





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


A__:  Union[str, Any]       					=					logging.getLogger(__name__)



def 							lowerCAmelCase_				(    ):
    UpperCamelCase__:					List[Any]												=      ArgumentParser()
    UpperCamelCase__							,				UpperCamelCase__:					Dict												=      parser.parse_known_args()
    for arg in unknown:
        if arg.startswith(("-", "--")):
            parser.add_argument(arg.split("=")[0])

    return parser.parse_args()



def 							lowerCAmelCase_				(    ):
    UpperCamelCase__:					Optional[int]												=      parse_args()
    UpperCamelCase__:					str												=      88_88
    UpperCamelCase__:					Dict												=      int(os.environ["SM_NUM_GPUS"])
    UpperCamelCase__:					Dict												=      json.loads(os.environ["SM_HOSTS"])
    UpperCamelCase__:					int												=      len(A_)
    UpperCamelCase__:					int												=      os.environ["SM_CURRENT_HOST"]
    UpperCamelCase__:					Dict												=      hosts.index(A_)
    UpperCamelCase__:					Optional[Any]												=      "INFO"

    if num_nodes > 1:
        UpperCamelCase__:					str												=      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:
        UpperCamelCase__:					Optional[int]												=      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()








def 							lowerCAmelCase_				(    A_  ,A_  ,A_):
    UpperCamelCase__:					Optional[int]												=      [1 / first_term]
    UpperCamelCase__:					int												=      1 / first_term
    for _ in range(number_of_terms - 1):
        first_term += common_difference
        arithmetic_progression.append(A_)
    UpperCamelCase__:					str												=      [1 / step for step in arithmetic_progression]
    return sum(A_)


if __name__ == "__main__":
   import doctest

   doctest.testmod()
   print(sum_of_harmonic_progression(1 / 2, 2, 2))

