


"""simple docstring"""
import warnings

from ...utils import logging
from .image_processing_dpt import DPTImageProcessor


SCREAMING_SNAKE_CASE :    Any									=				logging.get_logger(__name__)



class 			_UpperCAmelCase (							__snake_case				):






		'''simple docstring'''

		def __init__(self				,       *a_				,       **a_					):





			'''simple docstring'''

			warnings.warn(
			    '''The class DPTFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please'''
			    ''' use DPTImageProcessor instead.'''				,       a_				,       )
			super().__init__(*a_				,       **a_					)







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

import torch_xla.distributed.xla_multiprocessing as xmp

def a__    (       ):






  '''simple docstring'''





  __magic_name__				     =       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=A_,     default=1,     help="""Number of TPU cores to use (1 or 8)."""					)

  # positional
  parser.add_argument(
      """training_script""",     type=A_,     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=A_					)

  return parser.parse_args()

def a__    (       ):






  '''simple docstring'''





  __magic_name__				     =       parse_args()

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

  # Patch sys.argv
  __magic_name__				     =       [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()

