





import contextlib
from multiprocessing import Pool, RLock

from tqdm.auto import tqdm

from ..utils import experimental, logging


SCREAMING_SNAKE_CASE__       :			str			      =						logging.get_logger(__name__)







class   __lowerCAmelCase			:
   _UpperCamelCase :						str     		=				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   ):
   a__	:						Any      		=  num_proc if num_proc <= len(lowerCamelCase   ) else len(lowerCamelCase   )
   a__	:						Any      		=  []  # We organize the splits ourselve (contiguous splits)
   for index in range(lowerCamelCase   ):
      a__	:						int      		=  len(lowerCamelCase   ) // num_proc
      a__	:						Optional[int]      		=  len(lowerCamelCase   ) % num_proc
      a__	:						List[Any]      		=  div * index + min(lowerCamelCase							, lowerCamelCase   )
      a__	:						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(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]}"""   )
   a__		,     a__	:						str      		=  None, None
   if not disable_tqdm:
      a__		,     a__	:						int      		=  (RLock(),), tqdm.set_lock
   with Pool(lowerCamelCase							, initargs=lowerCamelCase							, initializer=lowerCamelCase   ) as pool:
      a__	:						List[str]      		=  pool.map(lowerCamelCase							, lowerCamelCase   )
   logger.info(F"""Finished {num_proc} processes"""   )
   a__	:						List[Any]      		=  [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   ):
   a__	:						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:
      a__	:						Union[str, Any]      		=  None








from PIL import Image






def       _A  (      lowerCamelCase							, lowerCamelCase   ):

   def brightness(lowerCamelCase   ) -> float:
      return 128 + level + (c - 128)

   if not -255.0 <= level <= 255.0:
      raise ValueError("level must be between -255.0 (black) and 255.0 (white)"   )
   return img.point(lowerCamelCase   )


if __name__ == "__main__":
  # Load image
  with Image.open("""image_data/lena.jpg""") as img:
    # Change brightness to 100
    SCREAMING_SNAKE_CASE__       :			List[str]			      =						change_brightness(img, 1_0_0)
    brigt_img.save("""image_data/lena_brightness.png""", format="""png""")

