



'''simple docstring'''







from __future__ import annotations




class 				__lowerCAmelCase:






			def __init__(   self  :							List[str]      ,       SCREAMING_SNAKE_CASE  :							int	):




					"""simple docstring"""







					SCREAMING_SNAKE_CASE_						:str										=      vertices
					SCREAMING_SNAKE_CASE_						:List[str]										=      [[0] * vertices for _ in range(a_	)]






			def 				_lowercase	(   self  :							List[Any]      ,       SCREAMING_SNAKE_CASE  :							list[int]	):




					"""simple docstring"""







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






			def 				_lowercase	(   self  :							List[Any]      ,       SCREAMING_SNAKE_CASE  :							list[int]      ,       SCREAMING_SNAKE_CASE  :							list[bool]	):




					"""simple docstring"""







					SCREAMING_SNAKE_CASE_						:Any										=      1E7
					SCREAMING_SNAKE_CASE_						:Union[str, Any]										=      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:
									SCREAMING_SNAKE_CASE_						:Optional[Any]										=      distances_from_source[vertex]
									SCREAMING_SNAKE_CASE_						:str										=      vertex
					return min_index






			def 				_lowercase	(   self  :							Optional[int]      ,       SCREAMING_SNAKE_CASE  :							int	):




					"""simple docstring"""







					SCREAMING_SNAKE_CASE_						:List[Any]										=      [int(1E7	)] * self.vertices  # distances from the source
					SCREAMING_SNAKE_CASE_						:Optional[Any]										=      0
					SCREAMING_SNAKE_CASE_						:Any										=      [False] * self.vertices

					for _ in range(self.vertices	):
							SCREAMING_SNAKE_CASE_						:Tuple										=      self.minimum_distance(a_      ,       a_	)
							SCREAMING_SNAKE_CASE_						:str										=      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]
									):
											SCREAMING_SNAKE_CASE_						:Any										=      distances[u] + self.graph[u][v]

					self.print_solution(a_	)


if __name__ == "__main__":
							SCREAMING_SNAKE_CASE__     : Dict				=   Graph(9)
							SCREAMING_SNAKE_CASE__     : List[str]				=   [
							    [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)




'''simple docstring'''

from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast
from ...utils import logging


__lowercase:		List[str]    						=  logging.get_logger(__name__)

__lowercase:		List[Any]    						=  {
    "uclanlp/plbart-base": "https://huggingface.co/uclanlp/plbart-base/resolve/main/config.json",
    # See all PLBART models at https://huggingface.co/models?filter=plbart
}







class 			UpperCAmelCase			(							SCREAMING_SNAKE_CASE__):
 _lowerCamelCase			:       Optional[int]            =       'plbart'
 _lowerCamelCase			:       Union[str, Any]            =       ['past_key_values']
 _lowerCamelCase			:       Tuple            =       {'num_attention_heads': 'encoder_attention_heads', 'hidden_size': 'd_model'}

 def __init__(			self			:						Optional[Any],       a_			:						Union[str, Any]=5_0005,       a_			:						int=1024,       a_			:						str=6,       a_			:						Union[str, Any]=3072,       a_			:						Optional[int]=12,       a_			:						Optional[Any]=6,       a_			:						Dict=3072,       a_			:						Dict=12,       a_			:						int=0.0,       a_			:						List[Any]=0.0,       a_			:						Optional[Any]=True,       a_			:						List[str]=True,       a_			:						Tuple="gelu",       a_			:						Any=768,       a_			:						Dict=0.1,       a_			:						List[Any]=0.1,       a_			:						Union[str, Any]=0.0,       a_			:						Optional[Any]=0.02,       a_			:						Union[str, Any]=0.0,       a_			:						int=True,       a_			:						Dict=1,       a_			:						Optional[int]=0,       a_			:						Optional[int]=2,       a_			:						Any=2,       **a_			:						Optional[Any],       ):





    """simple docstring"""



    UpperCamelCase__			    =    vocab_size
    UpperCamelCase__			    =    max_position_embeddings
    UpperCamelCase__			    =    d_model
    UpperCamelCase__			    =    encoder_ffn_dim
    UpperCamelCase__			    =    encoder_layers
    UpperCamelCase__			    =    encoder_attention_heads
    UpperCamelCase__			    =    decoder_ffn_dim
    UpperCamelCase__			    =    decoder_layers
    UpperCamelCase__			    =    decoder_attention_heads
    UpperCamelCase__			    =    dropout
    UpperCamelCase__			    =    attention_dropout
    UpperCamelCase__			    =    activation_dropout
    UpperCamelCase__			    =    activation_function
    UpperCamelCase__			    =    init_std
    UpperCamelCase__			    =    encoder_layerdrop
    UpperCamelCase__			    =    decoder_layerdrop
    UpperCamelCase__			    =    classifier_dropout
    UpperCamelCase__			    =    use_cache
    UpperCamelCase__			    =    encoder_layers
    UpperCamelCase__			    =    scale_embedding  # scale factor will be sqrt(d_model) if True
    super().__init__(
        pad_token_id=a_,       bos_token_id=a_,       eos_token_id=a_,       is_encoder_decoder=a_,       forced_eos_token_id=a_,       **a_,       )







class 			UpperCAmelCase			(							SCREAMING_SNAKE_CASE__):

 @property
 def 		lowercase_    (			self			:						int       ):





    """simple docstring"""



    return OrderedDict(
        [
            ("input_ids", {0: "batch", 1: "sequence"}),
            ("attention_mask", {0: "batch", 1: "sequence"}),
        ]       )

 @property
 def 		lowercase_    (			self			:						Tuple       ):





    """simple docstring"""



    if self.use_past:
       return OrderedDict(
           [
               ("last_hidden_state", {0: "batch", 1: "sequence"}),
               ("past_keys", {0: "batch", 2: "sequence"}),
               ("encoder_last_hidden_state", {0: "batch", 1: "sequence"}),
           ]       )
    else:
       return OrderedDict(
           [
               ("last_hidden_state", {0: "batch", 1: "sequence"}),
               ("encoder_last_hidden_state", {0: "batch", 1: "sequence"}),
           ]       )