

'''simple docstring'''

def 				lowercase (					__magic_name__			,   __magic_name__							):



					'''simple docstring'''







					print("\nVertex Distance"							)
					for i in range(__magic_name__							):
										if dist[i] != float("inf"							):
															print(__magic_name__			,   "\t"			,   int(dist[i]							)			,   end="\t"							)
										else:
															print(__magic_name__			,   "\t"			,   "INF"			,   end="\t"							)
										print()





def 				lowercase (					__magic_name__			,   __magic_name__			,   __magic_name__							):



					'''simple docstring'''







					UpperCAmelCase		:							Dict        =       float("inf"							)
					UpperCAmelCase		:							Tuple        =       -1
					for i in range(__magic_name__							):
										if (not vset[i]) and mdist[i] < min_val:
															UpperCAmelCase		:							Any        =       i
															UpperCAmelCase		:							str        =       mdist[i]
					return min_ind





def 				lowercase (					__magic_name__			,   __magic_name__			,   __magic_name__							):



					'''simple docstring'''







					UpperCAmelCase		:							Dict        =       [float("inf"							) for _ in range(__magic_name__							)]
					UpperCAmelCase		:							Optional[int]        =       [False for _ in range(__magic_name__							)]
					UpperCAmelCase		:							str        =       0.0

					for _ in range(v - 1							):
										UpperCAmelCase		:							Dict        =       min_dist(__magic_name__			,   __magic_name__			,   __magic_name__							)
										UpperCAmelCase		:							Tuple        =       True

										for i in range(__magic_name__							):
															if (
															    (not vset[i])
															    and graph[u][i] != float("inf"							)
															    and mdist[u] + graph[u][i] < mdist[i]
															):
																				UpperCAmelCase		:							Any        =       mdist[u] + graph[u][i]

					print_dist(__magic_name__			,   __magic_name__							)


if __name__ == "__main__":
				a       :      List[Any]  	=			int(input("Enter number of vertices: ").strip())
				a       :      Tuple  	=			int(input("Enter number of edges: ").strip())

				a       :      Any  	=			[[float("inf") for i in range(V)] for j in range(V)]

				for i in range(V):
								a       :      Optional[int]  	=			0.0

				for i in range(E):
								print("\nEdge ", i + 1)
								a       :      Optional[int]  	=			int(input("Enter source:").strip())
								a       :      Union[str, Any]  	=			int(input("Enter destination:").strip())
								a       :      Any  	=			float(input("Enter weight:").strip())
								a       :      Optional[Any]  	=			weight

				a       :      Dict  	=			int(input("\nEnter shortest path source:").strip())
				dijkstra(graph, V, gsrc)



'''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


a       :      List[Any]  	=			logging.get_logger(__name__)

a       :      Dict  	=			{
    "apple/mobilevitv2-1.0": "https://huggingface.co/apple/mobilevitv2-1.0/resolve/main/config.json",
}







class   UpperCamelCase__   (       lowercase__       ):


		"""simple docstring"""

		SCREAMING_SNAKE_CASE__  :     List[Any]       =							"mobilevitv2"







		def __init__(			self   ,      snake_case=3   ,      snake_case=2_5_6   ,      snake_case=2   ,      snake_case=2.0   ,      snake_case="swish"   ,      snake_case=3   ,      snake_case=3_2   ,      snake_case=0.1   ,      snake_case=0.02   ,      snake_case=1e-5   ,      snake_case=5_1_2   ,      snake_case=[6, 1_2, 1_8]   ,      snake_case=0.1   ,      snake_case=2_5_5   ,      snake_case=[2, 4, 3]   ,      snake_case=[1_2_8, 1_9_2, 2_5_6]   ,      snake_case=1.0   ,      snake_case=2   ,      snake_case=0.0   ,      snake_case=0.0   ,      **snake_case   ,      ):


							'''simple docstring'''

							super().__init__(**snake_case      )

							UpperCAmelCase		:							Tuple        =       num_channels
							UpperCAmelCase		:							Optional[int]        =       image_size
							UpperCAmelCase		:							Optional[int]        =       patch_size
							UpperCAmelCase		:							Optional[int]        =       expand_ratio
							UpperCAmelCase		:							List[Any]        =       hidden_act
							UpperCAmelCase		:							Optional[Any]        =       conv_kernel_size
							UpperCAmelCase		:							str        =       output_stride
							UpperCAmelCase		:							Optional[Any]        =       initializer_range
							UpperCAmelCase		:							Optional[Any]        =       layer_norm_eps
							UpperCAmelCase		:							List[str]        =       n_attn_blocks
							UpperCAmelCase		:							Any        =       base_attn_unit_dims
							UpperCAmelCase		:							str        =       width_multiplier
							UpperCAmelCase		:							Optional[int]        =       ffn_multiplier
							UpperCAmelCase		:							List[Any]        =       ffn_dropout
							UpperCAmelCase		:							List[str]        =       attn_dropout
							UpperCAmelCase		:							Optional[Any]        =       classifier_dropout_prob

							# decode head attributes for semantic segmentation
							UpperCAmelCase		:							Optional[Any]        =       aspp_out_channels
							UpperCAmelCase		:							Dict        =       atrous_rates
							UpperCAmelCase		:							int        =       aspp_dropout_prob
							UpperCAmelCase		:							List[str]        =       semantic_loss_ignore_index







class   UpperCamelCase__   (       lowercase__       ):


		"""simple docstring"""

		SCREAMING_SNAKE_CASE__  :     Optional[int]       =							version.parse("1.11"       )







		@property
		def 				A_	(			self      ):


							'''simple docstring'''

							return OrderedDict([("pixel_values", {0: "batch", 1: "num_channels", 2: "height", 3: "width"})]      )







		@property
		def 				A_	(			self      ):


							'''simple docstring'''

							if self.task == "image-classification":
												return OrderedDict([("logits", {0: "batch"})]      )
							else:
												return OrderedDict([("last_hidden_state", {0: "batch"}), ("pooler_output", {0: "batch"})]      )







		@property
		def 				A_	(			self      ):


							'''simple docstring'''

							return 1e-4
