assertEqual(config.out_features   ,[config.stage_names[0], config.stage_names[2]]      )
									self.assertEqual(config.out_indices   ,[0, 2]      )

									# Error raised when out_indices do not correspond to out_features
									with self.assertRaises(lowerCamelCase__      ):
													UpperCAmelCase__					=							config_class(out_features=['stage1', 'stage2']   ,out_indices=[0, 2]      )







					def 		__lowerCAmelCase						(    self       :     Optional[int]      ):
									UpperCAmelCase__				,     UpperCAmelCase__					=							self.model_tester.prepare_config_and_inputs_for_common()

									for model_class in self.all_model_classes:
													UpperCAmelCase__					=							model_class(lowerCamelCase__      )
													UpperCAmelCase__					=							inspect.signature(model.forward      )
													# signature.parameters is an OrderedDict => so arg_names order is deterministic
													UpperCAmelCase__					=							[*signature.parameters.keys()]
													UpperCAmelCase__					=							['pixel_values']
													self.assertListEqual(arg_names[:1]   ,lowerCamelCase__      )







					def 		__lowerCAmelCase						(    self       :     str      ):
									UpperCAmelCase__				,     UpperCAmelCase__					=							self.model_tester.prepare_config_and_inputs_for_common()

									for model_class in self.all_model_classes:
													UpperCAmelCase__					=							model_class(lowerCamelCase__      )
													self.assertEqual(len(model.channels      )   ,len(config.out_features      )      )
													UpperCAmelCase__					=							model.num_features
													UpperCAmelCase__					=							[config.stage_names.index(lowerCamelCase__      ) for feat in config.out_features]
													UpperCAmelCase__					=							[num_features[idx] for idx in out_indices]
													self.assertListEqual(model.channels   ,lowerCamelCase__      )

													UpperCAmelCase__					=							copy.deepcopy(lowerCamelCase__      )
													UpperCAmelCase__					=							None
													UpperCAmelCase__					=							model_class(lowerCamelCase__      )
													self.assertEqual(len(model.channels      )   ,1      )
													self.assertListEqual(model.channels   ,[num_features[-1]]      )

													UpperCAmelCase__					=							copy.deepcopy(lowerCamelCase__      )
													UpperCAmelCase__					=							None
													UpperCAmelCase__					=							model_class(lowerCamelCase__      )
													self.assertEqual(len(model.channels      )   ,1      )
													self.assertListEqual(model.channels   ,[num_features[-1]]      )







					def 		__lowerCAmelCase						(    self       :     Any      ):
									UpperCAmelCase__				,     UpperCAmelCase__					=							self.model_tester.prepare_config_and_inputs_for_common()

									for model_class in self.all_model_classes:
													UpperCAmelCase__					=							model_class(lowerCamelCase__      )
													model.to(lowerCamelCase__      )
													model.eval()
													UpperCAmelCase__					=							model(**lowerCamelCase__      )

													self.assertEqual(len(result.feature_maps      )   ,len(config.out_features      )      )
													self.assertEqual(len(model.channels      )   ,len(config.out_features      )      )
													self.assertEqual(len(result.feature_maps      )   ,len(config.out_indices      )      )
													self.assertEqual(len(model.channels      )   ,len(config.out_indices      )      )

													# Check output of last stage is taken if out_features=None, out_indices=None
													UpperCAmelCase__					=							copy.deepcopy(lowerCamelCase__      )
													UpperCAmelCase__					=							None
													UpperCAmelCase__					=							model_class(lowerCamelCase__      )
													model.to(lowerCamelCase__      )
													model.eval()
													UpperCAmelCase__					=							model(**lowerCamelCase__      )

													self.assertEqual(len(result.feature_maps      )   ,1      )
													self.assertEqual(len(model.channels      )   ,1      )

													UpperCAmelCase__					=							copy.deepcopy(lowerCamelCase__      )
													UpperCAmelCase__					=							None
													UpperCAmelCase__					=							model_class(lowerCamelCase__      )
													model.to(lowerCamelCase__      )
													model.eval()
													UpperCAmelCase__					=							model(**lowerCamelCase__      )

													self.assertEqual(len(result.feature_maps      )   ,1      )
													self.assertEqual(len(model.channels      )   ,1      )

													# Check backbone can be initialized with fresh weights
													UpperCAmelCase__					=							copy.deepcopy(lowerCamelCase__      )
													UpperCAmelCase__					=							False
													UpperCAmelCase__					=							model_class(lowerCamelCase__      )
													model.to(lowerCamelCase__      )
													model.eval()
													UpperCAmelCase__					=							model(**lowerCamelCase__      )







					def 		__lowerCAmelCase						(    self       :     Optional[Any]      ):
									UpperCAmelCase__				,     UpperCAmelCase__					=							self.model_tester.prepare_config_and_inputs_for_common()

									for backbone_class in self.all_model_classes:
													UpperCAmelCase__					=							backbone_class(lowerCamelCase__      )

													self.assertTrue(hasattr(lowerCamelCase__   ,'backbone_type'      )      )
													self.assertTrue(hasattr(lowerCamelCase__   ,'stage_names'      )      )
													self.assertTrue(hasattr(lowerCamelCase__   ,'num_features'      )      )
													self.assertTrue(hasattr(lowerCamelCase__   ,'out_indices'      )      )
													self.assertTrue(hasattr(lowerCamelCase__   ,'out_features'      )      )
													self.assertTrue(hasattr(lowerCamelCase__   ,'out_feature_channels'      )      )
													self.assertTrue(hasattr(lowerCamelCase__   ,'channels'      )      )

													self.assertIsInstance(backbone.backbone_type   ,lowerCamelCase__      )
													# Verify num_features has been initialized in the backbone init
													self.assertIsNotNone(backbone.num_features      )
													self.assertTrue(len(backbone.channels      ) == len(backbone.out_indices      )      )
													self.assertTrue(len(backbone.stage_names      ) == len(backbone.num_features      )      )
													self.assertTrue(len(backbone.channels      ) <= len(backbone.num_features      )      )
													self.assertTrue(len(backbone.out_feature_channels      ) == len(backbone.stage_names      )      )







					def 		__lowerCAmelCase						(    self       :     List[str]      ):
									UpperCAmelCase__				,     UpperCAmelCase__					=							self.model_tester.prepare_config_and_inputs_for_common()
									UpperCAmelCase__					=							inputs_dict['pixel_values'].shape[0]

									for backbone_class in self.all_model_classes:
													UpperCAmelCase__					=							backbone_class(lowerCamelCase__      )
													backbone.to(lowerCamelCase__      )
													backbone.eval()

													UpperCAmelCase__					=							backbone(**lowerCamelCase__      )

													# Test default outputs and verify feature maps
													self.assertIsInstance(outputs.feature_maps   ,lowerCamelCase__      )
													self.assertTrue(len(outputs.feature_maps      ) == len(backbone.channels      )      )
													for feature_map, n_channels in zip(outputs.feature_maps   ,backbone.channels      ):
																	self.assertTrue(feature_map.shape[:2]   ,(batch_size, n_channels)      )
													self.assertIsNone(outputs.hidden_states      )
													self.assertIsNone(outputs.attentions      )

													# Test output_hidden_states=True
													UpperCAmelCase__					=							backbone(**lowerCamelCase__   ,output_hidden_states=lowerCamelCase__      )
													self.assertIsNotNone(outputs.hidden_states      )
													self.assertTrue(len(outputs.hidden_states      )   ,len(backbone.stage_names      )      )
													for hidden_state, n_channels in zip(outputs.hidden_states   ,backbone.channels      ):
																	self.assertTrue(hidden_state.shape[:2]   ,(batch_size, n_channels)      )

													# Test output_attentions=True
													if self.has_attentions:
																	UpperCAmelCase__					=							backbone(**lowerCamelCase__   ,output_attentions=lowerCamelCase__      )
																	self.assertIsNotNone(outputs.attentions      )




"""simple docstring"""






from __future__ import annotations
class     snake_case	:




					"""simple docstring"""

					def __init__(    self       :     Tuple   ,lowerCamelCase__       :     int      ):
									UpperCAmelCase__					=							vertices
									UpperCAmelCase__					=							[[0] * vertices for _ in range(lowerCamelCase__      )]







					def 		__lowerCAmelCase						(    self       :     Dict   ,lowerCamelCase__       :     list[int]      ):
									print('Vertex \t Distance from Source'      )
									for vertex in range(self.vertices      ):
													print(lowerCamelCase__   ,'\t\t'   ,distances_from_source[vertex]      )







					def 		__lowerCAmelCase						(    self       :     List[Any]   ,lowerCamelCase__       :     list[int]   ,lowerCamelCase__       :     list[bool]      ):
									UpperCAmelCase__					=							1e7
									UpperCAmelCase__					=							0

									# Search not nearest vertex not in the shortest path tree
									for vertex in range(self.vertices      ):
													if distances_from_source[vertex] < minimum and visited[vertex] is False:
																	UpperCAmelCase__					=							distances_from_source[vertex]
																	UpperCAmelCase__					=							vertex
									return min_index







					def 		__lowerCAmelCase						(    self       :     List[Any]   ,lowerCamelCase__       :     int      ):
									UpperCAmelCase__					=							[int(1e7      )] * self.vertices  # distances from the source
									UpperCAmelCase__					=							0
									UpperCAmelCase__					=							[False] * self.vertices

									for _ in range(self.vertices      ):
													UpperCAmelCase__					=							self.minimum_distance(lowerCamelCase__   ,lowerCamelCase__      )
													UpperCAmelCase__					=							True

													# Update dist value of the adjacent vertices
													# of the picked vertex only if the current
													# distance is greater than new distance and
													# the vertex in not in the shortest path tree
													for v in range(self.vertices      ):
																	if (
																	    self.graph[u][v] > 0
																	    and visited[v] is False
																	    and distances[v] > distances[u] + self.graph[u][v]
																	):
																					UpperCAmelCase__					=							distances[u] + self.graph[u][v]

									self.print_solution(lowerCamelCase__      )


if __name__ == "__main__":
						lowerCAmelCase__  :  List[str]											=     Graph(9)
						lowerCAmelCase__  :  Tuple											=     [
						    [0, 4, 0, 0, 0, 0, 0, 8, 0],
						    [4, 0, 8, 0, 0, 0, 0, 11, 0],
						    [0, 8, 0, 7, 0, 4, 0, 0, 2],
						    [0, 0, 7, 0, 9, 14, 0, 0, 0],
						    [0, 0, 0, 9, 0, 10, 0, 0, 0],
						    [0, 0, 4, 14, 10, 0, 2, 0, 0],
						    [0, 0, 0, 0, 0, 2, 0, 1, 6],
						    [8, 11, 0, 0, 0, 0, 1, 0, 7],
						    [0, 0, 2, 0, 0, 0, 6, 7, 0],
						]
						graph.dijkstra(0)



