




import json
import logging
import os
import subprocess
from argparse import ArgumentParser


lowercase__    :					Optional[Any]					=						logging.getLogger(__name__)


def 						lowerCamelCase__   (		):







	'''simple docstring'''





	snake_case_		   =					ArgumentParser()
	snake_case_   ,				snake_case_		   =					parser.parse_known_args()
	for arg in unknown:
		if arg.startswith(("-", "--")							):
			parser.add_argument(arg.split("="							)[0]							)

	return parser.parse_args()


def 						lowerCamelCase__   (		):







	'''simple docstring'''





	snake_case_		   =					parse_args()
	snake_case_		   =					8888
	snake_case_		   =					int(os.environ["SM_NUM_GPUS"]							)
	snake_case_		   =					json.loads(os.environ["SM_HOSTS"]							)
	snake_case_		   =					len(_A							)
	snake_case_		   =					os.environ["SM_CURRENT_HOST"]
	snake_case_		   =					hosts.index(_A							)
	snake_case_		   =					"INFO"

	if num_nodes > 1:
		snake_case_		   =					f"python -m torch.distributed.launch \\n                --nnodes={num_nodes}  \\n                --node_rank={rank}  \\n                --nproc_per_node={num_gpus}  \\n                --master_addr={hosts[0]}  \\n                --master_port={port} \\n                ./run_glue.py \\n                {''.join(['nested fstring' for parameter,value in args.__dict__.items()]							)}"
	else:
		snake_case_		   =					f"python -m torch.distributed.launch \\n            --nproc_per_node={num_gpus}  \\n            ./run_glue.py \\n            {''.join(['nested fstring' for parameter,value in args.__dict__.items()]							)}"
	try:
		subprocess.run(_A					,     shell=_A							)
	except Exception as e:
		logger.info(_A							)


if __name__ == "__main__":
		main()






from typing import TYPE_CHECKING

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


lowercase__    :					List[str]					=						{
    "configuration_xlm_prophetnet": ["XLM_PROPHETNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "XLMProphetNetConfig"],
}

try:
		if not is_sentencepiece_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowercase__    :					Optional[Any]					=						["XLMProphetNetTokenizer"]

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowercase__    :					List[Any]					=						[
		    "XLM_PROPHETNET_PRETRAINED_MODEL_ARCHIVE_LIST",
		    "XLMProphetNetDecoder",
		    "XLMProphetNetEncoder",
		    "XLMProphetNetForCausalLM",
		    "XLMProphetNetForConditionalGeneration",
		    "XLMProphetNetModel",
		    "XLMProphetNetPreTrainedModel",
		]


if TYPE_CHECKING:
		from .configuration_xlm_prophetnet import XLM_PROPHETNET_PRETRAINED_CONFIG_ARCHIVE_MAP, XLMProphetNetConfig

		try:
				if not is_sentencepiece_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .tokenization_xlm_prophetnet import XLMProphetNetTokenizer

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_xlm_prophetnet import (
				    XLM_PROPHETNET_PRETRAINED_MODEL_ARCHIVE_LIST,
				    XLMProphetNetDecoder,
				    XLMProphetNetEncoder,
				    XLMProphetNetForCausalLM,
				    XLMProphetNetForConditionalGeneration,
				    XLMProphetNetModel,
				    XLMProphetNetPreTrainedModel,
				)

else:
		import sys

		lowercase__    :					Any					=						_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)
