
'''simple docstring'''







from ctypes import c_float, sizeof
from enum import Enum
from typing import TYPE_CHECKING, Optional, Union


if TYPE_CHECKING:
      from .. import AutoFeatureExtractor, AutoProcessor, AutoTokenizer  # tests_ignore

class       lowerCamelCase_							(	lowerCAmelCase_  ):






   '''simple docstring'''

   A :     str				=	c_float


   @property
   def 	_UpperCamelCase       (  self ):
       return sizeof(self.value )





def 						snake_case__ (lowerCAmelCase_					,  lowerCAmelCase_					,  lowerCAmelCase_ = 0	):
    # < 0 is possible if using a dynamic axis
    if dimension <= 0:
        UpperCamelCase__      =			fixed_dimension

    dimension -= num_token_to_add
    return dimension





def 						snake_case__ (lowerCAmelCase_					,  lowerCAmelCase_	):
    return num_parameters * dtype.size





def 						snake_case__ (lowerCAmelCase_	):
    from .. import AutoFeatureExtractor, AutoProcessor, AutoTokenizer  # tests_ignore

    try:
        return AutoProcessor.from_pretrained(lowerCAmelCase_	)
    except (ValueError, OSError, KeyError):
        UpperCamelCase__    ,  UpperCamelCase__      =			None, None
        try:
            UpperCamelCase__      =			AutoTokenizer.from_pretrained(lowerCAmelCase_	)
        except (OSError, KeyError):
            pass
        try:
            UpperCamelCase__      =			AutoFeatureExtractor.from_pretrained(lowerCAmelCase_	)
        except (OSError, KeyError):
            pass

        if tokenizer is not None and feature_extractor is not None:
            raise ValueError(
                F'Couldn\'t auto-detect preprocessor for {model_name}. Found both a tokenizer and a feature extractor.'	)
        elif tokenizer is None and feature_extractor is None:
            return None
        elif tokenizer is not None:
            return tokenizer
        else:
            return feature_extractor









'''simple docstring'''







import heapq





def 						snake_case__ (lowerCAmelCase_					,  lowerCAmelCase_					,  lowerCAmelCase_	):
    UpperCamelCase__      =			[(0, start)]  # cost from start node,end node
    UpperCamelCase__      =			set()
    while heap:
        ((UpperCamelCase__)    ,  (UpperCamelCase__))      =			heapq.heappop(lowerCAmelCase_	)
        if u in visited:
            continue
        visited.add(lowerCAmelCase_	)
        if u == end:
            return cost
        for v, c in graph[u]:
            if v in visited:
                continue
            UpperCamelCase__      =			cost + c
            heapq.heappush(lowerCAmelCase_					,  (next_item, v)	)
    return -1


lowercase__     :  Any    					=			{
    'A': [['B', 2], ['C', 5]],
    'B': [['A', 2], ['D', 3], ['E', 1], ['F', 1]],
    'C': [['A', 5], ['F', 3]],
    'D': [['B', 3]],
    'E': [['B', 4], ['F', 3]],
    'F': [['C', 3], ['E', 3]],
}
lowercase__     :  Optional[int]    					=			{
    'B': [['C', 1]],
    'C': [['D', 1]],
    'D': [['F', 1]],
    'E': [['B', 1], ['F', 3]],
    'F': [],
}
lowercase__     :  Union[str, Any]    					=			{
    'B': [['C', 1]],
    'C': [['D', 1]],
    'D': [['F', 1]],
    'E': [['B', 1], ['G', 2]],
    'F': [],
    'G': [['F', 1]],
}

lowercase__     :  Union[str, Any]    					=			dijkstra(G, 'E', 'C')
print(short_distance)  # E -- 3 --> F -- 3 --> C == 6

lowercase__     :  Optional[int]    					=			dijkstra(Ga, 'E', 'F')
print(short_distance)  # E -- 3 --> F == 3

lowercase__     :  Any    					=			dijkstra(Ga, 'E', 'F')
print(short_distance)  # E -- 2 --> G -- 1 --> F == 3

if __name__ == "__main__":
      import doctest

      doctest.testmod()




