





'''simple docstring'''






import os
import platform
import sys


__lowerCamelCase						: Union[str, Any]		=   '3'

print('Python version:', sys.version)

print('OS platform:', platform.platform())
print('OS architecture:', platform.machine())

try:
						import torch

						print('Torch version:', torch.__version__)
						print('Cuda available:', torch.cuda.is_available())
						print('Cuda version:', torch.version.cuda)
						print('CuDNN version:', torch.backends.cudnn.version())
						print('Number of GPUs available:', torch.cuda.device_count())
except ImportError:
						print('Torch version:', None)

try:
						import transformers

						print('transformers version:', transformers.__version__)
except ImportError:
						print('transformers version:', None)













'''simple docstring'''






import contextlib
from multiprocessing import Pool, RLock

from tqdm.auto import tqdm

from ..utils import experimental, logging


__lowerCamelCase						: Union[str, Any]		=   logging.get_logger(__name__)







class 		UpperCAmelCase   :


  """simple docstring"""







  lowerCAmelCase_					=				None




@experimental
def 					_a   (__SCREAMING_SNAKE_CASE  ,      __SCREAMING_SNAKE_CASE  ,      __SCREAMING_SNAKE_CASE  ,      __SCREAMING_SNAKE_CASE  ,      __SCREAMING_SNAKE_CASE  ,      __SCREAMING_SNAKE_CASE  ,      __SCREAMING_SNAKE_CASE   ):


  """simple docstring"""

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

  return _map_with_joblib(__SCREAMING_SNAKE_CASE  ,      __SCREAMING_SNAKE_CASE  ,      __SCREAMING_SNAKE_CASE  ,      __SCREAMING_SNAKE_CASE  ,      __SCREAMING_SNAKE_CASE  ,      __SCREAMING_SNAKE_CASE  ,      __SCREAMING_SNAKE_CASE   )


def 					_a   (__SCREAMING_SNAKE_CASE  ,      __SCREAMING_SNAKE_CASE  ,      __SCREAMING_SNAKE_CASE  ,      __SCREAMING_SNAKE_CASE  ,      __SCREAMING_SNAKE_CASE  ,      __SCREAMING_SNAKE_CASE  ,      __SCREAMING_SNAKE_CASE   ):


  """simple docstring"""

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

  if len(__SCREAMING_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(__SCREAMING_SNAKE_CASE   )}, '''
        f'''length: {sum(len(i[1]   ) for i in split_kwds   )}'''   )

  logger.info(
      f'''Spawning {num_proc} processes for {len(__SCREAMING_SNAKE_CASE   )} 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(__SCREAMING_SNAKE_CASE  ,      initargs=__SCREAMING_SNAKE_CASE  ,      initializer=__SCREAMING_SNAKE_CASE   ) as pool:
    _UpperCamelCase       			=pool.map(__SCREAMING_SNAKE_CASE  ,      __SCREAMING_SNAKE_CASE   )
  logger.info(f'''Finished {num_proc} processes'''   )
  _UpperCamelCase       			=[obj for proc_res in mapped for obj in proc_res]
  logger.info(f'''Unpacked {len(__SCREAMING_SNAKE_CASE   )} objects'''   )

  return mapped


def 					_a   (__SCREAMING_SNAKE_CASE  ,      __SCREAMING_SNAKE_CASE  ,      __SCREAMING_SNAKE_CASE  ,      __SCREAMING_SNAKE_CASE  ,      __SCREAMING_SNAKE_CASE  ,      __SCREAMING_SNAKE_CASE  ,      __SCREAMING_SNAKE_CASE   ):


  """simple docstring"""

  import joblib

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


@experimental
@contextlib.contextmanager
def 					_a   (__SCREAMING_SNAKE_CASE   ):


  """simple docstring"""

  _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






