



def 	__a					(   lowerCAmelCase_       : list[int]      ,lowerCAmelCase_       : list[int]      ,lowerCAmelCase_       : int    )				->			bool:






						'''simple docstring'''



						return not any(
						    neighbour == 1 and colored_vertices[i] == color
						    for i, neighbour in enumerate(lowerCAmelCase_    )    )



def 	__a					(   lowerCAmelCase_       : list[list[int]]      ,lowerCAmelCase_       : int      ,lowerCAmelCase_       : list[int]      ,lowerCAmelCase_       : int    )				->			bool:






						'''simple docstring'''



						if index == len(lowerCAmelCase_    ):
												return True

						# Recursive Step
						for i in range(lowerCAmelCase_    ):
												if valid_coloring(graph[index]      ,lowerCAmelCase_      ,lowerCAmelCase_    ):
																		# Color current vertex
																		UpperCAmelCase_=       i
																		# Validate coloring
																		if util_color(lowerCAmelCase_      ,lowerCAmelCase_      ,lowerCAmelCase_      ,index + 1    ):
																								return True
																		# Backtrack
																		UpperCAmelCase_=       -1
						return False



def 	__a					(   lowerCAmelCase_       : list[list[int]]      ,lowerCAmelCase_       : int    )				->			list[int]:






						'''simple docstring'''



						UpperCAmelCase_=       [-1] * len(lowerCAmelCase_    )

						if util_color(lowerCAmelCase_      ,lowerCAmelCase_      ,lowerCAmelCase_      ,0    ):
												return colored_vertices

						return []









from typing import Optional

import pyspark

from .. import Features, NamedSplit
from ..download import DownloadMode
from ..packaged_modules.spark.spark import Spark
from .abc import AbstractDatasetReader






class 		lowercase						(			snake_case__):






	"""simple docstring"""


	def __init__(     self     :						int						,  __UpperCAmelCase     :						pyspark.sql.DataFrame						,  __UpperCAmelCase     :						Optional[NamedSplit] = None						,  __UpperCAmelCase     :						Optional[Features] = None						,  __UpperCAmelCase     :						bool = True						,  __UpperCAmelCase     :						str = None						,  __UpperCAmelCase     :						bool = False						,  __UpperCAmelCase     :						str = None						,  __UpperCAmelCase     :						bool = True						,  __UpperCAmelCase     :						str = "arrow"						,  **__UpperCAmelCase     :						str						,  )      ->			Dict:
							super().__init__(
							    split=__UpperCAmelCase						,  features=__UpperCAmelCase						,  cache_dir=__UpperCAmelCase						,  keep_in_memory=__UpperCAmelCase						,  streaming=__UpperCAmelCase						,  **__UpperCAmelCase						,  )
							UpperCAmelCase_=       load_from_cache_file
							UpperCAmelCase_=       file_format
							UpperCAmelCase_=       Spark(
							    df=__UpperCAmelCase						,  features=__UpperCAmelCase						,  cache_dir=__UpperCAmelCase						,  working_dir=__UpperCAmelCase						,  **__UpperCAmelCase						,  )




	def   _SCREAMING_SNAKE_CASE		(     self     :						Any					)      ->			Dict:
							if self.streaming:
													return self.builder.as_streaming_dataset(split=self.split					)
							UpperCAmelCase_=       None if self._load_from_cache_file else DownloadMode.FORCE_REDOWNLOAD
							self.builder.download_and_prepare(
							    download_mode=__UpperCAmelCase						,  file_format=self._file_format						,  )
							return self.builder.as_dataset(split=self.split					)




