




"""simple docstring"""


import contextlib
from multiprocessing import Pool, RLock

from tqdm.auto import tqdm

from ..utils import experimental, logging


_A													=      logging.get_logger(__name__)


class _lowerCamelCase    :
   _lowerCamelCase    :int     				=     None






@experimental
def 	lowercase_				(			__UpperCAmelCase    ,		__UpperCAmelCase    ,		__UpperCAmelCase    ,		__UpperCAmelCase    ,		__UpperCAmelCase    ,		__UpperCAmelCase    ,		__UpperCAmelCase				)						->    Optional[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 	lowercase_				(			__UpperCAmelCase    ,		__UpperCAmelCase    ,		__UpperCAmelCase    ,		__UpperCAmelCase    ,		__UpperCAmelCase    ,		__UpperCAmelCase    ,		__UpperCAmelCase				)						->    str:
      lowerCAmelCase__      :			Dict   =	num_proc if num_proc <= len(__UpperCAmelCase				) else len(__UpperCAmelCase				)
      lowerCAmelCase__      :			str   =	[]  # We organize the splits ourselve (contiguous splits)
      for index in range(__UpperCAmelCase				):
            lowerCAmelCase__      :			Any   =	len(__UpperCAmelCase				) // num_proc
            lowerCAmelCase__      :			Union[str, Any]   =	len(__UpperCAmelCase				) % num_proc
            lowerCAmelCase__      :			Tuple   =	div * index + min(__UpperCAmelCase    ,		__UpperCAmelCase				)
            lowerCAmelCase__      :			Union[str, Any]   =	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__      :			Optional[Any]   =	None, None
      if not disable_tqdm:
            lowerCAmelCase__ ,   lowerCAmelCase__      :			Tuple   =	(RLock(),), tqdm.set_lock
      with Pool(__UpperCAmelCase    ,		initargs=__UpperCAmelCase    ,		initializer=__UpperCAmelCase				) as pool:
            lowerCAmelCase__      :			Tuple   =	pool.map(__UpperCAmelCase    ,		__UpperCAmelCase				)
      logger.info(f"""Finished {num_proc} processes"""				)
      lowerCAmelCase__      :			str   =	[obj for proc_res in mapped for obj in proc_res]
      logger.info(f"""Unpacked {len(__UpperCAmelCase				)} objects"""				)

      return mapped



def 	lowercase_				(			__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 	lowercase_				(			__UpperCAmelCase				)						->    Any:
      lowerCAmelCase__      :			int   =	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__      :			List[Any]   =	None











"""simple docstring"""


def 	lowercase_				(			__UpperCAmelCase    ,		__UpperCAmelCase				)						->    str:
      return "\n".join(
          f"""{number} * {i} = {number * i}""" for i in range(1    ,		number_of_terms + 1				)				)


if __name__ == "__main__":
  print(multiplication_table(number=5, number_of_terms=1_0))





