



"""simple docstring"""


from dataclasses import dataclass
from typing import List, Optional, Union

import numpy as np
import PIL
from PIL import Image

from ...utils import BaseOutput, is_torch_available, is_transformers_available







@dataclass
# Copied from diffusers.pipelines.stable_diffusion.__init__.StableDiffusionPipelineOutput with Stable->Alt
class  A_     (	SCREAMING_SNAKE_CASE_							):



						"""simple docstring"""
						__UpperCamelCase													=				42
						__UpperCamelCase													=				42


if is_transformers_available() and is_torch_available():
				from .modeling_roberta_series import RobertaSeriesModelWithTransformation
				from .pipeline_alt_diffusion import AltDiffusionPipeline
				from .pipeline_alt_diffusion_imgaimg import AltDiffusionImgaImgPipeline













'''simple docstring'''

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

import torch_xla.distributed.xla_multiprocessing as xmp






def 						_UpperCAmelCase     (	)      ->      Optional[Any]:





						"""simple docstring"""
						lowercase_   : List[str]   	=      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 						_UpperCAmelCase     (	)      ->      str:





						"""simple docstring"""
						lowercase_   : Optional[int]   	=      parse_args()

						# Import training_script as a module.
						lowercase_   : str   	=      Path(args.training_script				)
						sys.path.append(str(script_fpath.parent.resolve()				)				)
						lowercase_   : int   	=      script_fpath.stem
						lowercase_   : List[Any]   	=      importlib.import_module(a				)

						# Patch sys.argv
						lowercase_   : List[str]   	=      [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()
