




from collections import OrderedDict
from typing import List, Mapping

from packaging import version

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


__magic_name__  :  Optional[int]					=       logging.get_logger(__name__)

__magic_name__  :  Optional[Any]					=       {
    """google/efficientnet-b7""": """https://huggingface.co/google/efficientnet-b7/resolve/main/config.json""",
}





class     SCREAMING_SNAKE_CASE__		(UpperCAmelCase__			):
     lowercase_ :      Dict				= 'efficientnet'
     def __init__(						self	:		int       ,						__lowerCamelCase	:		Optional[int] = 3       ,						__lowerCamelCase	:		int = 6_00       ,						__lowerCamelCase	:		str = 2.0       ,						__lowerCamelCase	:		Dict = 3.1       ,						__lowerCamelCase	:		Tuple = 8       ,						__lowerCamelCase	:		Tuple = [3, 3, 5, 3, 5, 5, 3]       ,						__lowerCamelCase	:		Optional[Any] = [32, 16, 24, 40, 80, 1_12, 1_92]       ,						__lowerCamelCase	:		str = [16, 24, 40, 80, 1_12, 1_92, 3_20]       ,						__lowerCamelCase	:		Optional[Any] = []       ,						__lowerCamelCase	:		Union[str, Any] = [1, 2, 2, 2, 1, 2, 1]       ,						__lowerCamelCase	:		Any = [1, 2, 2, 3, 3, 4, 1]       ,						__lowerCamelCase	:		int = [1, 6, 6, 6, 6, 6, 6]       ,						__lowerCamelCase	:		List[str] = 0.25       ,						__lowerCamelCase	:		Optional[int] = "swish"       ,						__lowerCamelCase	:		Union[str, Any] = 25_60       ,						__lowerCamelCase	:		Dict = "mean"       ,						__lowerCamelCase	:		Optional[int] = 0.02       ,						__lowerCamelCase	:		str = 0.001       ,						__lowerCamelCase	:		List[str] = 0.99       ,						__lowerCamelCase	:		Dict = 0.5       ,						__lowerCamelCase	:		List[Any] = 0.2       ,						**__lowerCamelCase	:		Tuple       ,						):



       """simple docstring"""
       super().__init__(**lowerCamelCase__						)

       lowerCAmelCase__										=      num_channels
       lowerCAmelCase__										=      image_size
       lowerCAmelCase__										=      width_coefficient
       lowerCAmelCase__										=      depth_coefficient
       lowerCAmelCase__										=      depth_divisor
       lowerCAmelCase__										=      kernel_sizes
       lowerCAmelCase__										=      in_channels
       lowerCAmelCase__										=      out_channels
       lowerCAmelCase__										=      depthwise_padding
       lowerCAmelCase__										=      strides
       lowerCAmelCase__										=      num_block_repeats
       lowerCAmelCase__										=      expand_ratios
       lowerCAmelCase__										=      squeeze_expansion_ratio
       lowerCAmelCase__										=      hidden_act
       lowerCAmelCase__										=      hidden_dim
       lowerCAmelCase__										=      pooling_type
       lowerCAmelCase__										=      initializer_range
       lowerCAmelCase__										=      batch_norm_eps
       lowerCAmelCase__										=      batch_norm_momentum
       lowerCAmelCase__										=      dropout_rate
       lowerCAmelCase__										=      drop_connect_rate
       lowerCAmelCase__										=      sum(lowerCamelCase__						) * 4





class     SCREAMING_SNAKE_CASE__		(UpperCAmelCase__			):
     lowercase_ :      Optional[Any]				= version.parse("1.11"			)
     @property
     def        A__      (						self	:		str						):



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



     @property
     def        A__      (						self	:		List[Any]						):



       """simple docstring"""
       return 1e-5


from __future__ import annotations
def 		snake_case__	(		lowercase							,				lowercase					):
   print(F'''Vertex\tShortest Distance from vertex {src}'''					)
   for i, d in enumerate(lowercase					):
      print(F'''{i}\t\t{d}'''					)
def 		snake_case__	(		lowercase							,				lowercase							,				lowercase					):
   for j in range(lowercase					):
      lowerCAmelCase_  ,	lowerCAmelCase_  ,	lowerCAmelCase_:							List[str]       =	(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 		snake_case__	(		lowercase							,				lowercase							,				lowercase							,				lowercase					):
   lowerCAmelCase_:							int       =	[float("inf"					)] * vertex_count
   lowerCAmelCase_:							Dict       =	0.0

   for _ in range(vertex_count - 1					):
      for j in range(lowercase					):
         lowerCAmelCase_  ,	lowerCAmelCase_  ,	lowerCAmelCase_:							Any       =	(graph[j][k] for k in ["src", "dst", "weight"])

         if distance[u] != float("inf"					) and distance[u] + w < distance[v]:
            lowerCAmelCase_:							List[str]       =	distance[u] + w

   lowerCAmelCase_:							str       =	check_negative_cycle(lowercase							,				lowercase							,				lowercase					)
   if negative_cycle_exists:
      raise Exception("Negative cycle found"					)

   return distance


if __name__ == "__main__":
 import doctest

 doctest.testmod()

 a  :      List[str]            =    int(input("""Enter number of vertices: """).strip())
 a  :      Any            =    int(input("""Enter number of edges: """).strip())

 a  :      list[dict[str, int]]            =    [{} for _ in range(E)]

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

 a  :      List[Any]            =    int(input("""\nEnter shortest path source:""").strip())
 a  :      Tuple            =    bellman_ford(graph, V, E, source)
 print_distance(shortest_distance, 0)