



"""simple docstring"""





import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path

import torch_xla.distributed.xla_multiprocessing as xmp
def        a__     (				):
      UpperCAmelCase_      			=							ArgumentParser(
          description=(
              "PyTorch TPU distributed training launch helper utility that will spawn up multiple distributed processes"
          )				)

      # Optional arguments for the launch helper
      parser.add_argument("--num_cores"     ,      type=lowerCAmelCase__     ,      default=1     ,      help="Number of TPU cores to use (1 or 8)."				)

      # positional
      parser.add_argument(
          "training_script"     ,      type=lowerCAmelCase__     ,      help=(
              "The full path to the single TPU training "
              "program/script to be launched in parallel, "
              "followed by all the arguments for the "
              "training script"
          )     ,      )

      # rest from the training program
      parser.add_argument("training_script_args"     ,      nargs=lowerCAmelCase__				)

      return parser.parse_args()
def        a__     (				):
      UpperCAmelCase_      			=							parse_args()

      # Import training_script as a module.
      UpperCAmelCase_      			=							Path(args.training_script				)
      sys.path.append(str(script_fpath.parent.resolve()				)				)
      UpperCAmelCase_      			=							script_fpath.stem
      UpperCAmelCase_      			=							importlib.import_module(lowerCAmelCase__				)

      # Patch sys.argv
      UpperCAmelCase_      			=							[args.training_script] + args.training_script_args + ["--tpu_num_cores", str(args.num_cores				)]

      xmp.spawn(mod._mp_fn     ,      args=()     ,      nprocs=args.num_cores				)


if __name__ == "__main__":
  main()









"""simple docstring"""





import warnings

from ...utils import logging
from .image_processing_flava import FlavaImageProcessor


lowerCamelCase       	=						logging.get_logger(__name__)
class 				lowercase__       (   SCREAMING_SNAKE_CASE				):







       '''simple docstring'''


       def __init__(							self      :  Union[str, Any]		,    *_UpperCAmelCase      :  List[Any]		,    **_UpperCAmelCase      :  Union[str, Any]   )			->						None:


             '''simple docstring'''




             warnings.warn(
                 "The class FlavaFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please"
                 " use FlavaImageProcessor instead."		,    _UpperCAmelCase		,    )
             super().__init__(*_UpperCAmelCase		,    **_UpperCAmelCase   )




