



"""simple docstring"""

from typing import Optional

from .. import Features, NamedSplit
from ..packaged_modules.text.text import Text
from ..utils.typing import NestedDataStructureLike, PathLike
from .abc import AbstractDatasetReader







class    __lowercase     (					SCREAMING_SNAKE_CASE__):







						"""simple docstring"""







						def __init__(self   ,		lowercase__   ,		lowercase__ = None   ,		lowercase__ = None   ,		lowercase__ = None   ,		lowercase__ = False   ,		lowercase__ = False   ,		lowercase__ = None   ,		**lowercase__   ,		):
											super().__init__(
											    _lowercase   ,		split=_lowercase   ,		features=_lowercase   ,		cache_dir=_lowercase   ,		keep_in_memory=_lowercase   ,		streaming=_lowercase   ,		num_proc=_lowercase   ,		**_lowercase   ,		)
											snake_case_					:		Optional[Any] 					=					path_or_paths if isinstance(_lowercase   ,		_lowercase       ) else {self.split: path_or_paths}
											snake_case_					:		Optional[int] 					=					Text(
											    cache_dir=_lowercase   ,		data_files=_lowercase   ,		features=_lowercase   ,		**_lowercase   ,		)







						def 						__UpperCamelCase							(self       ):

											if self.streaming:
																snake_case_					:		Optional[int] 					=					self.builder.as_streaming_dataset(split=self.split       )
											# Build regular (map-style) dataset
											else:
																snake_case_					:		Optional[int] 					=					None
																snake_case_					:		Optional[int] 					=					None
																snake_case_					:		Union[str, Any] 					=					None
																snake_case_					:		List[Any] 					=					None

																self.builder.download_and_prepare(
																    download_config=_lowercase   ,		download_mode=_lowercase   ,		verification_mode=_lowercase   ,		base_path=_lowercase   ,		num_proc=self.num_proc   ,		)
																snake_case_					:		Optional[Any] 					=					self.builder.as_dataset(
																    split=self.split   ,		verification_mode=_lowercase   ,		in_memory=self.keep_in_memory       )
											return dataset









"""simple docstring"""

import random







def 							SCREAMING_SNAKE_CASE__      (		SCREAMING_SNAKE_CASE__ :  int				,    SCREAMING_SNAKE_CASE__ :  float				,    SCREAMING_SNAKE_CASE__ :  bool = False			):



					"""simple docstring"""





					snake_case_					:		dict 					=					{i: [] for i in range(SCREAMING_SNAKE_CASE__			)}

					# if probability is greater or equal than 1, then generate a complete graph
					if probability >= 1:
										return complete_graph(SCREAMING_SNAKE_CASE__			)
					# if probability is lower or equal than 0, then return a graph without edges
					if probability <= 0:
										return graph

					# for each couple of nodes, add an edge from u to v
					# if the number randomly generated is greater than probability probability
					for i in range(SCREAMING_SNAKE_CASE__			):
										for j in range(i + 1				,    SCREAMING_SNAKE_CASE__			):
															if random.random() < probability:
																				graph[i].append(SCREAMING_SNAKE_CASE__			)
																				if not directed:
																									# if the graph is undirected, add an edge in from j to i, either
																									graph[j].append(SCREAMING_SNAKE_CASE__			)
					return graph







def 							SCREAMING_SNAKE_CASE__      (		SCREAMING_SNAKE_CASE__ :  int			):



					"""simple docstring"""





					return {
					    i: [j for j in range(SCREAMING_SNAKE_CASE__			) if i != j] for i in range(SCREAMING_SNAKE_CASE__			)
					}


if __name__ == "__main__":
			import doctest

			doctest.testmod()




