





def      lowerCAmelCase_ (       __a		)     ->		list:







  """simple docstring"""





  if any(not isinstance(__a	,    __a		) or x < 0 for x in sequence		):
    raise TypeError("Sequence must be list of non-negative integers"		)
  for _ in range(len(__a		)		):
    for i, (rod_upper, rod_lower) in enumerate(zip(__a	,    sequence[1:]		)		):
      if rod_upper > rod_lower:
        sequence[i] -= rod_upper - rod_lower
        sequence[i + 1] += rod_upper - rod_lower
  return sequence


if __name__ == "__main__":
     assert bead_sort([5, 4, 3, 2, 1]) == [1, 2, 3, 4, 5]
     assert bead_sort([7, 9, 4, 3, 5]) == [3, 4, 5, 7, 9]





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      (			A__       ):






				'''simple docstring'''



				def __init__(       self			:int			,			lowerCAmelCase__			:NestedDataStructureLike[PathLike]			,			lowerCAmelCase__			:Optional[NamedSplit] = None			,			lowerCAmelCase__			:Optional[Features] = None			,			lowerCAmelCase__			:str = None			,			lowerCAmelCase__			:bool = False			,			lowerCAmelCase__			:bool = False			,			lowerCAmelCase__			:Optional[int] = None			,			**lowerCAmelCase__			:Optional[int]			,			)		->			Tuple:
										super().__init__(
										    lowerCAmelCase__			,			split=lowerCAmelCase__			,			features=lowerCAmelCase__			,			cache_dir=lowerCAmelCase__			,			keep_in_memory=lowerCAmelCase__			,			streaming=lowerCAmelCase__			,			num_proc=lowerCAmelCase__			,			**lowerCAmelCase__			,			)
										__SCREAMING_SNAKE_CASE						:     List[str]					=		path_or_paths if isinstance(lowerCAmelCase__			,			lowerCAmelCase__	) else {self.split: path_or_paths}
										__SCREAMING_SNAKE_CASE						:     int					=		Text(
										    cache_dir=lowerCAmelCase__			,			data_files=lowerCAmelCase__			,			features=lowerCAmelCase__			,			**lowerCAmelCase__			,			)



				def 		__magic_name__(       self			:Dict	)		->			Tuple:
										# Build iterable dataset
										if self.streaming:
																__SCREAMING_SNAKE_CASE						:     int					=		self.builder.as_streaming_dataset(split=self.split	)
										# Build regular (map-style) dataset
										else:
																__SCREAMING_SNAKE_CASE						:     List[str]					=		None
																__SCREAMING_SNAKE_CASE						:     str					=		None
																__SCREAMING_SNAKE_CASE						:     Dict					=		None
																__SCREAMING_SNAKE_CASE						:     Tuple					=		None

																self.builder.download_and_prepare(
																    download_config=lowerCAmelCase__			,			download_mode=lowerCAmelCase__			,			verification_mode=lowerCAmelCase__			,			base_path=lowerCAmelCase__			,			num_proc=self.num_proc			,			)
																__SCREAMING_SNAKE_CASE						:     Optional[int]					=		self.builder.as_dataset(
																    split=self.split			,			verification_mode=lowerCAmelCase__			,			in_memory=self.keep_in_memory	)
										return dataset
