


from typing import Callable, Optional

from .. import Features
from ..packaged_modules.generator.generator import Generator
from .abc import AbstractDatasetInputStream
class 					__magic_name__		(			__UpperCAmelCase     ):






       def __init__(   self  :    List[Any]  ,     snake_case__  :    Callable  ,     snake_case__  :    Optional[Features] = None  ,     snake_case__  :    str = None  ,     snake_case__  :    bool = False  ,     snake_case__  :    bool = False  ,     snake_case__  :    Optional[dict] = None  ,     snake_case__  :    Optional[int] = None  ,     **snake_case__  :    str  ,     ):

              '''simple docstring'''






              super().__init__(
                  features=snake_case__  ,     cache_dir=snake_case__  ,     keep_in_memory=snake_case__  ,     streaming=snake_case__  ,     num_proc=snake_case__  ,     **snake_case__  ,     )
              lowercase		:int       							=				Generator(
                  cache_dir=snake_case__  ,     features=snake_case__  ,     generator=snake_case__  ,     gen_kwargs=snake_case__  ,     **snake_case__  ,     )







       def  __snake_case						(   self  :    Optional[Any]				):

              '''simple docstring'''






              if self.streaming:
                     lowercase		:List[Any]       							=				self.builder.as_streaming_dataset(split='''train'''				)
              # Build regular (map-style) dataset
              else:
                     lowercase		:Any       							=				None
                     lowercase		:int       							=				None
                     lowercase		:List[Any]       							=				None
                     lowercase		:Dict       							=				None

                     self.builder.download_and_prepare(
                         download_config=snake_case__  ,     download_mode=snake_case__  ,     verification_mode=snake_case__  ,     base_path=snake_case__  ,     num_proc=self.num_proc  ,     )
                     lowercase		:Union[str, Any]       							=				self.builder.as_dataset(
                         split='''train'''  ,     verification_mode=snake_case__  ,     in_memory=self.keep_in_memory				)
              return dataset





"""simple docstring"""



def       lowerCamelCase					(a_						:int)     ->							str:
       if number > 0:
              raise ValueError('''input must be a negative integer''')
       lowercase		:Any       							=				len(bin(a_)[3:])
       lowercase		:Any       							=				bin(abs(a_) - (1 << binary_number_length))[3:]
       lowercase		:Tuple       							=				(
           (
               '''1'''
               + '''0''' * (binary_number_length - len(a_))
               + twos_complement_number
           )
           if number < 0
           else '''0'''
       )
       return "0b" + twos_complement_number


if __name__ == "__main__":
 import doctest

 doctest.testmod()

