



"""simple docstring"""





import contextlib
from multiprocessing import Pool, RLock

from tqdm.auto import tqdm

from ..utils import experimental, logging


lowerCamelCase       	=						logging.get_logger(__name__)
class 				lowercase__       :







       '''simple docstring'''


       UpperCamelCase						=					None



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

      return mapped
def        a__     (				lowerCAmelCase__     ,      lowerCAmelCase__     ,      lowerCAmelCase__     ,      lowerCAmelCase__     ,      lowerCAmelCase__     ,      lowerCAmelCase__     ,      lowerCAmelCase__				):
      # 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=lowerCAmelCase__				):
            return joblib.Parallel()(
                joblib.delayed(lowerCAmelCase__				)((function, obj, types, None, True, None)				) for obj in iterable				)


@experimental
@contextlib.contextmanager
def        a__     (				lowerCAmelCase__				):
      UpperCAmelCase_      			=							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:
            UpperCAmelCase_      			=							None









"""simple docstring"""





from __future__ import annotations

from collections import namedtuple
from dataclasses import dataclass
@dataclass
class 				lowercase__       :







       '''simple docstring'''


       UpperCamelCase						=					42
       UpperCamelCase						=					None
       UpperCamelCase						=					None



lowerCamelCase       	=						namedtuple("""CoinsDistribResult""", """moves excess""")
def        a__     (				lowerCAmelCase__				):

      if root is None:
            return 0

      # Validation
      def count_nodes(lowerCAmelCase__				) -> int:
            if node is None:
                  return 0

            return count_nodes(node.left				) + count_nodes(node.right				) + 1

      def count_coins(lowerCAmelCase__				) -> int:
            if node is None:
                  return 0

            return count_coins(node.left				) + count_coins(node.right				) + node.data

      if count_nodes(lowerCAmelCase__				) != count_coins(lowerCAmelCase__				):
            raise ValueError("The nodes number should be same as the number of coins"				)

      # Main calculation
      def get_distrib(lowerCAmelCase__				) -> CoinsDistribResult:

            if node is None:
                  return CoinsDistribResult(0     ,      1				)

            UpperCAmelCase_			,   UpperCAmelCase_      			=							get_distrib(node.left				)
            UpperCAmelCase_			,   UpperCAmelCase_      			=							get_distrib(node.right				)

            UpperCAmelCase_      			=							1 - left_distrib_excess
            UpperCAmelCase_      			=							1 - right_distrib_excess

            UpperCAmelCase_      			=							(
                left_distrib_moves
                + right_distrib_moves
                + abs(lowerCAmelCase__				)
                + abs(lowerCAmelCase__				)
            )
            UpperCAmelCase_      			=							node.data - coins_to_left - coins_to_right

            return CoinsDistribResult(lowerCAmelCase__     ,      lowerCAmelCase__				)

      return get_distrib(lowerCAmelCase__				)[0]


if __name__ == "__main__":
  import doctest

  doctest.testmod()




