



"""simple docstring"""





from __future__ import annotations




def 	UpperCAmelCase     (		A	:						list[float]     ,				A	:						str       ):

		'''simple docstring'''


		print(f'Vertex\tShortest Distance from vertex {src}'       )
		for i, d in enumerate(A       ):
				print(f'{i}\t\t{d}'       )




def 	UpperCAmelCase     (		A	:						list[dict[str, int]]     ,				A	:						list[float]     ,				A	:						int       ):

		'''simple docstring'''


		for j in range(A       ):
				_UpperCAmelCase ,					_UpperCAmelCase ,					_UpperCAmelCase							 =		(graph[j][k] for k in ['src', 'dst', 'weight'])
				if distance[u] != float('inf'       ) and distance[u] + w < distance[v]:
						return True
		return False




def 	UpperCAmelCase     (		A	:						list[dict[str, int]]     ,				A	:						int     ,				A	:						int     ,				A	:						int       ):

		'''simple docstring'''


		_UpperCAmelCase							 =		[float('inf'       )] * vertex_count
		_UpperCAmelCase							 =		0.0

		for _ in range(vertex_count - 1       ):
				for j in range(A       ):
						_UpperCAmelCase ,					_UpperCAmelCase ,					_UpperCAmelCase							 =		(graph[j][k] for k in ['src', 'dst', 'weight'])

						if distance[u] != float('inf'       ) and distance[u] + w < distance[v]:
								_UpperCAmelCase							 =		distance[u] + w

		_UpperCAmelCase							 =		check_negative_cycle(A     ,				A     ,				A       )
		if negative_cycle_exists:
				raise Exception('Negative cycle found'       )

		return distance


if __name__ == "__main__":
					import doctest

					doctest.testmod()

					lowercase  							=					int(input('''Enter number of vertices: ''').strip())
					lowercase  							=					int(input('''Enter number of edges: ''').strip())

					lowercase  							=					[{} for _ in range(E)]

					for i in range(E):
										print('''Edge ''', i + 1)
										lowercase							,       lowercase							,       lowercase  							=					(
										    int(x)
										    for x in input('''Enter source, destination, weight: ''').strip().split(''' ''')
										)
										lowercase  							=					{'''src''': src, '''dst''': dest, '''weight''': weight}

					lowercase  							=					int(input('''\nEnter shortest path source:''').strip())
					lowercase  							=					bellman_ford(graph, V, E, source)
					print_distance(shortest_distance, 0)







"""simple docstring"""





from collections import OrderedDict
from typing import Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices


lowercase  							=					logging.get_logger(__name__)

lowercase  							=					{
    '''microsoft/swin-tiny-patch4-window7-224''': (
        '''https://huggingface.co/microsoft/swin-tiny-patch4-window7-224/resolve/main/config.json'''
    ),
    # See all Swin models at https://huggingface.co/models?filter=swin
}




class 			lowercase__			(      A,					A    ):
							'''simple docstring'''







							_UpperCAmelCase      				=					'''swin'''

							_UpperCAmelCase      				=					{
							    '''num_attention_heads''': '''num_heads''',
							    '''num_hidden_layers''': '''num_layers''',
							}






							def __init__(  self	,       snake_case=224	,       snake_case=4	,       snake_case=3	,       snake_case=96	,       snake_case=[2, 2, 6, 2]	,       snake_case=[3, 6, 12, 24]	,       snake_case=7	,       snake_case=4.0	,       snake_case=True	,       snake_case=0.0	,       snake_case=0.0	,       snake_case=0.1	,       snake_case="gelu"	,       snake_case=False	,       snake_case=0.02	,       snake_case=1E-5	,       snake_case=32	,       snake_case=None	,       snake_case=None	,       **snake_case	,       )			->							List[Any]:
									super().__init__(**snake_case						)

									_UpperCAmelCase							 =		image_size
									_UpperCAmelCase							 =		patch_size
									_UpperCAmelCase							 =		num_channels
									_UpperCAmelCase							 =		embed_dim
									_UpperCAmelCase							 =		depths
									_UpperCAmelCase							 =		len(snake_case						)
									_UpperCAmelCase							 =		num_heads
									_UpperCAmelCase							 =		window_size
									_UpperCAmelCase							 =		mlp_ratio
									_UpperCAmelCase							 =		qkv_bias
									_UpperCAmelCase							 =		hidden_dropout_prob
									_UpperCAmelCase							 =		attention_probs_dropout_prob
									_UpperCAmelCase							 =		drop_path_rate
									_UpperCAmelCase							 =		hidden_act
									_UpperCAmelCase							 =		use_absolute_embeddings
									_UpperCAmelCase							 =		layer_norm_eps
									_UpperCAmelCase							 =		initializer_range
									_UpperCAmelCase							 =		encoder_stride
									# we set the hidden_size attribute in order to make Swin work with VisionEncoderDecoderModel
									# this indicates the channel dimension after the last stage of the model
									_UpperCAmelCase							 =		int(embed_dim * 2 ** (len(snake_case						) - 1)						)
									_UpperCAmelCase							 =		['stem'] + [f'stage{idx}' for idx in range(1	,       len(snake_case						) + 1						)]
									_UpperCAmelCase ,					_UpperCAmelCase							 =		get_aligned_output_features_output_indices(
									    out_features=snake_case	,       out_indices=snake_case	,       stage_names=self.stage_names						)







class 			lowercase__			(      A    ):
							'''simple docstring'''







							_UpperCAmelCase      				=					version.parse('''1.11'''    )






							@property
							def        lowerCamelCase_   (  self						)			->							Mapping[str, Mapping[int, str]]:
									return OrderedDict(
									    [
									        ('pixel_values', {0: 'batch', 1: 'num_channels', 2: 'height', 3: 'width'}),
									    ]						)






							@property
							def        lowerCamelCase_   (  self						)			->							float:
									return 1E-4


