



def  lowerCamelCase_	(      lowerCAmelCase__	:	int				)       ->							str:

							'''simple docstring'''






							A      						=    int(lowerCAmelCase__				)
							if decimal in (0, 1):  # Exit cases for the recursion
														return str(lowerCAmelCase__				)
							A						,   A      						=    divmod(lowerCAmelCase__			,	2				)
							return binary_recursive(lowerCAmelCase__				) + str(lowerCAmelCase__				)






def  lowerCamelCase_	(      lowerCAmelCase__	:	str				)       ->							str:

							'''simple docstring'''






							A      						=    str(lowerCAmelCase__				).strip()
							if not number:
														raise ValueError('No input value was provided'				)
							A      						=    '-' if number.startswith('-'				) else ''
							A      						=    number.lstrip('-'				)
							if not number.isnumeric():
														raise ValueError('Input value is not an integer'				)
							return F'''{negative}0b{binary_recursive(int(lowerCAmelCase__				)				)}'''


if __name__ == "__main__":
				from doctest import testmod

				testmod()




from typing import Callable, Optional

from .. import Features
from ..packaged_modules.generator.generator import Generator
from .abc import AbstractDatasetInputStream



class        lowerCAmelCase__					(  _lowerCamelCase       ):


				def __init__(							self      :  int						, __UpperCamelCase      :  Callable						, __UpperCamelCase      :  Optional[Features] = None						, __UpperCamelCase      :  str = None						, __UpperCamelCase      :  bool = False						, __UpperCamelCase      :  bool = False						, __UpperCamelCase      :  Optional[dict] = None						, __UpperCamelCase      :  Optional[int] = None						, **__UpperCamelCase      :  str						, )		->     List[str]:
											super().__init__(
											    features=__UpperCamelCase						, cache_dir=__UpperCamelCase						, keep_in_memory=__UpperCamelCase						, streaming=__UpperCamelCase						, num_proc=__UpperCamelCase						, **__UpperCamelCase						, )
											A      						=    Generator(
											    cache_dir=__UpperCamelCase						, features=__UpperCamelCase						, generator=__UpperCamelCase						, gen_kwargs=__UpperCamelCase						, **__UpperCamelCase						, )


				def __UpperCamelCase						(							self      :  Union[str, Any]       )		->     Tuple:
											# Build iterable dataset
											if self.streaming:
																		A      						=    self.builder.as_streaming_dataset(split='train'       )
											# Build regular (map-style) dataset
											else:
																		A      						=    None
																		A      						=    None
																		A      						=    None
																		A      						=    None

																		self.builder.download_and_prepare(
																		    download_config=__UpperCamelCase						, download_mode=__UpperCamelCase						, verification_mode=__UpperCamelCase						, base_path=__UpperCamelCase						, num_proc=self.num_proc						, )
																		A      						=    self.builder.as_dataset(
																		    split='train'						, verification_mode=__UpperCamelCase						, in_memory=self.keep_in_memory       )
											return dataset