from __future__ import annotations
class 				a_ :






 '''simple docstring'''






 def __init__(			self					:  Any			,    lowercase__					:  int):







        '''simple docstring'''



        lowerCAmelCase__     	=					vertices
        lowerCAmelCase__     	=					[[0] * vertices for _ in range(lowercase__)]




 def 		__snake_case						(			self					:  Union[str, Any]			,    lowercase__					:  list[int]):







        '''simple docstring'''



        print('Vertex \t Distance from Source')
        for vertex in range(self.vertices):
               print(lowercase__			,    '\t\t'			,    distances_from_source[vertex])




 def 		__snake_case						(			self					:  Optional[Any]			,    lowercase__					:  list[int]			,    lowercase__					:  list[bool]):







        '''simple docstring'''



        lowerCAmelCase__     	=					1e7
        lowerCAmelCase__     	=					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:
                      lowerCAmelCase__     	=					distances_from_source[vertex]
                      lowerCAmelCase__     	=					vertex
        return min_index




 def 		__snake_case						(			self					:  List[str]			,    lowercase__					:  int):







        '''simple docstring'''



        lowerCAmelCase__     	=					[int(1e7)] * self.vertices  # distances from the source
        lowerCAmelCase__     	=					0
        lowerCAmelCase__     	=					[False] * self.vertices

        for _ in range(self.vertices):
               lowerCAmelCase__     	=					self.minimum_distance(lowercase__			,    lowercase__)
               lowerCAmelCase__     	=					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]
                      ):
                             lowerCAmelCase__     	=					distances[u] + self.graph[u][v]

        self.print_solution(lowercase__)


if __name__ == "__main__":
    lowerCAmelCase__							= Graph(9)
    lowerCAmelCase__							= [
        [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)

from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCAmelCase__							= logging.get_logger(__name__)

lowerCAmelCase__							= {
    'dandelin/vilt-b32-mlm': 'https://huggingface.co/dandelin/vilt-b32-mlm/blob/main/config.json'
}
class 				a_ (						SCREAMING_SNAKE_CASE						):






 '''simple docstring'''






 UpperCAmelCase_	 =					'vilt'




 def __init__(			self					:  Optional[Any]			,    lowercase__					:  Dict=30_522			,    lowercase__					:  Tuple=2			,    lowercase__					:  int=2			,    lowercase__					:  Optional[int]=40			,    lowercase__					:  Optional[int]=768			,    lowercase__					:  Tuple=12			,    lowercase__					:  Tuple=12			,    lowercase__					:  Union[str, Any]=3_072			,    lowercase__					:  int="gelu"			,    lowercase__					:  Tuple=0.0			,    lowercase__					:  Dict=0.0			,    lowercase__					:  Optional[int]=0.02			,    lowercase__					:  Tuple=1e-12			,    lowercase__					:  Dict=384			,    lowercase__					:  int=32			,    lowercase__					:  List[str]=3			,    lowercase__					:  int=True			,    lowercase__					:  List[str]=-1			,    lowercase__					:  Union[str, Any]=False			,    lowercase__					:  List[str]=-1			,    **lowercase__					:  int			,    ):







        '''simple docstring'''



        super().__init__(tie_word_embeddings=lowercase__			,    **lowercase__)

        lowerCAmelCase__     	=					vocab_size
        lowerCAmelCase__     	=					type_vocab_size
        lowerCAmelCase__     	=					modality_type_vocab_size
        lowerCAmelCase__     	=					max_position_embeddings

        lowerCAmelCase__     	=					hidden_size
        lowerCAmelCase__     	=					num_hidden_layers
        lowerCAmelCase__     	=					num_attention_heads
        lowerCAmelCase__     	=					intermediate_size
        lowerCAmelCase__     	=					hidden_act
        lowerCAmelCase__     	=					hidden_dropout_prob
        lowerCAmelCase__     	=					attention_probs_dropout_prob
        lowerCAmelCase__     	=					initializer_range
        lowerCAmelCase__     	=					layer_norm_eps

        lowerCAmelCase__     	=					image_size
        lowerCAmelCase__     	=					patch_size
        lowerCAmelCase__     	=					num_channels
        lowerCAmelCase__     	=					qkv_bias
        lowerCAmelCase__     	=					max_image_length
        lowerCAmelCase__     	=					num_images
