





def  SCREAMING_SNAKE_CASE   ( _UpperCAmelCase				)    ->  float:
    return 10 - x * x


def  SCREAMING_SNAKE_CASE   ( _UpperCAmelCase		,			_UpperCAmelCase				)    ->  float:
    # Bolzano theory in order to find if there is a root between a and b
    if equation(_UpperCAmelCase				) * equation(_UpperCAmelCase				) >= 0:
        raise ValueError('Wrong space!'				)

    lowerCamelCase__					:   List[Any]      				=	a
    while (b - a) >= 0.01:
        # Find middle point
        lowerCamelCase__					:   str      				=	(a + b) / 2
        # Check if middle point is root
        if equation(_UpperCAmelCase				) == 0.0:
            break
        # Decide the side to repeat the steps
        if equation(_UpperCAmelCase				) * equation(_UpperCAmelCase				) < 0:
            lowerCamelCase__					:   str      				=	c
        else:
            lowerCamelCase__					:   Any      				=	c
    return c


if __name__ == "__main__":
    import doctest

    doctest.testmod()

    print(bisection(-2, 5))
    print(bisection(0, 6))












import contextlib
from multiprocessing import Pool, RLock

from tqdm.auto import tqdm

from ..utils import experimental, logging


_UpperCAmelCase       : Union[str, Any]			     =       logging.get_logger(__name__)

class      lowerCAmelCase							:
 UpperCAmelCase__									=	None


@experimental
def  SCREAMING_SNAKE_CASE   ( _UpperCAmelCase		,			_UpperCAmelCase		,			_UpperCAmelCase		,			_UpperCAmelCase		,			_UpperCAmelCase		,			_UpperCAmelCase		,			_UpperCAmelCase				)    ->  Any:
    if ParallelBackendConfig.backend_name is None:
        return _map_with_multiprocessing_pool(
            _UpperCAmelCase		,			_UpperCAmelCase		,			_UpperCAmelCase		,			_UpperCAmelCase		,			_UpperCAmelCase		,			_UpperCAmelCase		,			_UpperCAmelCase				)

    return _map_with_joblib(_UpperCAmelCase		,			_UpperCAmelCase		,			_UpperCAmelCase		,			_UpperCAmelCase		,			_UpperCAmelCase		,			_UpperCAmelCase		,			_UpperCAmelCase				)


def  SCREAMING_SNAKE_CASE   ( _UpperCAmelCase		,			_UpperCAmelCase		,			_UpperCAmelCase		,			_UpperCAmelCase		,			_UpperCAmelCase		,			_UpperCAmelCase		,			_UpperCAmelCase				)    ->  Any:
    lowerCamelCase__					:   int      				=	num_proc if num_proc <= len(_UpperCAmelCase				) else len(_UpperCAmelCase				)
    lowerCamelCase__					:   Optional[int]      				=	[]  # We organize the splits ourselve (contiguous splits)
    for index in range(_UpperCAmelCase				):
        lowerCamelCase__					:   str      				=	len(_UpperCAmelCase				) // num_proc
        lowerCamelCase__					:   List[str]      				=	len(_UpperCAmelCase				) % num_proc
        lowerCamelCase__					:   Tuple      				=	div * index + min(_UpperCAmelCase		,			_UpperCAmelCase				)
        lowerCamelCase__					:   int      				=	start + div + (1 if index < mod else 0)
        split_kwds.append((function, iterable[start:end], types, index, disable_tqdm, desc)				)

    if len(_UpperCAmelCase				) != sum(len(i[1]				) for i in split_kwds				):
        raise ValueError(
            F"""Error dividing inputs iterable among processes. """
            F"""Total number of objects {len(_UpperCAmelCase				)}, """
            F"""length: {sum(len(i[1]				) for i in split_kwds				)}"""				)

    logger.info(
        F"""Spawning {num_proc} processes for {len(_UpperCAmelCase				)} objects in slices of {[len(i[1]				) for i in split_kwds]}"""				)
    lowerCamelCase__				,							lowerCamelCase__					:   List[str]      				=	None, None
    if not disable_tqdm:
        lowerCamelCase__				,							lowerCamelCase__					:   Union[str, Any]      				=	(RLock(),), tqdm.set_lock
    with Pool(_UpperCAmelCase		,			initargs=_UpperCAmelCase		,			initializer=_UpperCAmelCase				) as pool:
        lowerCamelCase__					:   Any      				=	pool.map(_UpperCAmelCase		,			_UpperCAmelCase				)
    logger.info(F"""Finished {num_proc} processes"""				)
    lowerCamelCase__					:   Union[str, Any]      				=	[obj for proc_res in mapped for obj in proc_res]
    logger.info(F"""Unpacked {len(_UpperCAmelCase				)} objects"""				)

    return mapped


def  SCREAMING_SNAKE_CASE   ( _UpperCAmelCase		,			_UpperCAmelCase		,			_UpperCAmelCase		,			_UpperCAmelCase		,			_UpperCAmelCase		,			_UpperCAmelCase		,			_UpperCAmelCase				)    ->  int:
    # progress bar is not yet supported for _map_with_joblib, because tqdm couldn't accurately be applied to joblib,
    # and it requires monkey-patching joblib internal classes which is subject to change
    import joblib

    with joblib.parallel_backend(ParallelBackendConfig.backend_name		,			n_jobs=_UpperCAmelCase				):
        return joblib.Parallel()(
            joblib.delayed(_UpperCAmelCase				)((function, obj, types, None, True, None)				) for obj in iterable				)


@experimental
@contextlib.contextmanager
def  SCREAMING_SNAKE_CASE   ( _UpperCAmelCase				)    ->  Tuple:
    lowerCamelCase__					:   List[str]      				=	backend_name

    if backend_name == "spark":
        from joblibspark import register_spark

        register_spark()

        # TODO: call create_cache_and_write_probe if "download" in steps
        # TODO: raise NotImplementedError when Dataset.map etc is called

    try:
        yield
    finally:
        lowerCamelCase__					:   str      				=	None





