

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

import torch_xla.distributed.xla_multiprocessing as xmp



def       __lowerCAmelCase      (						):
	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=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      (						):
	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(A    )

	# 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 ...configuration_utils import PretrainedConfig
from ...utils import logging


_a:    List[str] 							=			logging.get_logger(__name__)

_a:    Any 							=			{
    """sayakpaul/vit-msn-base""": """https://huggingface.co/sayakpaul/vit-msn-base/resolve/main/config.json""",
    # See all ViT MSN models at https://huggingface.co/models?filter=vit_msn
}

class 						__UpperCamelCase    (					lowercase						):
	SCREAMING_SNAKE_CASE__    				=     'vit_msn'




	def __init__(		self	:						Union[str, Any]		,	lowerCAmelCase	:						Optional[int]=768		,	lowerCAmelCase	:						Dict=12		,	lowerCAmelCase	:						str=12		,	lowerCAmelCase	:						List[str]=3_072		,	lowerCAmelCase	:						Tuple="gelu"		,	lowerCAmelCase	:						int=0.0		,	lowerCAmelCase	:						Optional[int]=0.0		,	lowerCAmelCase	:						Union[str, Any]=0.02		,	lowerCAmelCase	:						str=1e-06		,	lowerCAmelCase	:						Dict=224		,	lowerCAmelCase	:						str=16		,	lowerCAmelCase	:						List[Any]=3		,	lowerCAmelCase	:						Union[str, Any]=True		,	**lowerCAmelCase	:						List[str]		,	):


		'''simple docstring'''







		super().__init__(**lowerCAmelCase							)

		UpperCAmelCase_       				=			hidden_size
		UpperCAmelCase_       				=			num_hidden_layers
		UpperCAmelCase_       				=			num_attention_heads
		UpperCAmelCase_       				=			intermediate_size
		UpperCAmelCase_       				=			hidden_act
		UpperCAmelCase_       				=			hidden_dropout_prob
		UpperCAmelCase_       				=			attention_probs_dropout_prob
		UpperCAmelCase_       				=			initializer_range
		UpperCAmelCase_       				=			layer_norm_eps
		UpperCAmelCase_       				=			image_size
		UpperCAmelCase_       				=			patch_size
		UpperCAmelCase_       				=			num_channels
		UpperCAmelCase_       				=			qkv_bias