






from __future__ import annotations

from collections import deque
from queue import Queue
from timeit import timeit

__A      :       Any      =	{
    'A': ['B', 'C'],
    'B': ['A', 'D', 'E'],
    'C': ['A', 'F'],
    'D': ['B'],
    'E': ['B', 'F'],
    'F': ['C', 'E'],
}


def 						_UpperCamelCase							(     snake_case__							,			snake_case__							):
      __A		   =      {start}
      __A		   =      [start]
      __A		   =      Queue()
      queue.put(snake_case__							)
      while not queue.empty():
            __A		   =      queue.get()
            for w in graph[v]:
                  if w not in explored:
                        explored.add(snake_case__							)
                        result.append(snake_case__							)
                        queue.put(snake_case__							)
      return result


def 						_UpperCamelCase							(     snake_case__							,			snake_case__							):
      __A		   =      {start}
      __A		   =      [start]
      __A		   =      deque([start]							)
      while queue:
            __A		   =      queue.popleft()
            for child in graph[v]:
                  if child not in visited:
                        visited.add(snake_case__							)
                        result.append(snake_case__							)
                        queue.append(snake_case__							)
      return result


def 						_UpperCamelCase							(     snake_case__							):
      __A		   =      f"from __main__ import G, {name}"
      __A		   =      10_000
      __A		   =      timeit(f"{name}(G, 'A')"							,			setup=snake_case__							,			number=snake_case__							)
      print(f"{name:<35} finished {number} runs in {res:.5f} seconds"							)


if __name__ == "__main__":
       import doctest

       doctest.testmod()

       benchmark_function('breadth_first_search')
       benchmark_function('breadth_first_search_with_deque')
       # breadth_first_search                finished 10000 runs in 0.20999 seconds
       # breadth_first_search_with_deque     finished 10000 runs in 0.01421 seconds










'''simple docstring'''







from typing import List

import datasets
from datasets.tasks import ImageClassification

from ..folder_based_builder import folder_based_builder


__A      :       Tuple      =	datasets.utils.logging.get_logger(__name__)






class 					a__    (			folder_based_builder.FolderBasedBuilderConfig						):
     '''simple docstring'''







     _snake_case             =  None
     _snake_case             =  None







class 					a__    (			folder_based_builder.FolderBasedBuilder						):
     '''simple docstring'''







     _snake_case             =  datasets.Image()
     _snake_case             =  'image'
     _snake_case             =  ImageFolderConfig
     _snake_case             =  42  # definition at the bottom of the script
     _snake_case             =  ImageClassification(image_column='image' ,						label_column='label'						)







__A      :       Any      =	[
    '.blp',
    '.bmp',
    '.dib',
    '.bufr',
    '.cur',
    '.pcx',
    '.dcx',
    '.dds',
    '.ps',
    '.eps',
    '.fit',
    '.fits',
    '.fli',
    '.flc',
    '.ftc',
    '.ftu',
    '.gbr',
    '.gif',
    '.grib',
    '.h5',
    '.hdf',
    '.png',
    '.apng',
    '.jp2',
    '.j2k',
    '.jpc',
    '.jpf',
    '.jpx',
    '.j2c',
    '.icns',
    '.ico',
    '.im',
    '.iim',
    '.tif',
    '.tiff',
    '.jfif',
    '.jpe',
    '.jpg',
    '.jpeg',
    '.mpg',
    '.mpeg',
    '.msp',
    '.pcd',
    '.pxr',
    '.pbm',
    '.pgm',
    '.ppm',
    '.pnm',
    '.psd',
    '.bw',
    '.rgb',
    '.rgba',
    '.sgi',
    '.ras',
    '.tga',
    '.icb',
    '.vda',
    '.vst',
    '.webp',
    '.wmf',
    '.emf',
    '.xbm',
    '.xpm',
]
__A      :       List[Any]      =	IMAGE_EXTENSIONS


