


'''simple docstring'''






import contextlib
from multiprocessing import Pool, RLock

from tqdm.auto import tqdm

from ..utils import experimental, logging


__A   :    Optional[Any]											= logging.get_logger(__name__)






class   __snake_case			:







    """simple docstring"""



    lowercase  					=   None







@experimental
def 							UpperCamelCase_     (       A__   :  Tuple				,       A__   :  Any				,       A__   :  Tuple				,       A__   :  List[Any]				,       A__   :  Optional[Any]				,       A__   :  Any				,       A__   :  Union[str, Any]   ):
  '''simple docstring'''





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

  return _map_with_joblib(A__				,       A__				,       A__				,       A__				,       A__				,       A__				,       A__   )







def 							UpperCamelCase_     (       A__   :  Optional[Any]				,       A__   :  List[Any]				,       A__   :  Optional[Any]				,       A__   :  Tuple				,       A__   :  Dict				,       A__   :  Any				,       A__   :  List[str]   ):
  '''simple docstring'''





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

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

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

  return mapped







def 							UpperCamelCase_     (       A__   :  Any				,       A__   :  Union[str, Any]				,       A__   :  List[str]				,       A__   :  str				,       A__   :  Optional[Any]				,       A__   :  Any				,       A__   :  Any   ):
  '''simple docstring'''





  import joblib

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







@experimental
@contextlib.contextmanager
def 							UpperCamelCase_     (       A__   :  str   ):
  '''simple docstring'''





  lowerCAmelCase_     : Dict     =  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







'''simple docstring'''






def 							UpperCamelCase_     (       A__   :  list[list[int | float]]   ):
  '''simple docstring'''





  lowerCAmelCase_     : List[str]     =  len(A__   )
  lowerCAmelCase_     : Union[str, Any]     =  len(matrix[0]   )
  lowerCAmelCase_     : Optional[int]     =  min(A__				,       A__   )

  for row in range(A__   ):
    # Check if diagonal element is not zero
    if matrix[row][row] != 0:
      # Eliminate all the elements below the diagonal
      for col in range(row + 1				,       A__   ):
        lowerCAmelCase_     : int     =  matrix[col][row] / matrix[row][row]
        for i in range(A__				,       A__   ):
          matrix[col][i] -= multiplier * matrix[row][i]
    else:
      # Find a non-zero diagonal element to swap rows
      lowerCAmelCase_     : int     =  True
      for i in range(row + 1				,       A__   ):
        if matrix[i][row] != 0:
          lowerCAmelCase_,				lowerCAmelCase_     : List[Any]     =  matrix[i], matrix[row]
          lowerCAmelCase_     : Dict     =  False
          break
      if reduce:
        rank -= 1
        for i in range(A__   ):
          lowerCAmelCase_     : List[Any]     =  matrix[i][rank]

            # Reduce the row pointer by one to stay on the same row
      row -= 1

  return rank


if __name__ == "__main__":
  import doctest

  doctest.testmod()



