





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

import torch_xla.distributed.xla_multiprocessing as xmp







def   __lowerCamelCase   (				)						->							Dict:






		"""simple docstring"""

		A__     =  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   __lowerCamelCase   (				)						->							Tuple:






		"""simple docstring"""

		A__     =  parse_args()

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

		# Patch sys.argv
		A__     =  [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()










from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


A       :   Optional[int]					= {
    '''configuration_pix2struct''': [
        '''PIX2STRUCT_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''Pix2StructConfig''',
        '''Pix2StructTextConfig''',
        '''Pix2StructVisionConfig''',
    ],
    '''processing_pix2struct''': ['''Pix2StructProcessor'''],
}

try:
					if not is_vision_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					A       :   Optional[int]					= ['''Pix2StructImageProcessor''']


try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					A       :   Dict					= [
					    '''PIX2STRUCT_PRETRAINED_MODEL_ARCHIVE_LIST''',
					    '''Pix2StructPreTrainedModel''',
					    '''Pix2StructForConditionalGeneration''',
					    '''Pix2StructVisionModel''',
					    '''Pix2StructTextModel''',
					]

if TYPE_CHECKING:
					from .configuration_pixastruct import (
					    PIX2STRUCT_PRETRAINED_CONFIG_ARCHIVE_MAP,
					    PixaStructConfig,
					    PixaStructTextConfig,
					    PixaStructVisionConfig,
					)
					from .processing_pixastruct import PixaStructProcessor

					try:
										if not is_vision_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .image_processing_pixastruct import PixaStructImageProcessor

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_pixastruct import (
										    PIX2STRUCT_PRETRAINED_MODEL_ARCHIVE_LIST,
										    PixaStructForConditionalGeneration,
										    PixaStructPreTrainedModel,
										    PixaStructTextModel,
										    PixaStructVisionModel,
										)

else:
					import sys

					A       :   Any					= _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)



