




from itertools import compress, repeat
from math import ceil, sqrt







def       _a (		SCREAMING_SNAKE_CASE_				:							int	):

					if num <= 2:
										return []
					if num == 3:
										return [2]

					# Odd sieve for numbers in range [3, num - 1]
					__lowerCAmelCase							  =			bytearray(b"\x01"	) * ((num >> 1) - 1)

					for i in range(3 , int(sqrt(SCREAMING_SNAKE_CASE_	)	) + 1 , 2	):
										if sieve[(i >> 1) - 1]:
															__lowerCAmelCase							  =			i**2
															__lowerCAmelCase							  =			repeat(
															    0 , ceil((num - i_squared) / (i << 1)	)	)

					return [2] + list(compress(range(3 , SCREAMING_SNAKE_CASE_ , 2	) , SCREAMING_SNAKE_CASE_	)	)


if __name__ == "__main__":
					import doctest

					doctest.testmod()










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


UpperCamelCase__            =     logging.getLogger(__name__)







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

					return parser.parse_args()







def       _a (		):
					__lowerCAmelCase							  =			parse_args()
					__lowerCAmelCase							  =			88_88
					__lowerCAmelCase							  =			int(os.environ["SM_NUM_GPUS"]	)
					__lowerCAmelCase							  =			json.loads(os.environ["SM_HOSTS"]	)
					__lowerCAmelCase							  =			len(SCREAMING_SNAKE_CASE_	)
					__lowerCAmelCase							  =			os.environ["SM_CURRENT_HOST"]
					__lowerCAmelCase							  =			hosts.index(SCREAMING_SNAKE_CASE_	)
					__lowerCAmelCase							  =			"INFO"

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


if __name__ == "__main__":
					main()




