




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

import torch_xla.distributed.xla_multiprocessing as xmp


def 							__SCREAMING_SNAKE_CASE						(    ):

						'''simple docstring'''


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

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

						return parser.parse_args()


def 							__SCREAMING_SNAKE_CASE						(    ):

						'''simple docstring'''


						_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(snake_case_		)

						# 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()










from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_torch_available,
)


lowercase_			:       List[str]						       =				{
    'configuration_rwkv': ['RWKV_PRETRAINED_CONFIG_ARCHIVE_MAP', 'RwkvConfig', 'RwkvOnnxConfig'],
}

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				lowercase_			:       Any						       =				[
				    'RWKV_PRETRAINED_MODEL_ARCHIVE_LIST',
				    'RwkvForCausalLM',
				    'RwkvModel',
				    'RwkvPreTrainedModel',
				]


if TYPE_CHECKING:
				from .configuration_rwkv import RWKV_PRETRAINED_CONFIG_ARCHIVE_MAP, RwkvConfig, RwkvOnnxConfig

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_rwkv import (
								    RWKV_PRETRAINED_MODEL_ARCHIVE_LIST,
								    RwkvForCausalLM,
								    RwkvModel,
								    RwkvPreTrainedModel,
								)
else:
				import sys

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




