

'''simple docstring'''


import contextlib
from multiprocessing import Pool, RLock

from tqdm.auto import tqdm

from ..utils import experimental, logging


lowerCAmelCase__						:       str										=						logging.get_logger(__name__)




class     a			:






						"""simple docstring"""




						__UpperCAmelCase			     =    None





@experimental
def 	_a       (				__lowerCAmelCase		:      str   ,							__lowerCAmelCase		:      str   ,							__lowerCAmelCase		:      List[Any]   ,							__lowerCAmelCase		:      Optional[int]   ,							__lowerCAmelCase		:      int   ,							__lowerCAmelCase		:      Any   ,							__lowerCAmelCase		:      Tuple     ):

		"""simple docstring"""

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

		return _map_with_joblib(__lowerCAmelCase   ,							__lowerCAmelCase   ,							__lowerCAmelCase   ,							__lowerCAmelCase   ,							__lowerCAmelCase   ,							__lowerCAmelCase   ,							__lowerCAmelCase     )




def 	_a       (				__lowerCAmelCase		:      Dict   ,							__lowerCAmelCase		:      Optional[int]   ,							__lowerCAmelCase		:      Optional[Any]   ,							__lowerCAmelCase		:      Any   ,							__lowerCAmelCase		:      Union[str, Any]   ,							__lowerCAmelCase		:      Optional[Any]   ,							__lowerCAmelCase		:      Any     ):

		"""simple docstring"""

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

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

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

		return mapped




def 	_a       (				__lowerCAmelCase		:      Tuple   ,							__lowerCAmelCase		:      Optional[int]   ,							__lowerCAmelCase		:      List[str]   ,							__lowerCAmelCase		:      str   ,							__lowerCAmelCase		:      List[str]   ,							__lowerCAmelCase		:      int   ,							__lowerCAmelCase		:      str     ):

		"""simple docstring"""

		import joblib

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





@experimental
@contextlib.contextmanager
def 	_a       (				__lowerCAmelCase		:      str     ):

		"""simple docstring"""

		snake_case__						:       Any       						=  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:
				snake_case__						:       List[Any]       						=  None






'''simple docstring'''


def 	_a       (				__lowerCAmelCase		:      int     ):

		"""simple docstring"""

		if p < 2:
				raise ValueError('''p should not be less than 2!'''     )
		elif p == 2:
				return True

		snake_case__						:       Any       						=  4
		snake_case__						:       int       						=  (1 << p) - 1
		for _ in range(p - 2     ):
				snake_case__						:       Tuple       						=  ((s * s) - 2) % m
		return s == 0


if __name__ == "__main__":
					print(lucas_lehmer_test(7))
					print(lucas_lehmer_test(11))



