





def lowerCAmelCase__(__snake_case							)       ->   float:







	'''simple docstring'''







	if not nums:  # Makes sure that the list is not empty
		raise ValueError('''List is empty'''							)

	lowerCamelCase__              =	sum(__snake_case							) / len(__snake_case							)  # Calculate the average
	return sum(abs(x - average							) for x in nums							) / len(__snake_case							)


if __name__ == "__main__":
			import doctest

			doctest.testmod()










import contextlib
from multiprocessing import Pool, RLock

from tqdm.auto import tqdm

from ..utils import experimental, logging


_a						=   logging.get_logger(__name__)






class       __A					:

			'''simple docstring'''







			lowerCAmelCase_							  =		None





@experimental
def lowerCAmelCase__(__snake_case ,__snake_case ,__snake_case ,__snake_case ,__snake_case ,__snake_case ,__snake_case							)       ->   Tuple:







	'''simple docstring'''







	if ParallelBackendConfig.backend_name is None:
		return _map_with_multiprocessing_pool(
		    __snake_case ,__snake_case ,__snake_case ,__snake_case ,__snake_case ,__snake_case ,__snake_case							)

	return _map_with_joblib(__snake_case ,__snake_case ,__snake_case ,__snake_case ,__snake_case ,__snake_case ,__snake_case							)





def lowerCAmelCase__(__snake_case ,__snake_case ,__snake_case ,__snake_case ,__snake_case ,__snake_case ,__snake_case							)       ->   int:







	'''simple docstring'''







	lowerCamelCase__              =	num_proc if num_proc <= len(__snake_case							) else len(__snake_case							)
	lowerCamelCase__              =	[]  # We organize the splits ourselve (contiguous splits)
	for index in range(__snake_case							):
		lowerCamelCase__              =	len(__snake_case							) // num_proc
		lowerCamelCase__              =	len(__snake_case							) % num_proc
		lowerCamelCase__              =	div * index + min(__snake_case ,__snake_case							)
		lowerCamelCase__              =	start + div + (1 if index < mod else 0)
		split_kwds.append((function, iterable[start:end], types, index, disable_tqdm, desc)							)

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

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

	return mapped





def lowerCAmelCase__(__snake_case ,__snake_case ,__snake_case ,__snake_case ,__snake_case ,__snake_case ,__snake_case							)       ->   List[str]:







	'''simple docstring'''







	import joblib

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





@experimental
@contextlib.contextmanager
def lowerCAmelCase__(__snake_case							)       ->   int:







	'''simple docstring'''







	lowerCamelCase__              =	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__              =	None



